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FACILITATING SYNCHRONOUS COLLABORATION AMONG DISTRIBUTED AGENTS IN THE AIR TRAFFIC MANAGEMENT SYSTEM: A DESCRIPTIVE STUDY

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School o f The Ohio State Universify

By Jodi Heintz Obradovich, M S.

*****

The Ohio State University 2001

Dissertation Committee Approved by Philip J. Smith, Advbor

David D. Woods dvisor Charles Billings Department of Didustriai and Systems Engineering

' . îMte:»î UMl Number 3031238

UMl*

UMl Microform 3031238 Copyright 2002 by Bell & Howell Information and Leaming Company. All rights reserved. This microform edition Is protected against unauthorÈed copying under Title 17, United States Code.

Bell & Howell Information and Leaming Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 Copyright, by Jodi Heîntz Obradovich 2001 ABSTRACT

Work today is more cognitive than ever before. Workers participate in more teams and interact with more people having diverse expertise. This allows for multiple skills and perspectives to be brought to bear on problem-solving situations. With these changes arises the need to explore how people with different levels of expertise and diverse knowledge actually work together in the course of their “inter-situated.” activities. The emerging technologies to support collaborative work have the potential to enhance not only the effectiveness of intra-organizational teams but also inter- organizational collaborative teams. A rich example of inter-organizational cognitive teamwork can be found in the United States AirTraffic Management (ATM) System. The ATM System is an ongoing and dynamic distributed cognitive system with tremendously high stakes. Because of the cognitive complexity of managing the NAS, tasks are decomposed in a way that limits the amount of data and knowledge that each individual needs in order to do his or her work. When this assumption of task independence is inadequate, however, it is necessary for the responsible individuals to interact. An example of this is pre-flight planning, which is rapidly increasing fn the extent to which there is task interdependence among FAA traffic management staff and airline dispatch staff. As a result, there is a great need to develop effective methods for both groups to gather and synthesize data and to work coUaboratively decide how to act.

n ' , -2 t/l"': ’■ ■ “ y The research described ia tWs dissertatioa is a descriptive study of the performance of dyads engaged in a specific collaborative problem-solving task focusing on inefficiencies in the ATM system. The investigation focuses on how problem solving proceeds when the team members are from these two distinct yet interdependent organizations with unique knowledge and expertise, are spatially distributed, have a shared display available to them, and must communicate by telephone rather than face to face. Also of interest is how the data provided by a shared cognitive display is used by the participants, and how this tool participates as part of the cognitive system in the problem-solving process by facilitating the sharing of uniquely held knowledge. The findings of this study are presented and the effectiveness of the artifacts used is evaluated. Suggestions are proposed for the design of collaborative support tools and for process improvements to the distributed work processes, such as the one studied. Contributions of this work within the fields of cognitive systems engineering, interaction technologies (e.g., computer supported collaborative work), and the National Airspace System are discussed. Questions for future research are posed.

Ut ...

To my husband and soulmate Tony

and my children Nick, Clare, and Rebekah

IV ACKNOWLEDGMENTS

In order to fairly and accurately thank those who have contributed to my successes^ I would have to do two things - while reaching back to by grade school years, recall every person who has guided and influenced my love of leaming and thirst for knowledge and then put into words the debt of gratitude and appreciation I owe to each one. The first task is formidable, and the second requires using heart-full words in a way in which I am not skilled. So for all those t do not mention here, thank you. The following people have had a tremendous lasting impact on the most recent years of my life, and I thank them humbly and sincerely. I would first like to thank my parents, Tony and Joyce Heintz, for instilling their special work ethic, a love of leaming and discovery, and other qualities that have gotten me to where I am today. I thank my other family, the Obradoviches, for their unshaken confidence in me in this pursuit. To my next door neighbors, Bev and Bill Low, who are really part of my Columbus family who just happen to live next door, thank you for being there for my children as they were growing from babies, to toddlers, and now to soon-to- be young adults. Having “grandparents” like you was so good for them as their mom was being student. I want to thank the members of my dissertation committee, Philip Smith, David Woods, and Charles BQlings for supporting me in my academic work, wading through, all the details of my dissertation, and helping me to find the light at the end of the tunnel. I began my career-as-student under the advisement of David Woods, and his continued interest in and support of my work when my research moved me to another advisor, only served to make me a better muIti-discipKned practitioner of cognitive systems engineering. I feel most fortunate that I was able to collaborate with David on otherprojects that served to enrich my experience during my years at Ohio State. The encouragement, kind words, and wisdom that Charlie Billings shared with me over the years meant much to me. I appreciate your gentle way of critiquing my work and of nudging me in a more productive direction. Thank you, Dave and Charlie, for your unshaken belief that i have the skills and knowledge necessary to become a paitner with you in the work we have before us. The confidence you have in me has helped me to build it within myself. I express my most sincere and highest form of appreciation to my advisor, Phil Smith, for his guidance, encouragement, and understanding throughout the entire period over which these studies were conducted. Phil, your insight and suggestions were most valuable at every step in my path to the doctoral degree. Your patience, understanding, and support as I attempted to balance the demands of academia, while trying to raise my children in a loving and supportive home, made my experience that much more positive. You let me keep family as my highest priority without ever making me feel as though I was shortchanging my work for you, and yet you still challenged me to stretch and grow intellectually. I look forward to working with you as your colleague, and to our continuing friendship. I am indebted to the contribution of time and resources by representatives of both the airline and the FAA Air Route Traffic Control Centers with whom I worked. I thank Joe Bertapelli for his enthusiasm and for his help in allowing the dispatchers to participate in my study. IBs time and effort that went into organizing this effort is very much appreciated. I appreciate the time spent and planning done by Roger Beatty in order to make this project work. I thank him for the use of his cubicle, his computer, and his availability when there were technical difficulties. Very special thanks go to Tim Schmitz: who always came to the rescue when the conferencing technology was challenging me and winning. E also thank the managers at the Atlanta, Boston, Chicago, Minneapolis, and New York En Route Centers for inviting me to

VI come and conduct my research and for permitting their traffic managers to participate. The participants themselves deserve to be recognized because they enthusiastically volunteered to participate in something they knew little about and then engaged their dyad partners in conversations that led to the results of my study and allowed me to complete this dissertation. Unquestionably, this work would not have been possible without them. I thank the management team at my favorite fast-food establishment for offering me a place to park my car so that I did not have to spend endless numbers of minutes searching for a parking spot. I also appreciate them for my rent-free workspace, and for their willingness to be engaged in conversation when 1 needed a diversion from my work. Two people who helped me immeasurably, but were behind the scenes, are Roger Chapman and Joe Jezerinac. I thank Roger, a fellow graduate student, for his friendship and support as we both pursued this arduous journey. I appreciate his design and development of the C-SLANT tool that provided me an environment in which to create the slideshows for my research. I thank Joe for all his work and expert help with the POET application from which I was able to search the immense database of aviation data in order to create the scenarios on which the participants based their conversations. Rnally my biggest thanks go to my very best friend and soulmate, Anthony Obradovich, and to our children, Nicholas, Clare, and Rebekah. Tony, without your love and caring, your support and understanding, your help and encouragement, and your never-ending patience, I simply would not be been able to succeed in this endeavor. You have always encouraged me to follow my dreams and to continue my pursuit of this one, even though it made our life much more complicated. You are more deserving of the honors that this work has reaped than I am. Nick, Clare, and Rebekah, thank you for your patience and understanding, your concerns over my too late, and often sleepless, nights, and your continued support and belief that I could do this. My biggest fear while I was pursuing this degree was that

vu you would see education as something that took your Mom’^s time away from you, rather than something exciting and fun to pursue. Thankfully, those fears have not come true, and I am thrilled at your continuing desire to learn and discover, to read and ask questions, to be the best that you can be in all that you attempt. You make me proudt

This work was supported under a grant from the FAA Office of the Chief Scientist for Human Factors.

Jodi Heintz Obradovich November 30,2001

vut

!• VITA

Previous Education

M.S., Industrial and Systems Engineering, 1996, The Ohio State University Specialization: Cognitive Systems Engineering

Professional Experience

1998 to present Cognitive Systems Engineering, Inc., Columbus, OH Cognitive Systems Engineer/Analyst

1994 to present The Ohio State University, Columbus, OH

1986 to 1996 AT&T Bell Laboratories, Columbus, OH

1993 to 1996 Product Documentation Coordinator 1990 to 1993 Project Manager 1988 to 1990 Technical Education Planner 1986 to 1988 Software Developer

Professional Memberships

Human Factors and Ergonomics Society (HFES)

• Medical Systems and Rehabilitation Technical Group • Co^itive Engineering and Decision Making Technical Group Aerospace Technical Group TrainingTechnical Group

Supporting Education

B.S., Computer Liformation Systems, 1986, DeVRY Institute ofTechnolo^, Columbus, OH

M.S., Psychology, 1980, (All but thesis). Central Washington University, Ellensburg, WA Specialization: Counseling Psychology

BA., Psychology, 1976, Gonzaga University, Spokane, WA

ix ."-Ay;- : i " ' '

. .1: _ . ^- • .^* ■ ...

Awards

• The Jerome H. Ely Human Factors Article Award for the most outstanding article in Human Factors Journal daring 1999, The Human Factors and Ergonomic Society, August 2000.

• Finalist - Best Student Paper, Human Factors & Ergonomics Conference, 1996

• Best Student Paper, Training Technical Group, Human Factors & Ergonomics Conference, 1996

PUBLICATIONS

Journal Articles Guerlain, S.A., Smith, P J., Obradovich, J ü ., Rudmann, S., Strohm, P., Smith, J.W., Svirbely, J. (1996) Dealing with brittleness in the design of expert systems for immunohematology. JmmnnoAemarofogy,I2(3),10I-L07.

Obradovich, J.H. and Woods, DJD. (1996). Users as designers: How people cope with poor HCE design in computer-based medical devices, hi Tfie Journal o f the Human Factors and Ergonomics Society, 38(4), 574-592.

Obradovich, J.H., Smith, P J., Guerlain, S.A., Rudmann, S., Strohm, P., Smith, J.W., Svirbely, J., & Sachs, L. (1996) Empirical evaluation of the Transfusion Medicine Tutor. Immunohematology, 12(4), 169-174.

Book Chapters Guerlain, S., Smith, P J., Smith, J., Rudmann, S., Obradovich, J ü ., & Strohm, P. (1995). Decision support in medical systems, hi R. Parasuraman & M. Mouloua ^ds.). Automation and human performance: Theory and applications. Earlbaum, 385-406.

Obradovich, J.H., Smith, P J., Guerlain, S., Rudmann, S., Strohm, PX.,.Smith, J., Svirbely, J., & Sachs, L. (1996). The role of proactive and embedded training in the design of an expert system for teaching transfusion medicine, hi M. Mouloua & J. M. Koonce (Eds.), Human-Automation Interaction: Research and Practice. Mahwah,NJ.: Lawrence Erlbaum Associates, Publishers, p. 225-232. Conference Proceedings and Presentations

Obradovich, I,H., Smith, P J, Stephanie A. Guerlain, Rudraan, S., Jack W. Smith, J.W. (2000), Field evaluation of an intelligent tutoring system for teaching problem-solving skills in transfusion medicine. InProceedings o f the Human Factors and Ergonomics Society 44nd Annual Meeting, 2:338-341.

Obradovich, J,H., Smith, P J. Denning, R„ Chapman, R., Billings, C £ „ McCoy, E., & Woods, DD. (1998) Cooperative problem-solving challenges for the movement of aircraft on the ground. In Proceedings o fthe Human Factors and Ergonomics Society 42nd Annual Meeting. 0057-0061.

Obradovich, JÜ ., Smith, PJ., Guerlain, S., Smith, J.W., Rudmann, S., Sachs, L , Svirbely, J., Kennedy, M., & Strohm, PE. (1996). Design concepts for an instructional tool: Teaching abductive reasoning in antibody identification. In M J. Tauber (Ed.) CHI 96 Conference Companion, 13-14.

Obradovich, J ü ., Smith, P.J., Guerlain, S. Rudmann, S., Strohm, P., Smith, J., Sachs, L , Denning, R. (1996). The Transfusion Medicine Tuton Using Expert Systems Technology to Teach Domain-Specific Problem-Solving Skills. In F. Claude, Gauthier, G., & A. Lesgold (Eds.) Intelligent tutoring systems: Third international conference on intelligent tutoring systems. New York: Springer-Verlag, 521-530.

Obradovich, JJI., Guerlam, S., Smith, P.J., Smith, J.W., Rudmann, S., Sachs, L., Svirbely, J., Kennedy, M:,% Strohm, PX. (1996). The Transfusion Medicine Tuton The use of expert-systerris technology to teach students and provide support to practitioners in antibody identificatfon. In D.C. Edelson & E.A. Domeshek (Eds.) Proceedings o f the International Conference on the Leaming Sciences, 1996, Charlottesville, VA: AACE, 249-255.

Obradovich, J ü . (1996). The Transfusion Medicine Tuton A model for the design and use of expert systems for teaching. In Proceedings o fthe Human Factors and Ergonomics Society 40th Annual Meeting, 1055-1059.

Smith, PJ., Obradovich, JÜ ., Guerlain, S.A., Rudmann, S., Strohm, P., Smith, J.W. (1998). Successful Use of an Expert System to Teach Diagnostic Reasoning for Antibody Identification.. In F. Claude, Gauthier, G., & A. Lesgold (Eds.) Intelligent tutoring systems: Fourth international conference on intelligent tutoring systems. New York: Springer-Verlag.

XI FIELDS OF STUDY

Major Field Didustrial and Systems Engineering

Major Area of Spectalizatioa Cognitive Systems Engineering Dn Philip L Smith, Department of Industrial and Systems Engineering

Minor Area of Specialization Decision Making Dn Barbara Mellers, Department of Psychology

Minor Area of Specialization Visual Communication Dr. Elizabeth Sanders, Department of Industrial Design

XII TABLE OF CONTENTS

ABSTRACT...... H ACKNOWLEDGMENTS ...... v VITA...... xi U ST OF TABLES...... xc UST OF FIGURES...... xxi CHAPTER l INTRODUCTION...... 1 1.1 Significance o fPresent Work...... 4 1.2 Goals ...... 5 1.3 Dissertation Overview ------.6 CHAPTER 2 FRAMEWORK FOR ANALYSIS: A REVIEW OF THE LITERATURE...... 8 2.1 Introduction ...... 8 2.2 Communication within Groups/Teams ...... 9 2.2.1 Introduction...... 9 2.2.2 Perspective Taking in Conversation...... 10 2.23 Establishing Mutual Understanding through Reference ...... 12 2.2.4 Collaborative Nature of Communication______14 2.2.5 The Impact of Interaction Technologies ...... 16 2.2.5 Summary: Communication in Groups/Teams------16 2.3 Problem Solving/Decision Making in Complex Environments. ------17 23.L Introduction------17 2.3.2 Dimensions of the Problem ...... 18 2.3.3 Models of Problem-Solving ...... 19

XÜL 2.3.3.1 Descriptive Models ...... 19 2.3.3.2 Computational Models ...... 21 2.3.4 Team Problem Solving ...... 23 2.3.4.1 Group Dynamics Literature...... 26 2.3.4.2 The Nature of the Task...... 31 2.3.4.3 Prescriptive Models and Formal Procedures ...... 33 2.3.4.4 Summary: Team Problem Solving...... 40 2.4 Use ofTechnologies by Groups ...... 41 2.4.1 Introduction...... 41 2.4.2 Research Findings for Groups using Interaction Technologies ...... 45 2.42.1 Cooperative tasks...... 47 2.4.22 Taste involving conflict ...... 53 2.42.3 Mixed-motive taste ...... 55 2.4.3 Summary: Use of Interaction Technologies ...... 57 CHAPTER 3 RESEARCH CONTEXT...... 61 3.1 Introduction ...... 61 3.2 Air Traffic Management System ...... 61 3.3 Air Traffic Control (ATC) System ...... 62 3.3.1 En Route Environment...... 63 3.4 Traffic Flow Management System ...... 6S 3.4.1 Differing Goals and Priorities ...... 66 3.4.2 En Route Traffic Manager------67 3.4.3 ACC Dispatcher. ------68 3.5 Summary ...... 69 CHAPTER 4 METHODS ______70 4.1 Introduction ...... 70 4.2 Methodology ...... 71 4.2.1 Participants ...... 71 4.2.2 Setting ...... 72 42.3 Design ------72 4.2.3.1 Scenarios...... 73 4.2.3.2 Guiding questions------74 4.2.4 Procedure______76 4.2.4.1 Training ------76

XIV 4.2A2 Task Instructions...... 77 4.3 Tools...... 78 4 3 .1 Tools used by participants ...... 78 4.3.1.L Language ...... 78 4.3.1.2 Slideshow ...... 79 4.3.1.4 Microsoft Windows® MetMeeting ...... 80 4.3.1.5 Telephone ...... 81 4.3.1.6 Summary; Tools Used by Participants ...... 82 4.3.I.7 Tools used for data collection ...... 82 4.5 Task...... 83 4.6 Summary ...... —------85 CHAPTER 5 RESULTS AND DISCUSSION...... 86 5.1 Introduction. ------86 5.2 Scenarios...... 88 5.2.1 Scenario I. Chicago to Atlanta ...... 88 5.2.2 Scenario 2. Dallas-Ft. Worth to Atlanta ______.93 5 2 3 Scenario 3. Dailas-Ft. Worth to Nfînneapoüs-St. Paul ...... 39 5.2.4 Scenario 4. Chicago to Boston ------104 5.2.5 Scenario 5: Dallas-Ft. Worth to Newark...... 109 5.3 Knowledge Sharing: Distributing the knowledge base to match the locus of control ______113 5.3.1 Introduction______113 5.3.2 Airline/Center Communication/Collaboration------117 53.3 Air Traffic Management and Airline Considerations ______121 5.3.4 Arrival Flow Management Strategies ------122 5.3.4.1 Arrival fix balancing ______123 53.4.2 Ground delays and ground stops ______131 53.4.3 Time-based metering ______140 5.S.4.4 Alternate routing------141 53.43 Delay vectoring ------146 5.3.4.6 Altitude Separation ______148 5.3.5 Arrival Flow Management Constraints ______151 5.33.1 Runway configuration______151 533.2 Arrival rate/crossing traffic ______152 5.3.53 Peak arrival times------153 53.6 Airline Considerations ______153 5.3.6.1 Pilot Strategies ...... 154 5.3.6.2 Fuel consumption...... 157 5.3.63 Federal Airline Regulations (FARs) ...... 158 5.3.6.4 Ground delays versus airborne holding ...... 159 5.3.6.5 Airline Intra-organizational differences in priorities ...... 160 5.3.6.6 Flight Scheduling ...... 162 5.3.7 Unique proposals ...... 164 5.3.7.1 Utilize other close-in airports ...... 165 5.3.7.2 Dynamic redesign of the airspace ...... 168 5.3.8 Tools Used by ATM System Actors ...... 170 5.3.8.1 Flight Progress Strips ...... 170 53.8.2 TSD/ASD ...... 175 53.8.3 CTAS ...... 175 5.3.8.4 Monitor Alert ...... 176 53.8.5 FSM ...... 177 5.3.9 Summary...... 178 5.4 Communication and Collaboration...... 185 5.4.1 Introduction...... 185 5.4.2 The Rote of Cognitive Artifacts: Building Shared Perspectives through Reference...... — ...... 186 5.4.2.1 Introduction------186 5.4.2.2 Physical copresence ------187 5.4.23 Linguistic copresence...... — 188 5.4.2.4 Virtual copresence...... 188 5.4.2.5 Establishing linguistic and virtual copresence through reference ______192 5.4 2.6 Monitoring and revising utterance plans ...... 201 5.4.2.8 Summary and discussion ...... 203 5.4.3 (Re)prcsenting Experiences to Build Common Ground ------307 5.4.3.1 Bitroduction------207 5.4.3.2 Using storytelling as explanation ______208 5.4.3.3 Using stories as a tool for diagnosis ______209 5.4.3.4 Story triggers memory event leading to the sharing of new knowledge.... 211 5.4.35 Summary and discussion------213 5.4.4 Coping with Uncertainty when Data and Knowledge are Unavailable _____ 214 5.4.4.1 Introduction------214 5.4.4.2 “Filling in” for unavailable data ______215 5.4.43 Reluctance to simplify interpretations ______217 5.4.4.4 Summary and discussion______222 5.45 Effects of Dtcomplete Situation Assessment______223 5.4.5.1 Dttroduction223 S.4.5.2 Examples of Incomplete Situation Assessment ...... 224 S.4.4.4 Summary and discussion...... 235 5.5 Barriers (Designed into the Artifact) to Problem Solving 238 5.5.1 Lack of salience...... 238 5.5.2 Data in the Wrong Format ...... 239 5.5.3 Limitations of One-at-a-Time Sequential Views...... 243 5.6 Overall Discussion of Findings 245 CHAPTER 6 CONCLUSION 246 6.1 Introduction 246 6.2 Issues Specific to the Aviation Community 248 6.2.1 Characterization of the Aviation Research Context ...... 248 6.2.2 Aviation-Specific Findings ...... 250 6.3 Evaluation of Tools Used in Present Study 257 6.4 Issues for the Design of Distributed Collaborative Work Environments 263 6.4.1 General Characteristics of Distributed Environments ------263 6.4.2 Applying the Findings to Distributed Collaborative Work Environments 264 6.5 Future Tool Development 268 63.1 Allow for an fiiteractive Search for Data to Support the Dynamic Problem Solving Process, ______270 63.2 Provide a History of the Diteraction So That the Problem Solvers Are Able to See Where They Have Been to Better Decide Where They Need to G o 271 6.5.3 Provide Affordances in the Telepointing Device that Allows Each Participant Ease of Taking Control and Using the Tool ______271 6.5.4 Allow the Ability for Different Representations of the Data Which May Produce Different Insights ...... 271 6.53 Summary...... 272 6.6 Process Design for Distributed Collaborative Problem Solving 272 6.6.1 Combine asynchronous and synchronous capabilities ------273 6.6.2 Facilitator during synchronous interaction ______274 6.6.3 Communication and Interaction Protocols/Establishing Conventions of Use 274 6.7 Questions for Future Research 275 6.8 Concluding Remarks 276 ElEFERENCES 111 GLOSSARY 331 APPENDIX A: TRAINING 340 APPENDIX B: INSTRUCTIONS 342 APPENDIX C: SUBJECT FORMS and DEMOGRAPHICS 343 LIST OF TABLES

TABLE PAGE

2.1 Comparative Views of Problem-Solving Stages ...... 34

2.2 Distance-spanning and time-bridging media/channels ...... 44

3.1 Broad view of the AirTraffic Management System ...... 63

4. L Study design - Scenarios used and number of dyads per scenario — .74

5.1 Transcription Scheme ------87

5.2 Alternative solutions proposed by dyad within each scenario ...... 183

5.3 Knowledge shared between dyad partners during their discussions. ..184

5.4 Unavailable data categories by dyad ...... 215

53 Scenario 1 - Dyad I: Departure Dates and Time were parameters that were not mentioned aloud by the dyad. ______236

5.6 Scenario 2 - Dyad I: Air Time was not one of the parameters that was mentioned aloud------.234

6.1 Evaluation of artifacts used by participants------362

C-I. Traffic Manager Participants Demographics ______345

C-2. Dispatcher Participants Demographics ------347 LIST OF FIGURES

nOURE PAGE

3.1 Air Route Traffic Control Centers (ARTCC)...... 64

4.1 Example of how a slide allows relevant data to be chunked ...... 80

5.1 Slide 1 of Scenario 1: Chicago to Atlanta ...... 90

5.2 Slide 2 of Scenario 1: Chicago to Atlanta ...... 91

5.3 Slide 3 of Scenario I: Chicago to Atlanta...... 92

5.4 Slide 1 of Scenario 2: Dallas-Fort Worth to Atlanta ______94

5.5 Slide 2 of Scenario 2: Dallas-Fort Worth to Atlanta ______95

5.6 Slide 3 of Scenario 2: Dallas-Fort Worth to Atlanta ______96

5.7 Slide 4 of Scenario 2: Dallas-Fort Worth to Atlanta ...... 98

5.8 Slide I of Scenario 3r Dallas-Fort Worth to NCnneapoIis-St Paul... 100

5.9 Slide 2 of Scenario 3: Dallas-Fort Worth to Minneapolis-St Paul... 101

5.10 Slide 3 of Scenario 3: Dallas-Fort Worth to Minneapolis-St. Paul... 102

5.11 Slide 4 of Scenario 3: Dallas-Fort Worth to Minneapolis-St. Paul... 103

5.12 Slide 1 of Scenario 4: Chicago to Boston ______104

5.13 Slide 2 of Scenario 4: Chicago to Boston ______106

5.14 Slide 2 of Scenario 4: Chicago to Boston ...... 107 5.15 Slide 4 of Scenario 4: Chicago to Boston ...... 108

5.16 Slide I of Scenario 5 - Dailas-FL Worth to Newark ...... L10

5.17 Slide 2 of Scenario 5 - Dallas-Ft. Worth to Newark ...... I ll

5.18 Slide 3 of Scenario 5 - Dallas-Ft. Worth to Newark ...... 112

5.19 Reference using proper names of geographical locations in Scenario I - Chicago to Atlanta ...... 195

5.20 Data available with the Table of Slide I of Scenario 2 - Dallas- Ft. Worth to Atlanta ...... 196

5.21 Dallas-Ft. Worth to Atlanta - Slide 2 ...... 217

5.22 Slide 1 of the Scenario Dallas-FL Worth to Newark...... 220

523 Slide that the Dyadi.t partners are viewing while discussing scenario using an incorrect arrival timeframe...... 225

5.24 Diconect assumption due to incomplete situation assessment------230

525 Illustration of selective sampling of data already considered ...... 232

5.26 Alternate sources for determining arrival and departure airports ...... 236

5.27 DepaitTime metric is divided between two lines, leading to an inaccurate assessment of the situation...... 238

5.28 Comparing fuel usage across conditions ______239

5.29 Converting times from Zulu to EDT...... 240

5.30 Converting Zulu times to CDT.------241

531 Converting Zulu time to EDT.______242

5.32 Slide 2 of Scenario 5 - DFW to EWR ______244

533 Slide I of Scenario 5 - DFW to EWR ...... 244 A-1 Description of the kinds of data found on the first slide of the scenarios...... 340

A-2 Description of the kinds of data found on the second slide of the scenarios...... 341

A-3 Description of the kinds of data found on the third slide of the scenarios...... 341 CHAPTER 1

INTRODUCTION

"Work today is more cognitive than ever before. Workers are better educated and [often] more autonomous. Organizations are larger, more geographically distributed, and more compIex?’;CBinholt, SprouE& Kiesler, 1990, p. 321). Workers participate in more teams^ and mtemct with moreipepple having diverse expertise. This allows for multiple skills smdperspectives to be brought to bear on problem-solving situations. With these changes m i^ th e need to explore how people with different levels of expertise and diverse Jj^owle^dge actually work together in the course of their “inter-situated” activities. The emerging technologies to support collaborative work have the potential to enhance not only the effectiveness of intra-organizational teams but also inter-organizational collaborative teams. Many organizations are joining with other organizations to collaborate on joint endeavors (e.g. new product innovations and biomedical research). These collaborations are generally narrowly focused and limited in time. A rich example of inter-organizational cognitive teamwork can be found in the United States Air Traffic Management (ATM) System. The ATM System is not a simple inter-organizational collaboration, with a limited scope and timeffame. Rather, it is an ongoing and dynamic distributed cognitive system with tremendously high stakes. Today, approximately60,000 flights of commercial, military, and general aviation traffic occur daily in the U.S. National Airspace System (NAS)*, and that number is projected to increase three to five percent armually for the next 15 years (FAA 2000). This increase in air traffic will not be accompanied by a corresponding increase in available airspace, and yet, the ATM system will need to accommodate the rising number of aircraft while continuing to maintain safety and efficiency (Chang, Howard, Oiesen, Shisler, Tanino, & Wambsganss, 2001). Because of the cognitive complexity of managing the NAS, tasks are divided in a way that limits the amount of data and knowledge that each individual needs in order to do his or her work. However, when the assumption of task independence is inadequate, it is necessary for the responsible individuals to interact (Smith, 1999). One of the main tasks within the Traffic Flow Management (TFM) component of the ATM is pre- flight and traffic flow planning. A key feature of this process is its high level of task interdependence. In recent years, the National Airspace System (NAS) architecture has undergone significant change (Kerns, Smith, McCoy, & Orasanu, 1999; Smith, Billings, McCoy, & Orasanu, 1999; Smith, Billings, Woods, et al., 1997; Smith, McCoy, Orasanu et al., 1997; SnUth, McCoy, Orasanu et al., 1995). These changes reflect an increasing emphasis on giving air carriers greater flexibility in making alternative flight plans and thus becoming partners in the Air Traffic Management (ATM) System with the FAA in the management of traffic flow. The impacts of these changes have been studied to understand their effects on the locus of control and access to the knowledge and data necessary to make the best use of this control (Smith, Klopfenstein, McCoy et al., 1999) in managing the NAS. A theme that has emerged fiom these studies is that significant inefficiencies can result if the person, or group who has control of a flight does not have direct access to the necessary data or knowledge (e.g., information about the goals, constraints such as weather and traffic, and priorities of either the air carrier or FAA) to make the best decision, or if the

This number reflects the number o f flights prior to September LI,2001. 2 person or group with, control does not initiate an interaction with the person or group that does have direct access to this data or knowledge. The research described in this dissertation is a descriptive study of the performance of dyads engaged in a speciRc collaborative problem-solving task. The investigation focuses on how such problem solving proceeds when the team members (a) are from two distinct yet interdependent organizations with unique knowledge and expertise, (b) are spatially distributed, (c) have a shared display available to them, and (d) must communicate by telephone rather than face to face. Also of interest is how the data provided by a shared cognitive display is used by the participants, how this tool has an impact as part of the cognitive system in the problem-solving process and how it facilitates the sharing of uniquely held knowledge. The interactions studied here take place between people from two organizations (i.e.. Federal Aviation Administration and a commercial airline) that have different cultural and group norms. The relationship between the FAA and air carriers has been one of coopération in the shared goal of assuring the safety of the airspace, but also one of conflicting goals. The FAA is concerned with the effidency of the airspace as it applies to the éase and effectiveness with which controllers can maintain the flow of traffic ouLof, between, and into the nation’s airports. The air carriers are also concerned'Wittyeffidency, but their concern is with the cost- effectiveness of that effidency and with their competitive position. This study arose out of recommendations suggested by Smith, Klopfenstein, McCoy, et al. (1999) as one step toward ameliorating the problem of data and information gaps that can lead to ineffidendes in the National Airspace System (NAS). Specifically, this study describes synchronous interactions occurring between members of a dyad (an Airline Operations Center (ACC) dispatcher and a FAA traffic manager), using a shared cognitive display that provides a rich environment, as they confront scenarios developed from actual data that demonstrate ineffidendes in the NAS. It is probable, given the differing goals of these organizations, that the traffic manager and dispatcher in each dyad-pair bring with them to the interaction different perspectives on how to approach and achieve the goals set before them in the research task. This study places participants of these organizations into the problem­ solving situation of achieving,a common goal, which is to arrive at a common definition of a problem in a scenario that suggests inefriciencies in a specific area of the NAS, and to then generate alternative solutions that could eliminate or reduce the inefficiencies they have jointly defined.

1.1 Significance of Present Work

The present study has significance to the aviation community, as well as to the research literatures on communication, group problem solving and interaction technologies. It provides a first step in examining how distributed, interdependent, inter-organizational teams collaborate to identify and solve a complex problem using interaction technologies to aid them in their interactions and communication. This research aids in filling the need to understand the relationship between the cognitive processes that spatially distributed practitioners use when problem solving, how they arrive at a mutual understanding and definition of the problem, and then move forward to identify potential solutions to that problem. Also, this study adds to the research literature on how participants use cognitive tools to enhance their problem solving, and how these tools can be considered a part of the distributed cognitive system. Finally, this research provides insight that will aid in the design of more effective collaborative systems, allowing practitioners who are spatially distributed to participate in more effective, efficient, and satisfying collaborations. Research on technologies that support, mediate, orfacilitate teamwork has focused more on developing and analyzing technological applications than on understanding and refining the basic theoretical issues involving the functioning of these multi-participant situations. Although there is a wealth of well-founded research in organizational and social psychology concermng group interaction, group dynamics, and the behavior of individuals in groups, “there is a lack of an integrative, systematic conceptual framework in computer-supported group [collaboration}, that can serve as a foundation for future research. Groupware reflects a change in emphasis from ‘using computers to solve problems’ to ‘using computers to facilitate human interaction and communication’ ” (Ramarapu, Simkin, & Raisinghani, 1999, p. 166). Understanding how the interaction technologies (specifically the shared display and the telephone) are used in this study allows for recommendations to be made that can lead to the design of interaction technologies and computer artifacts that will enable future collaborations to be maximally successful. This study of collaborative problem solving within and between organizations requires a multi-disciplinary perspective, drawing from the social, cognitive, and organizational fields of psychology, as well as from communications, cognitive science, organizational science, and cognitive systems engineering.

1.2 Goals

The goals of this descriptive study include the following:

• To develop a better.understanding of what factors influence coUaboratiombetweea spatially distributed, inter-organizational members of a dyad who have different priorities, perspectives and knowledge as they engage each other in a problem-solving task.

• To determine what knowledge the participants find relevant to share with each other as they identify problems found within the scenarios and generate solutions to those problems. • To identify the processes that the team members use to establish common ground and to share their unique perspectives as they proceed in identifying the problems present in the task scenario.

• To study how the dyad partners cope with data and knowledge that is not available to them but is needed for an accurate assessment of the situation.

• To study the use of the cognitive artifacts made available in this study for facilitating the collaborative process between these dyad partners.

• To begin to determine what tools and processes are needed to more effectively support synchronous communication, collaboration and problem solving between distributed intra- and inter-organizational problem-solving teams.

Within all of these goals is the objective to identify potential generalizations that will apply broadly to distributed work, while still providing insights specific to this aviation context.

U Dissertation Overview

Chapter 2 presents a literature review of research and models in the fields of communication, problem solving^dedsion making, and the mediation and/or facilitation of these by interaction technologies. The caveat that the readers must remember as they read this chapter is that, in reality, each of these research areas weave in and out of each other, so the apparent distinction between fields is artificial, and one must blend: them as one would weave difièrent colors of thread to arrive at a tapestry that reveals a common: theme. . Therefore, Chapter 2 describes the theoretical foundation upon which the present research is based. The conceptual frameworks presented in this chapter were selected to illustrate underlying concepts and issues that characterize various research perspectives, as well as to help develop an understanding of the cognitive processes of collaborative team communication and problem solving. Chapter 3 introduces the reader to the domain of study through a description of the Air Traffic Management (ATM) System. The roles played by FAA traffic managers and Airline Operations Center (ACC) dispatchers in that system and the interdependencies between them are described. Chapter 4 presents the research methodology, giving details of the participants, study design, procedure, tools used by the participants and those used by the researcher for data capture during the study, and a description of the task given to the participants. Chapter 5 includes the analysis of the data gathered, as well as a discussion of the results of this analysis. The analysis includes the knowledge that was shared between the participants in each dyad, solutions that were proposed, the part played by the shared representational display in the distributed cognitive system, how the participants dealt with uncertainty created by data unavailable to them, how the use of stories and analogies enabled the building of common ground, and the effects that incomplete situation assessment had on the interaction. Also provided in Chapter 5 is a discussion of the findings thatprdvide a foundation for providing recommendations of processes and artifacts in the design of future distributed collaborative problem solving systems. Finally, Chapter 6 sums up the results of these studies by evaluating the interactional effectiveness of the artifacts used in the study. Enhancements to make the artifacts more efficient are proposed and contributions of the research within the fields of cognitive systems engineering, interaction technologies (e.g., computer supported collaborative work), and the National Airspace System are discussed. Questions for future research are posed. CHAPTER!

FRAMEWORK FOR ANALYSIS: A REVIEW OF THE LITERATURE

2.1 Introduction

This chapter presents the conceptual and empirical framework upon which the present study is based by reviewing the relevant literature within a variety of disciplines and demonstrates the firm theoretical foundation established by previous researchers. As Checkland (1981) argues, the categories by which this review is organized “are man-made and arbitrary. It is not nature which divides itself into...psychoIogy, sociology, [communications], etc., it is we who impose these divisions on nature” (p. 60). Thus, it will become apparent to the reader how the separate disciplines reviewecf here have a unity that underlies the divisions that have been imposed. The difficulties and successes that arise in a collaborative interaction between cognitive actors can be thought of, very generally, as the essence of the communication process and the structure that is employed in that interaction. The cognitive tools employed by the actors to enhance the problem-solving process also play a part in that collaborative interaction. Therefore, the conceptual framework used for the study repotted here draws on research and theory from different areas relating to effective communication and collaboration. The major concepts of the

8 framework are ia the areas of communfcatron, problem solving and decision making, and the mediation and/or facilitation of these by interaction technologies" and the cognitive influences of these technologies that can affect the interaction. Cognitive systems engineering,provides the frame within which these multiple threads of reseaich are woven into a tapestry, enabling prediction of the emergent properties of the' resultitfg picture that cannot be done by any thread separately. In other wordsTnetwig^e conversational partners and the cognitive artifacts used in this study as a single cognitive system allows for a fuller understanding of what occurs in the collaborative interaction between these participants as they work to identify and solve a problem-solving task. This understanding provides insight into what may be required to design an environment that allows for the fullest collaboration between problem solvers.

2.2 Communication within Groups/Teams^

2.2.1 Introduction

Contemporary scholars view communication as the process by which people attribute meaning, form relationships, make decisions and solve problems (Frey, 1995). Communicatioa is a cooperative endeavor, an implicit social contract between speaker and listeners about how information is to be given and received (Person, 1999). Grice (1975) provides a general set of conversational guidelines in his Cooperative Principle, which states that speakers must attempt to follow certain conversational conventions or maxims so that their utterances are clear and avoid ambiguity (maxim of manner), informative without adding unneeded information (maxim of quantity), truthfiil with accurate information (maxim of quality), and

■ To follow Andriesseit (1996), the more general term “interaction technology” is used for electronic technology that is put in place to mediate and/or facilitate interaction. relevant (maxim of relation). Di order to ensure clear and unambiguous communication^ a speaker and listener collaborate to make the conversation successful- By engaging in the collaborative process of communication, conversational partners are able to take the other’s perspective into consideration, build shared perspectives, and establish mutual understanding in their problem­ solving endeavors.

2.2.2 Perspective Taking in Conversation

...perspective taking is an essential attribute of communication and emergentb meaning... . Hardin and Higgins, 1996, p. 40

Perspective-taking models of communication assume that individuals experience the world from different vantage points and the perspective one takes is influenced to some degree by that vantage point. Some of the components of a person’s perspective that are relevant to the study of cognition in communication and problem solving have been specified by Krauss andFussell (1988) as (a) background knowledge, beliefs, and attitudes, (b) current interpretations of events, (c) plans and goals, (d) social coritext, (e) physical context, and (f) the listener’s representation of the speaker’s perspective. In the context of face-to face conversation, collaborators participating in the interaction are able to gather information that understanding has occurred from a variety of sources. These include questions, comments, vocal back-channel responses (e.g., acknowledgments such as, “uh huh,” and assessments, such as

^ Even though arguments can be made that the tenns 'goup' and 'team' are distinctly different, the literature often does not reflect those distinctions. Because o f this ambiguity; how these terms are used in this review is reflective of the way they were used in the research being discussed. 10 “gosh,” “really”), and non-vocal back channels (e.g., smiles, head nods), as well as, their partners’ subsequent contributions to the conversation (the relevant next turn) (Sacks & Schegloff, 1979). This feedback allows the conversational partners to develop a mutual knowledge that can be built upon in subsequent messages. Feedback allows the participants to achieve a perspective that may not be obtainable in situations that do not allow such interaction to occur in message production. Also, the availability of feedback reduces the cognitive load of message production and comprehension because the speaker is aware on a moment-by-moment basis of the addressee’s understanding, and thus, there is less need to engage in the complex processing required to formulate effective models of the addressee’s knowledge constructed from prior assumptions (Schober, 1993). The speaker can also use additional messages to clarify any misunderstandings (Auer, 1984; Clark & Wilkes-Gibbs, 1986; Sacks & Schegloff, 1979). For example, the speaker may use “installment” phrases (Clark & Wilkes- Gibbs, 1986) to provide information incrementally, with pauses between these increments so the listener can provide feedback on whether or not he or she understands. Alternatively, the speaker can use “pre-sequences” (Jefferson, 1975), or preliminary queries (e.g., “You’ve heard of a metering program?”) to establish whether some body of knowledge is oris not part of the shared knowledge before creating a more detailed message, hr the same way, the listener can avoid some of the cognitive work involved in making sense of an ambiguous message by signaling a lack of understanding. Non-acceptance of an utterance due to misunderstanding leads to repair. In everyday conversations, repair is almost always initiated on the spot and is completed quickly. Schegloff (1991) shows how repair of perceived miscommunications serves as a means of maintaining both shared reference and appropriate social relations during conversations. He also illustrates how the flexibility of conversational language allows for imprecision and ambiguity because

II the entire interactive and situational context, not just a speaker’s words, is available for establishing mutual unders^ding among the conversational parmers. The perspective-taking research suggests that communicators take into account both the relatively stable aspects of another’s perspective, such as background knowledge and attitudes, as well as the more immediate situation and the state of current comprehension (e.g., Clark & Wilkes-Gibbs, 1986; Sperber & Wilson, 1986; Krauss & Fussell, 1991).

2.2.5 Establishing Mutual Understanding through Reference

As conversational partners interact, they are able to apply new knowledge to their assumptions about the others’ perspectives that can lead to the establishment of mutual understanding. Research Endings suggest that dyads use the collaborative process of reference as a way of building a joint perspective (Anderson, 1987; Lyons, 1977) and establishing mutual understanding (Clark & Wilkes-Gibbs, 1986). The idea behind this collaborative process of reference is that the partners accept mutual responsibility for each reference (i.e., the speaker must be confident that the referent will become mutually known to him or her and his/her listener) (Clark & Marshall, 1992.) This means that the speaker tries to establish the mutual belief that the listener has understood the speaker’s reference before the parmers continue.

-- V ’■ ■ Lyons (1977) specifies three basic types of reference: deixis, anaphora, and proper names. A deictic expression is used to point or gesture at some feature in the surrounding context and used to establish immediate physical co-presence (Hawkins, 1978) (e.g., “I want r/iar.”). An anaphoric expression is a definite pronoun used to refer to something that has already been introduced into the conversation and is thus linguistically co-present (e.g., “Every sector has a capacity, and when it’s forecast to go red, it’s overcapacity.”), fit the literature anaphora is often subsumed under deixis, rather than being a separate type of reference. A proper name is used to refer to something that is mutually known due to community

12 membership (e.g., for co-membership in the bTational Airspace System community: “Minneapolis-St. Paul” or “the Command Center”) (Clark & Schaefer, 1989). Copresence, whether due to physical, linguistic orcommunity membership, provides the evidence for “common ground" in comprehension between people engaged in conversation. Common ground can be defined as the set of knowledge, beliefs, and pre-suppositions that each conversational partner assumes are held by both, i.e., what they assume to be their mutual knowledge, mutual beliefs, mutual assumptions, and mutual attitudes (Clark & Carlson, 1992; Clark & Schaefer, 1989; Stalnaker, 1978). According to Clark & Marshall (1992), the strongest evidence that people are prepared to accept for the existence of mutual knowledge is physical copresence, which exists when the speaker, the listener, and the referent are physically and openly present together. The participants take as common ground what they are currently experiencing and what they have already experienced. This being so, the speaker can assume that the listener is attending to the fact that all three are co-present (assumption of attention), is doing so at the same time as the speaker (assumption of simultaneity), and both speaker and listener are drawing the same conclusions (assumption of rationality). When taking into consideration the timing of physical copresence in relation to the act of reference, three varieties of physical copresence can be recognized: potential, immediate, and prior. It may be that the listener is not paying attention to the referent, but it is in plain view. The speaker can say “this referent,” which then allows the listener to locate it and look at it, completing the requirements of physical copresence between speaker, listener, and referent. This type of copresence is called potential physical copresence, and the speaker can assume that the listener is able to locate the referent (assiunption of locatability) and will then be attending: (assumption of attention) to it at the same time (assumption of simultaneity) as the speaker with, the same understanding (assumption of rationality).

13 When both speaker and listener are focusing on the referent at the same time and the speaker says “this referent,” immediate physical copresence is occurring (assumptions of simultaneity, attention, and rationality). An instance o f prior physical copresence occurs when both speaker and listener have attended to the referent in the near past but may not be at the present moment. The speaker may say “that referent” and can assume that the listener is able to recall the earlier copresence of the referent, speaker, and listener (assumption of recallability). Linguistic copresence is when the mention of the object/referent and the conversational partners are openly present together. It includes all of the conversation up to and including the utterance currently being interpreted by the pair. Linguistic copresence requires all of the same assumptions as physical copresence but also requires understandability (i.e., that the listener will understand the speaker's reference and is assuming the existence of the referent in some world). Community membership is evidence that if something is universally known in a community then two people in that community can assume that they mutually know it. There are two assumptions required for mutual knowledge of something. First, the speaker must believe that he and the listener mutually know that they belong to the same communier (assumption of community co-membership), and second, the speaker must believe that everyone in that community knows that particular r/ii/ig (assumption of associativity). Often the establishment of mutual knowledge is by a combination of physical and linguistic copresence and mutual knowledge based on community membership.

2.2.4 Collaborative Nature o f Communication

From the dialogic perspective of conversation, meaning is socially situated and the meaning of an utterance can be only understood in the context of the particular situation in which it occurred. The communicative exchange is more than the combined outputs of two autonomous actors; it is a Joint accomplishment of the

14 conversational partners. Dialogic models state that the goal of communication is the achievement of inter-subjectivity or mutual understanding. As Rommetveit (1980) states, “Mutual understanding can[notJ... be accounted for in terms of either unequivocally shared knowledge of the world or linguistically mediated meaning" (p. 109). Instead it emerges from the process of interaction and is neither implicit in the knowledge that participants bring to the situation, nor is it explicit in the language. Clark's collaborative model of communication is perhaps the must fully articulated example of the dialogic perspective (Clark & Brennan, 1991; Clark & Schaefer, 1989; Clark & Wilkes-Gibbs, 1986; Issacs & Clark, 1987). The fundamental premise of the collaborative model of communication is that communication consists of more than a sequence of messages produced by participants. Meaning emerges from the cognitive process by which speakers and listeners come to agree that those messages have been understood and common ground is continuing to be established. By the principle of least collaborative effort, people should try to ground with as little combined effort as possible. However, what takes effort changes with the medium of communication (Clark & Brennan, 1991), and thus, communicators must use whatever techniques are available in a medium that will lead to the least collaborative effort. For example, m face-to-face conversation, the participants are typically co-present and can readily see and hear what the other is doing and looking at, and they can see oneanother. hi face-to-face interactions, via telephone conversations, and with some types of teleconferencing, conversational partners can hear each other's words and intonation, andean time turn taking. However, in these media, speech is ephemeral aifdfades quickly; whereas, email, answering machine, and chat features of on-line text-based conferencing, allow for reviewability. Revisability is possible in email, and to some extent in online conferences, hi face- to-face and telephone conversations most self-repairs must be done publicly.

15 Jà- %

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2.2.5 The Impact o f Interaction Technologies

Designing interaction technologies requires a consideration of the cost tradeoffs associated with establishing grounding that diffèrent media impose. Some of those costs are formulation costs (time and effort) of forming and revising utterances, production costs of producing an utterance, reception costs (e.g., listening is easier than reading unless trying to understand complicated instructions or abstract arguments), and understanding costs, which can be compounded when contextual cues are missing (Clark & Brennen, 1991). Another cost is asynchrony, which involves how people time their utterances (Jefferson, 1972). In media without copresence, visibility, audibility, or simultaneity, time is much less precise, so grounding techniques that rely on the precision of turn taking go up in cost (e.g., in media that allow only asynchronous interaction). There is also display cost, which involves the ease with which conversational partners can point to, nod at, or present an object as reference to support the speaker’s utterance.

2.2.5 Summary: Communication in Groups/Teams

This section focused on the importance of communication as a collaborative process that allows people to attribute meaning, form relationships, make decisions, and solve problems. One of the goals of effective communication is the establishment of mutual understanding and, therefore, common ground. It is important to understand that this cognitive process of grounding occurs through a continual updating of the perspectives of the conversational partners, such as background knowledge and attitudes, as well the immediate situation and the state of current comprehension. The collaborative process of reference is an integral part of building a shared perspective and establishing mutual understanding. Three basic types of reference are deixis, anaphora, and proper names, and it is through these

16 that physical and linguistic copresence, as well as conununity membership are established, making it possible for the partners to achieve common ground. The interaction technologies that are used by the conversational partners can impact the achievement of each of these forms of copresence. There are cost tradeoffs that are associated with each of the different media. These costs are measured by the amount of time and cognitive effort needed to form and revise utterances, to produce and receive utterances, as well as those costs associated with the ease with which conversational partners can use reference to support their utterances.

2.3 Problem Solyîng/Decision Making'* in Complex Environments

2.3d Introduction

The previous section focused on considerations that arise in designing an environment to support communication within a group. These considerations included the impacts of physical versus linguistic copresence, the extent of community membership, and the collaborative use of reference in building a joint perspective and establishing mutual understanding. Communication is a dynamic, collaborative achievement of theconversational partners situated in a particular context, where meaning emerges from the cognitive processes of interaction between these partners. Also, pràéntéd iii the previous section was the issue of cost tradeoffs that are associated v ^ d iff^ n t interaction technologies chosen to mediate/facilitate the interactioifahd how those costs can affect the establishment of -I#" common ground between conversational partners. Clearly, the impact of the communication environment also depends on the nature of the task. For this study, that task is problem solving. Specifically, the

* Even though one can argue that the terms ^probtem solving’ and ’decision making’ are distinct, they are used interchangeably in this thesis. 17

dir'rxyd--. ' '"if: V dyads (each consisting of one FAA traffic manager and one airline dispatcher) were presented with data regarding a real-world scenario that indicated a problem, and were asked to work together to develop and evaluate possible solutions to this problem. Thus, understanding the literature on task characteristics and models of problem-solving behaviors, as well as the literature on communication that was discussed in the previous section brings a broader perspective for understanding the focus and findings of the study reported in this paper.

2.5.2 Dimensions o f the Problem

In studying problem-solving models and behavior, it is important to understand how problems vary on a number of qualitative “dimensions.” Well- defined problems have the initial state, operators, and goals specified (e.g., solving an equation or adding numbers). With ill-defined o t ill-structured problems, any or all of the components are uncertain, (e.g., medical diagnosis) (Dunbar, 1998; Glass, Holyoak, & Santa, 1979; Newell, 1969). Because ill-structured problems do not have a predetermined path to a solution, the selection of what to do next must be made while the problem is in the process of being solved. In her investigation of complex, ill-structured problems, where solutions involve diverse sources of knowledge. Nit (1986) proposed that the following characteristics were important features influencing problem-solving performance:

“• A large solution space • Noisy and unreliable data • A variety of input data and the need to integrate diverse information • The need for many independent or semt-independent pieces of knowledge to [be integrated! to form a solution • The need to use multiple reasoning techniques

18 • The need for multiple lines of reasoning • The need for an evolutionary construction of the solution” (Nii, 1986, p.I03)

Another classification scheme is discussedby VanLehn (1989) who suggests that problem-solving tasks can be divided into two categories - knowledge-rich and knowledge-lean. Knowledge-lean tasks are those tasks requiring only the information that is provided in the instructions to solve the problem (e.g., puzzle solving, game playing, and logic). The second category suggested by VanLehn is the knowledge-rich task. Knowledge-rich task domains require many instructions to even begin to solve the problem. These types of problem domains (e.g., physics, medical diagnosis, air traffic management) may take years of experience in order to develop expertise in the task.

2.3.3 ModeU o f Problem-Solving

2.3.3.1 Descriptive Models

Descriptive theories of problem solving are concerned with how and why people think and act the way they do. Simon (1955) introduced the concept of bounded rationality by which he meant that people do not think rationally (i.e., using a normative model) because doing so requires excessive cognitive effort. Simon (1969; Newell & Simon, 1972) and his colleagues started investigating how people solve difficult problems. They used complex problems having no key element that would lead to the solution of the problem. Simon (1969) defined a complex system as “one made up of a large number of parts that interact in simple ways. In such systems the whole is more than, the sum of the parts, jin the sense that] given the properties of the parts and the laws o f their interaction, it is not a trivial matter to infer the properties of the whole” (p. 63). He focused on

19 characterizing the processes underlying problem solving, and by using concurrent verbalizations obtained from the problem solvers, he was able to identify the mental operations, representations, and strategies people use to solve problems. Therefore, Simon assumed that people are unable to calculate the optimal choice and proposed his decision model of "satisficing, ” This model implies that people think of options, one by one, and choose the first course of action that meets or surpasses some minimum criterion that satisfies them. Simon suggested that people “satisfice” because they are unable to recognize the optimal course of action. When satisficing, people often use rules-of-thumb or heuristics to aid them in their problem solving. Simon and his colleagues stress that complex problem solving consists of a search in a problem space and is goal-directed. Simon and Newell’s problem- solving-as-search theory can be described in terms of two cooperating sub-processes understanding and search. In this type of problem solving, a problem is well defined if the participant’s understanding of the problem produces a problem space, that is, an initial state, a set of operators, and a solution state description. The search sub-process then consists of strategies for moving fix>m state to state through the application of various operators until the goal state is achieved, A classic task, a knowledge-lean task as described by VanLehn (1989), used by Newell and Simon (1972) is the Tower of Hanoi problem. Lovett and Anderson (1996) investigated how previous experience influences solving particularclasses'of problems. Their findings indicate that problem solvers use both the cumht state of the problem and their previous successful use of particulttf opeiratore when deciding what to do next in solving a problem. Schunn and Dunbim (I9B(^ investigated the priming effect that solutions to one problem have on ’so l\^g ’à similar problem. They found that earlier experience on one problem did have a predictable effect on their current problem­ solving efforts. This has led to investigations as to what role previous experience plays in the current performance of solving a problem.

20 Much research has involved the examination of differences between novice and expert problem solvers. Glaser and Chi (1988) state that “investigations into knowledge-rich domains show strong interactions between structures of knowledge and processes of reasoning and problem solving.” These cognitive structures that contain information about aspects of a particular situation or a general class of situations have been referred to as schemas (Schank & Abelson, 1997) or schemata (Rumelhart & Ortony, 1977). Problem solving in complex domains has been characterized as finding an appropriate problem schema in long-term memory and filling this schema with the specific parameters of the problem at hand (Chi, Feltovich, & Glaser, 1981; Chi, Glaser, & Rees, 1982;Hinsley, Hayes, & Simon, 1977), and there is a rich research tradition on types of analogical reasoning that occurs when people problem solve (e.g., Gentner, 1989; Kokinov & Petrov, 2001; McClelland, 1995; Ross & Kennedy, 1990; Rumelhart & Abrahamson, 1973). The schema or analog that is retrieved is a crucial determinant of how the current problem is construed and subsequently solved because it determines what knowledge is brought to bear in generating hypotheses and strategies to solve it. Schemas are thought to guide how people process information, directing their attention and memory, which in turn causes some events to be noticed and remembered while others are not (Grzelak, 1982). These descriptive models have been proposed to describe how people problem solve and have led to the development of computational models, which have allowed researchers to further test their theories of human problem solving.

2.3.3.2 Computational Models

As scientific understanding of the phenomenon of analogy in problem solvinghas progressed, so too has the development of computational models that simulate a variety of the phenomenon in analogy and retrieval. (Gentner &

21

Iff: Vïp-: : &.Z : * I î :. ..J ' ; r „ - r ■ * 4' -- - -s Holyoak, 1997), One such model that is relevant to how experts reason is Case- Based Reasoning (e.g., Kolodner, 1993). Case-based reasoning (CBR) is a cognitive model that grew out of schema theory and focuses on the role of experience in reasoning and the relationships among reasoning, learning, and memory. This model maintains that people reason from cases or analogs and is supported by studies conducted in a variety of domains and in a wide range of tasks. Ross (1989) and Schunn & Dunbar (1996) have shown that people learning a new skill often refer back to previous problems to refresh their memories on how to do a task. Lancaster and Kolodner (1987) conducted research that showed that both novice and expert car mechanics use their own experiences and those of others to help them generate hypotheses about what is wrong with a car, to recognize problems, and to remember how to test for different diagnoses. Researchers at GTE (Kopeikina, Bandau, & Remmon, 1988) discovered that engineers reason about what could go wrong with telephone switching networks by using previous cases of breakdowns or problems occurring in the system. By observing expert decision makers in complex and dynamic situations, Klein and Calderwood (1988) found that experts use cases to understand situational dynamics, to generate options, and to predict the outcome of implementing those options. This case-based model of reasoning incorporates problem solving, understanding, and learning and integrates these with memory processes (Kolodner, 1993). By understanding a new problem.in terms of past experiences (or cases) and interpreting the nevr situation by comparing and contrasting it to the old problem situations that have been recalled, a reasoner can arrive at a solution for the new situation. : . " When faced with a iiem,%oblemfthe problem solver assesses the situation to generate a problem description. Based on this assessment, relevant prior cases are retrieved that have problem descriptions relevant to the new problem. The solution of the most relevant case is then adapted and applied to the new problem.

2 2 ■ ■ ■ . --.- '-- -' '. r'-:.-.7 J; ir;''r . .. - ■ '■.:- ■•. -T ,. L : : ' >:-■. -.. ' . - ' - . . ... : c . - .V..- - ■ .

Kolodner and Leake (1996) suggest several advantages that case-based reasoning provides. This model of problem solving allows the reasoner to arrive at problem solutions quickly and to propose solutions in complex domains that contain uncertainty, making it possible to interpret open-ended and ill-dedned concepts. Case-based reasoning allows the reasoner to focus on the important parts of a problem, and can provide the reasoner with notice of potential problems that have occurred in the past, thus reducing the cognitive load of the reasoner who is interacting with a complex real-world environment.

2.3A Team Problem Solving

It seems reasonable to expect that what happens at the group level cannot contradict what we accurately understand to happen at the Individual level, and that what happens at the individual level cannot contradict what we accurately understand to happen at the group level Steiner, 1986, p. 284

The previous section introduced different dimensions and characteristics on which a problem-solving task can be defined and included such dimensions as well- structured versus ill-structured and knowledge-rich versus knowledge-lean. These distinctions are important due to the difference in the cognitive demands placed upon the problem solver, as well as the strategies and knowledge needed by the problem solver to successfully perform the particular problem-solving task. Also presented in the previous section was a discussion of various descriptive models of problem solving (e.g., problem-solving-as-search (e*.g., Newell & Simon, 1972) and analogical problem solving (e g., Kolodner, 1993). Most of the problem-solvingliterature discussed in the previous section focused on individual problem, solvers. However, many decisions, and often very important decisions, are not made by individuals but teams. Because organizations today are more team based, the research literature is beginning to focus more on team decision making (e.g., Argote & McGrath, 1993; Georgopolous, 1986; Jams,

23 1972,1982; Miner, I9S4; Neale &Northcraft, 1990; Cannoa-Bowers, Salas, & Converse, 1993; Smith & Vanacek, 1988; Valadch & Schwenk, 1996). A team Is a distinct entity Independent of Its Individual members (Durkheim, 1968); therefore, we cannot rely solely on decision-making research that focuses on Individuals to help us understand how teams make decisions. The study of teams must also Include team-as-entlty situated In a specific context. Thus, In order to situate the present study within the research literature. It Is Important to not only understand that the task set before the dyads (each consisting of a traffic manager and a dispatcher) In the present study Is complex. Ill-structured, and knowledge-rich, but also that the dyad Is a collaborative team with the shared task of arriving at a common problem definlfioh, as well as generating and evaluating solutions to that problem. Therefore, examining the team problem-solving literature Is the next step in this literature review for situating the context of the research presented In this paper. The research that has been conducted on team decision making/problem solving has found advantages as well as disadvantages for using groups rather than Individuals. Shaw (1932) accords a higher value to group solutions to problems than to Individual solutions. Davis (1969) maintains that the group does not always do a better job than the Individual. Research literature from group dynamics and from management suggests that team decisions are often poorer than decisions made by the “best” member of the team QDIehl & Stroebe, 1987; FInholt, Sproull, & Klesler, 1990; Hackman & Morris, 1975; Marquait, 1955; Shaw, 1992; Shaw & Ashton, 1976; TIndale & Davis, 1983). However, research on teams suggests that they can. generate different representations of a problem than an Individual working alone, allowing for the potential examination of more than one problem representation and then the selection of the best (Dunbar, 1998). This Is possible because teams may bring multiple sources of knowledge and experience, a wider variety of perspectives, and the potential syner^ associated with collaborative

24 activity (Bass & Ryterbanct, 1979; Hof&nan, 1961; Klaus & Glaser, 1968; Maier & Hoffinan, 1965; Morgan Lassiter, 1992; Pelz, 1956). Teams, however, addcoraplexities to the decision-making process not seen at the individual level. For example, within a team individual members may have unique information about different task elements or cues, and those members, also, may not share their unique information in group discussion (e.g., Stasser& Titus, 1987; Grigone & Has tie, 1993). Individuals may apply different weights to the same cues than other team members. Different areas of expertise are distributed among the team members so that even when they have access to the same information, they may evaluate it much differently and from different perspectives. The cognitive burden becomes greater for the members of a team performing a decision-making task than it is for an individual decision maker. They must engage in three activities simultaneously. They mustrecall information (either from their memories or notes), mustexchange that information, either by receiving or giving it to others in the group, and they must process that information, which involves the social and cognitive implications of that information and storing it in memory. Thus, it is possible that engaging in one of the activities interferes with a person’s ability to engage fully in the other two (e.g.. Ball & Zuckerman, 1992; Lamm & Trommsdorff, 1973). Other constructs (e.g., trust in others, cooperation, coordination, and power or status differences among team members) also exist within teams (Guzzo, 1995; Wittenbaum & Stasser, 1996). Understanding the process and means by which teams arrive at decisions requires going beyond a simple extension of individual- decision making practices. One needs to consider a plethora of factors unique to team decision making (e.g., group dynamics, interpersonal communication skills, conflict, competition, and hidden agendas).

25 2.3 A I Group Dynamics Literature

The essence of group dynamics is the interplay between each individual member of the group and the group itself Ramarapu, Simkin, RaTsinghant, 1999, p. 163

In the 1940's and 1950s group dynamics research began to focus on such things as the effects of communication, influence, and group cohesiveness on the individual group member (e,g., Bavelas, 1950; Deutsch, 1949; Festinger, 1951; Zander, 1958). Steiner (1972) suggests that the reportedly small correlation between the average skill level of teams members and overall team performance is due to “process loss." According to Steiner, process loss occurs whenever team member efforts are wasted or duplicated while meeting the coordination and communication requirements for team performance. Many group theorists have noted that groups fail to maximize their productivity because of process impairments (e.g., Hackman & Morris, 1975; Hill, 1982; Janis, 1982; Steiner, 1972; Watson & Michaelson, 1988). The research literature on small group decision making is replete with findings of impairments to group productivity (Cottrell, 1972; Diehl & Stroebe, 1987; Forsyth, 1983; fiighram, Levinger, Graves, & Peckham, 1974; Janis, 1982; Stoner, 1968). A number of distinct team- or group-based behaviors have been observed that are not ordinarily seen in the decision-making behavior of individual. Of interest in the present study ate such behaviors as production blocking, the common knowledge effect, and selective sampling.

Production blocking, a foim pf productivity loss in brainstorming groups, has never been tested directly,, and the indirect evidence is limited (Diehl & Stroebe, 1987). It appears, howëver,.thàtia brainstorming activities, because team members are prohibited firom verbalizing their ideas as they occur (due to the turn-taking sequences that occur in exchanges between speaker and listeners) (Grice, 1975; 26 -' ■:;-- .-:: - 1- - - ' \ .;%v ' ' ■ ; % ; :pf

Sacks, Schegloff, & Jefferson, 1975), they may forget orsuppress them because they seem less relevant oç.Iess original at a later time. It also may be that listening to the ideas of other team members may be distracting and. interfere with an individual’s own thinking. The brainstorming technique (Osborne, 1957) is by far the best-known group technique used for finding creative solutions to problems. However, the majority of empirical evidence does not support Osborne’s method (Lam & Trommsdorff, 1973; Mullen, Johnson, & Salas, 1991). Bouchard and Hare (1970) compared the productivity of 5-, 7-, and 9-person brainstorming groups with that of nominal groups (i.e., individuals working alone and then pooling their ideas). They found that the productivity of the two types of groups correlated negatively with group size, i.e., as the groups increased in size, their productivity decreased. This finding is consistent with a production-blocking interpretation because the length of delay, or the probability of delay, of participation is likely to increase with group size. In one study by Diehl and Stroebe (1987), individuals working alone generated more solutions of a higher quality than four-person groups. For group brainstorming the evidence seems to be clean Individuals brainstorming alone and later pooling their output produce more ideas with quality at least as high as do the same number of people brainstorming in a group (McGrath, 1984).

Common knowledge effect. In any group, individual members have access to information and knowledge from sources outside the group. Therefore, the potential information for group use in their problem-solving task is the sum of all of the information accessible to each of its members. The actual information available to the group is the intersection of the information that is shared among the group members (McGrath & Hollingshead, 1993). The common knowledge effect is defined as the tendency for groups to discuss information that is held by all group members (shared information) more often than information that is held by only one group member (unshared, or unique, information) (Grigone & Hastie, 1993; Stasser,

27 Taylor, &Hànna, 1989). Ci general, the common knowledge effect increases as group size increases (Stasser et al., 1989) and as information load increases (Stasser & Titus, 1987). Wittenbaum and Stasser (1996) point out the multitude of factors that can influence the effective sharing of information between group members. These include time constraints, the expertise and status of individual members, the nature of the task, and the degree of collaboration that exists between members. Stasser and Stewart (1992) found that problem solvers discuss unshared information more often when they believe that the task has a correct solution than when they believe that it is a matter of Judgment. Stasser and Stewart explain this finding by suggesting that in the correct-solution task the risk of arriving at an incorrect solution motivates the problem solvers to consider all the necessary information. In the judgment task, problem solvers believe that group consensus is the only way to determine that the answer is accurate, so they focus on reaching consensus rather than doing a complete information search. Stasser et al. (1989) directly measured group-level information sampling during group discussion using audio tape recordings. They found, across all conditions, groups sampled. 46% of the common information cues possessed by more than one group member but only 18% of the unique information cues available to only one member of the group. In addition, the sampling bias favoring common information was worse in the presence of specific instructions to examine all available information before making a decision. Apparently, shared information is given more weight in group problem solving than is unshared information (Gigone & Hastie, 1993; Stasser & Stewart, 1992). Because shared information has a greater presence in group discussion than : ' .... : unshared information, it exerts more infiuehce on group members (Stasser et al., 1989; Propp, 1997), suggesting that there is an important need to discover ways to ensure that critical information, i&shared. The common knowledg^fficf has been observed in many different tasks. Gigone and Hastie (1993) examined individual judgments, pooling of information,

28 and group Judgments in three person groups, with information that was shared, partly shared, or unshared. The task involved group members predicting the grade of a student based on several factors, such as GPA. The researchers found that shared information was given greater weight than unshared information in final judgments, and individuals’ pre-discussion judgments predicted the group judgments. This suggests that shared information has not only greater influence on group Judgments but also on individual members’ Judgments made before the group discussion. This finding is consistent with those in the Jury decision-making literature (Gerbasi, Zuckerman, & Reis, 1977; Stasser, Kerr, & Bray, 1982; Stasser, Kerr, & Davis, 1989). Larson, Foster-Fishman, & Keys (1994) suggest that the bias toward discussing shared information and neglecting unique information may be more pronounced in newly formed groups where conformity pressures are high and the group members are motivated to emphasize their similarities rather than their differences. Since the majority of small group research is conducted in one-time groups, it is possible that the common knowledge effect may be less pronounced in groups interacting overtime (e.g., Cummings, Schlosser, & Arrow, 1996). However, Kim (1997) observes that as groups gain experience with each other and with a task, they may focus even more on common information and be even less likely to use information that is unique to particular group members.

Selective sampling. Another interesting feature observed in group discussion is that groups often return to previously considered information. This resampling process appears to be selective as some items are mentioned and never reconsidered, whereas other items may emerge repeatedly during the course of discussion. Larson, Christensen, Abbot, and Franz (1995) had individual members of three-person medical teams view video tapes of a physician’s initial interview with a patient and then, as a group; discuss the case and agree on a diagnosis. By editing the videotapes, the authors manipulated the unique and shared information

29 that members of each triad received. For example, in one triad, only one person would be given ‘headaches’ as a presenting symptom, and in another triad all members might know that information before the discussion. If all three members knew before the discussion about ‘headaches,’ the team was more likely to consider the symptom more than once than if only one member of the triad initially viewed a tape that contained the ‘headache’ complaint. Overall, initially shared information was twice as likely as uniquely held information to be repeated after it was mentioned. Stasser, Taylor, and Hanna (1989) observed similar results. It seems that information that is common before team discussion not only has a sampling advantage (the common knowledge effect), but also a resampling advantage over uniquely held information. These findings can have serious implications if the critical information needed to choose the best decision alternative is information/knowledgelKatfs uniquely held by only one member of the team. Even if that critical information is mentioned in the discussion, it appears that the focus of the discussion is likely to remain on the information that was commonly shared before the group discussion. This commonly held information will be sampled and re-sampled, effectively rendering the critical information inert. There have been attempts to prescribe procedures that could reduce the sampling bias toward commonly held information. Among these are telling the groups that there is a correct answer to the task (S tasser and Stewart, 1992) and specifying what members have what information (Henry, 1995; Schittekatte, & Van Hill, 1996; Stasser, Stewart, & Wittenbaum, 1995). However, even these prescriptions have not led to the elimination of the common knowledge effect. Another area that has been explored is the potential for using cognitive conflict (i.e., controversy over the best way to achieve the team’s goal) in decision­ making groups to improve theireffectiveness (Amason, 1996; Jehn, 1995). “[C]ognitive conflict stems from the existence of multiple perspectives or strategies for achieving the group’s goals....[andl.. juanifests itself through the identification and examination of multiple plans or scenarios for achieving group goals”

30 CDeVme, 1999, p. 612). Tjosvold (1985) suggests that it is this conflict that increases the potential members’ endeavor to describe and justify their positions. Particular formalized methods have been used to induce cognitive conflict with inconsistent findings as to theireffectiveness (Schwenk, 1990). The goal of using these methods is to encourage the questioning of underlying assumptions and the consideration of alternatives. However, one runs the risk that affective conflict (i.e., conflict that is interpersonal and may create tension, argument and withdrawal) will result when introducing these methods to increase cognitive conflict. In addition, DeVine (1999) suggests that “experts may need to be pushed, prodded, and even provoked into sharing their specialized information" (p. 627). When considering the mixed-motive decision-making group (where the motive to compete is often mixed with the motive to cooperate), one must ask whether cognitive conflict is an inherent characteristic. That is, in a group where members are fully aware of their different perspectives and different goals, they will also be aware that how they approach the task at hand will differ. Thus, whether the sharing of uniquely held information is more likely to occur naturally in groups with mixed motives than in a cooperative group remains an open research question. Currently the research literature on the common knowledge effect and information resampling does not include mixed-motive decision-making teams.

2.3.4.2 The Nature of the Task

The nature of the cognitive task is judged to be one of the most important factors affecting problem solving in groups (Hackman & Morris, 1976; Hoffinan, 1965; Poole, 1983; McGrath, 1984). One of the ways of characterizing group tasks is by the relative degree of problem-solving difficulty (Shaw, 1981). “Task difficulty refers to the degree of cognitiveload, or mental effort, required to identify a problem solution” (Gallupe &. DeSanctis, 1988, p. 280). With the greater intellectual effort that is required to- analyze and evaluate the information used in a

31 complex problemTSoIvmg t^fc is the probability that a greater number of issues and alternatives must be considered in order to reach the optimal solution (Shaw, 1932; Hackman, 1968). - The complexity of the problem may also be an important factor in its identification. The problem may produce ambiguous or seemingly incongruent symptoms or it may have multiple causes that are interdependent and change over time (Moreland & Levine, 1992). Also, as with FAA traffic managers and airline dispatchers, who belong to different organizations with different cultures and different perspectives on the use of the National Airspace System, what is identified as a problem by one member of the team may not be viewed as a problem by another member.

Task Interdependence, A variety of research supports the view that the interdependent nature of a task affects the performance of the decision-making team. For example, task interdependence can affect the level of cooperation within a group (Shaw, 1973), the group’s ability to prevent process losses (Steiner, 1972), and the nature of the interpersonal interactions among the group members (Gersick, 1988; Kelley & McGrath, 1985). Thompson’s (1967) hierarchy of organizational tasks is classified in terras of dependency and is based on the exchange of information or resources. If a person can perform a task without interaction with anyone else, it is deemed an independent task. However, when people’s performance requires support of others, the task involves some level of interdependence. Thompson identifies three types of task interdependencies: pooled, sequential, and reciprocal. Pooled interdependency involves individuals contributing a distinct product to the overall task, but unless each person performs adequately, overall task performance and quality is degraded (e.g., shoveling snow). Because eacb person’s contribution is distinct, pooled tasks can occur in parallel. Sequential interdependency occurs when one task must be completed before the next can

32 begin. Therefore, each person’s contribution is dependent on the contribution of the person before him or her and affects how the next person will perform his or her task. Reciprocal interdependency occurs when the output from one person is the input for the next person and that person’s output becomes input for the first person. An example of a task that involves reciprocal interdependency is one of making sense of equivocal data. Watson, Bostrom and Dennis (1994) introduce a fourth type of task interdependence to Thompson’s classifications: matrix. Matrix interdependency is a combination of pooled and sequential interdependency. Individuals work on tasks relatively independently, but also receive and use input from others who are doing the same task. Saavedra, Earley, and Van Dyne (1993) propose team interdependence as the fourth level of Thompson’s group task Interdependency, defining it as “group members jointly diagnose, problem solve, and collaborate to complete a tasld’ (p. 63). As the complexity of interdependence among tasks increases, so too do the cognitive requirements for coordination, communication, and collaboration among group members (Argote & McGrath, 1993; Gailbraith, 1987; Slocum & Sims, 1980; Thompson, 1967). The degree of cooperation or conflict inherent in a task, as distinguished from interpersonal conflict, depends largely on the degree to which diverse perspectives, values, or interests lead to differences in preferences for alternative outcomes.

2.3.4.3 Prescriptive Models and Formal Procedures

Some researchers believe that formal procedures will improve the problem­ solving performance of the team by decreasing the complexity of the task. There have been many attempts^to»divide the problem-solving activity into discrete stages or functions ÇFanis & Mann, IS^JrBEroRawa, 1982; Gouran & Hirokawa, 1983). Table 2.1 provides an outline ofi Ae ph^es of problem solving that have been

33 proposed during the twentieth, century to be critical in arriving at the most effective solution to a problem. According to most of these prescriptive schemes, good decision making involves the following steps (conducted in a linear fashion): identify and understand the problem, generate all realistic and acceptable courses of action, evaluate each of these alternatives as to the positive and negative consequences associated with each, and finally, select the best alternative based on that evaluation. The following discussion gives a brief description of each stage and research that indicates its importance in the course of problem solving.

Dewey C1910) McBuraey& Polya(l957) Moreland & Hammond. trance (1939) Levine (1992) Keeney, &Rraiffa (1999)

Feet adifïïculty Define problem Understand Identify problem Define problem problem Analyze causes and Analyze problem Construct plan Develop Clarify objectives implications alternatives

Suggest solutions Suggest solutions Carry out plan Select solution Develop range of alternatives Evaluate Develop proposed Check results Understand suggestions solutions consequences of each alternative Choose best Further verify Maketrade-ofB suggestion Choose best alternative

Table 2.1. Comparative Views of Problem-Solving Stages

Problem Identification. Kast and Rosenzseig (1974) state that the purpose of the problem definition stage is to assess the current state as well as the desired state of the task. The complexify of a problem may influence the ease with which a problem solver arrives at identifying it. An ill-structured problem can produce ambiguous or apparent incongruities fh the manifestation of symptoms, and can

34 tend to have multiple, interacting causes. With complex problems, identification oftea requires a considerable amount of information about the events that have occurred. This stage is particularly important in team problem solving because it allows the variety of perspectives of individual members to be brought to bear on the problem. Van de Yen & Delbecq (1974) have found that this process of idea generation is often reduced by time pressures and by the failure of the team to incorporate the views expressed by each member. The group dynamics literature documents the fact that naturally interacting groups often overlook or pass too quickly through the problem-identiRcation stage packman & Morris, 1975; BGrokawa, 1983; Park, 1982). When this occurs the problem space may become limited which then may influence the number of alternatives that are generated.

Alternatives^ Generation^ Kast & Rosenzseig (1974) prescribe that the goal for the altematives-generation stage is to generate as many alternatives as possible. The problem-structuring literature, based on the cognitive psychology theories of human memory and information retrieval, suggests ways of structuring decision problems in ways that will allow the retrieval of a complete list of alternatives (or at least, reduce the chance of omitting viable alternative solutions) (Gettys & Fisher, 1979; Pitz & Sachs, 1984). However, it has also been suggested that the generation of all viable alternatives to a problem solution could lead to a poor and perhaps costly decision (Scherer, 1986). Understanding what factors facilitate and what factors inhibit the generation of alternatives in problem solving may help improve this stage of problem solving. Fischhoff, Slovic, & Lichtenstein (1977) and Gettys, Pliske, Manning, & Casey (1987) found that when people think of alternative actions, they often neglect the most obvious candidates and seem to be unaware of the omitted alternatives. Those omitted alternatives, thus, are not considered, leaving people with the belief that they have analyzed the problem more thoroughly than they actually have.

35 Some factors that may influence the number of alternatives considered include the availability of information (i.e., the ease with which information can be perceived, recalled, or thought about) (Hogarth, 1980; Nisbett & Ross, 1980; Tversky & Kahneman, 1974), avoidance of uncertainty (which can increase with the number of alternatives considered) (Driscoll & Lanzetta, 1965; Driscoll, Tognoli, & Lanzetta, 1966), and the norms of the group or organization (Hogarth, 1980). Harrison and Bazerman (1995) suggest that team decision making has the potential to increase the number of alternatives generated more than the potential for a single decision maker; however, there is much empirical evidence that indicates that this ‘potential’ is not realized (e.g., Diehl & Strobe, 1987; Lam & Trommsdorff, 1973; Mullen, Johnson, & Salas, 1991).

Alternatives Evaluation, This phase involves critically evaluating the relative merits of each alternative in relation to the established characteristics of an acceptable answer. Research suggests that individuals and groups have the best chance of making appropriate decisions when they follow this practice (see Gouran, 1982; Janis, 1982; Janis & Mann, 1977; Scheidel & Crowell, 1979). However, applying criteria to alternatives assumes that the decision maker possesses the skills, knowledge, and a highly developed sense of objectivity to do this effectively. Rokeach (1973) suggests that the evaluation of alternatives becomes an inferential problem and cites evidence that shows people have difficulty making those inferences. How people make decisions and judgments when uncertainty exists has been a subject of interest for the past 30 years (Hschhoff, Slovic, & Lichtenstein, 1977; Hogarth, 1987; Tversky & Kahneman, 1981).

Alternative Selection, One of the conclusions that has been arrived at is that people are not very good at integratfng information that they have observed in their environments (Edwards, 1961;Enhotn

\ 36 ■ -i - -- I- * - .--r' r-.— ■ - T . - ‘'-t . h ^ ■•i.s \ ...... - :r ^ • -■ - - ;

problem, the number oMternatlves generated, incomplete or inaccurate information-, time Imutations; and cost-resj^ctions all serve to bound the solution set and can seriously ^ p ^ S w / deselection of one alternative among those that have been evaluated occursï^ljr

Summary: Prescriptive Models, From the previous descriptions of the stages of decision making, it is apparent that they are inter-related. Sherer (1986) argues that how a problem is defined may have an impact on alternative generation. He states that the research on ill-structured problems provides method prescriptions for the facilitation of generating ideas. Pitz, Sachs, and Heerboth (1980) used ill- structured tasks to investigate what variables impact a person’s cognitive capacity to generate alternatives. All of the information about the problem was given at one time, and the instructions were for the subjects to generate alternative solutions. The results suggest that the way a problem is structured or framed for a decision maker will impact the quantity and quality of the alternatives generated (i.e., the less structured and less defined the task, the less alternatives are generated). Cyert and March (1963) and Simon (1976) propose that, rather than evaluating a number of alternatives and choosing the best, decision makers consider alternatives sequentially, one at a time, until an alternative is found that meets the “good enough" criterion of the satisficing principle. Harrison and Bazerman (1995) suggest that this behavior leads to fewer alternatives being considered than using a formaiized decision-making procedure that involves generating alternatives, evaluating all of them, and then choosing the best. However, prior experience and the formulation of the choice problem might affect the order in which the alternatives are considered so that the first alternatives generated may be those about which the decision maker has the highest expectation (Cyert & March, 1963; Kahneman & Tversky, 1979), even though they may not provide a better solution than alternatives considered later or not at all.

37 Poole (1991) listed a number of reasons why researchers believe that formal procedures will improve the problem-solving behavior of teams. He states that formalized procedures allow team members to structure their thinking and reasoning, increase the likelihood that the members of the group will focus on the same issue at the same time, and make it difficult for a few members of the group to dominate the discussion. He suggests that these procedures will help give direction to a meeting, give group members the ability to examine the quality of the discussion as it proceeds, and help the members feel that they are in control of the problem-solving process. Some evidence indicates that teams that follow formal procedures make better decisions than teams participating in free discussion. The findings are that, compared with free-discussion teams, those using formal procedures arrive at more accurate answers, (even though they take longer to reach them) (Hall & Watson, 1970), make higher quality decisions ^.arson, 1969), tend to generate more non­ overlapping ideas, feel more free to participate, are better able to face conflict, and are less cohesive but more satished with their accomplishments (Delbecq, Van de Yen, and Gustafson, 1975). Evidence also indicates that formal procedures enhance the commitment that members feel toward the group decision. White, Dittrick & Lang (1980) looked at groups of nurse administrators who either used formal procedures or free discussion. The nurses who used formal procedures in their group discussions were more likely to implement their decisions than those who used free discussion. However, there are researchers who have obtained evidence that formal procedures do not help teams perform critical functions. For example, Hirokawa (1985) examined four teams, three that followed different sets of formal procedures and one that used free discussion. He looked at the number of critical functions that they performed and the qualiQr of decisions they made. He found no differences between tb e ^ u p s . The way^in which groups engage in decision making have been studied and show that decisiommakers do not move in a linear fashion from problem, identification to analysis to solution. Rather, they tend to move iteratively from one phase to another and then back again, gaining bits of insight and agreement at various intervals, sometimes returning to reaffirm an earlier point or position (e.g., Rsher& Ellis, 1990; Hirokawa, 1985; Poole & Roth, 1989). Scheidel and Crowell (1964) analyzed how specific proposals are made and discussed in a group setting and found that groups engaged in free discussion tended to focus on individual proposals in short sequences where each proposal would be clarified^ discussed, and evaluated as a good or bad idea, and then that proposal topic would be discontinued as the group moved on to another proposal. If a proposal was evaluated positively then it tended to re-surface later in the discussion. This repetition of items has been called “spiraling” (Fisher & Ellis, 1990; Propp, 1997; Scheidel & Crowell, 19#) or cyclical processes (Poole & Roth, 1989) and calls into question the generality of the linear model, suggesting that linearity is an ideal from which groups deviate in their discussions. Pavitt's (1994) research supports the findings of spiraling in free discussion and suggest that the demands of formal procedures are unnatural. Stasser, Taylor & Hanna ( 1989), in their research on information flow through group discussion, suggest that pooling of shared information cannot be enhanced easily by procedural instructions. Other studies also have raised doubts about the effectiveness of formalized approaches (Campbell, 1968; McCall & Kaplan, 1985; Rotter & Portugal, 1969; Schoner, Rose, & Hoyt, 1974). Pavitt (1993) suggests that the mixed results that have been found in the research on formal group discussion procedures may be due to people^s differences in their “preferences for procedural order’* (PPG) (Pumam, 1979), or in their desire to make decisions in a. structured or fiiee discussion. Hirokawa, Ice, and Cook (1988) distinguished between, people with high PPG and those with low PPG preferences and found that those with high PPG made higher quality decisions using reflective thinking than in free discussion, and those with low PPG made higher quality decisions using fiee discussion. Although this suggests another interesting

- - 39 - : -• : ■ .

research direction, it is briefly presented here only to indicate that there may be more factors involved in determining whether the use of formalized procedures results in more successful team problem solving than does free discussion.

2.3.4.4 Summary: Team Problem Solving

This section has outlined ways in which team problem solving differs from and is more complex than individual problem solving. Research has shown that a team does not always do a better Job in problem solving than an individual (e.g., Diehl & Stroebe, 1987; Finholt, Sproull, & Kiesler, 1990; Shaw, 1992; Tindale & Davis, 1983). However, other research suggests that teams have a greater potential for solving complex problems than do individuals because teams are able to examine more than one problem representation (e g., Dunbar, 1998) and bring a variety of knowledge and experience and a wider variety of perspectives to the problem-solving task (e g., Bass &Ryterband, 1979; Klaus & Glaser, 1968; Morgan & Lassiter, 1992). The study presented in this paper focuses on teams of two individuals collaborating to solve a complex problem; therefore, this section also examined group dynamics literature that has discovered weaknesses found within teams during problem solving. Specifically, these behaviors are production blocking (e.g., Bouchard & Hare, 1970; Diehl & Stroebe, 1987), failure to share unique information among the team members (resulting in the common knowledge effect) (e.g., Grigone & Hastie, 1993; Stasser, Taylor, & Hanna, 1989; Wittenbaum & Stasser, 1996), and the selective sampling of information (e.g., Larson et al., 1995; Stasser & Stewart, 1992; Stasser et al., 1989). Because the success of the problem-solving task in which the FAA traffic manager and airline dispatcher in each dyad are engaged for the present study is dependent on unique knowledge being shared, the research on the common knowledge effect and the resampling issue is particularly critical. Production

40 blocking is also an important phenomenon to consider as it can serve to inhibit the sharing of knowledge. This section discussed the nature of the task, defining the different kinds of interdependencies that can exist between problem-solving partners and the task on which they are collaborating. Certainly, the dyads in the present research are engaged in a task that requires an interdependent relationship as they jointly diagnose, problem solve, and collaborate to complete their task. Finally, this section focused on the issue of what, if any, benefit formalized, problem-solving procedures have on the quality of the process and outcome of the task. At the present time, the results of such research seem equivocal. Some evidence indicates that teams following formal procedures arrive at more accurate answers, make higher quality decisions, and are more committed toward the team decision than those teams that participate in fiee discussion. However, other researchers emphasize that following formal procedures does not allow adequate pooling of shared information and may actually inhibit some members from sharing knowledge and engaging fully in the problem-solving task. This research is relevant to the current study because the instructions given to each dyad included an outline of procedural problem-solving steps, but these were not formalized and their use was not enforced during the resulting discussion.

2.4 Use of Technologies by Groups

...the computer...a medîimtfor sharing communication.... Schrage, 1990, p. xviii

Interaction technology ...that through which interaction occurs.... Whitworth, Gallupe, and McQueen, 2000, p. 435

2.4.1 Introduction

The introduction of tools to support new ways of communicating and working can have tremendous social and organizational impacts, leading people to ; .»■■ attend to different things, have contact with différent people, and depend on one another in different ways. Take, for exanipte, Üie?teleçhpne, which has had a profound social and organizational impact (Aronson, 1971; Hopper, 1992). The telephone routinely extended attention, social contacts and interdependence beyond the patterns determined possible by physical proximity. These effects were not foreseen when the telephone was originally introduced fischer, 1985), and the unanticipated consequences emerged as people changed their patterns of behavior. As with the telephone, other interaction technologies and their effects must be understood by how they are accepted and shaped by the people who use them to facilitate or mediate interaction with others. The research cited in the section on Group Dynamics has documented and described some ways that groups are predictable, for example, production blocking during idea generation tasks, sharing only commonly held information, and selectively sampling certain information over other information that may be as or more important to the task. Whether positive or negative, the dynamics of face-to- face interaction are usually predictable and similar across groups (Brown, 2000; Forsyth, 1983). However, research presented here illustrates that the dynamics of electronic group interaction differ from results found in studies on the dynamics of interactions in face-to-face problem solving groups, and they seem to be less predictable. For example, in idea generation tasks, production blocking was not observed in groups using electronic support systems as evidenced by findings of these groups generating more unique, high-quality ideas than groups meeting face- to-face. Another example of the differences found is that groups using interaction technologies appear to share even less information with other members than groups interacting face to face. Currently there is a plethora of labels forthe electronic systems that are being developed and the activities in which they are being used to support interaction within groups. The system labels include the following: groupware (Galegher & Kraut, 1990; Johansen, 1988), group support systems (GSS) (Benbasat

42 &Lim, 1993; Watson, DeSanctis & Poole, 1988), group decision-support systems (GDSS) (DeSanctis & Gallupe, 1987; Dickson, DeSanctis & Poole, 1991), group communication-support systems (GCSS) (IBItz,Turoff, & Johnson, 1988; Hollingshead, 1993; Smith & Vanacek, 1990), group negotiation-support systems (GNSS) (Bui, Jelassi, & Shakun, 1992; Lim, 2000), electronic meeting systems (EMS) (Nunamaker, Dennis, Valacich, Vogel, & George, 1991). Activity labels include the following; computer conferencing (Hiltz, Johnson, & Turoff, 1986; Sproull & Kiesler, 1991), computer-mediated communication (CMC) (McDaniel, Olson, & Magee, 1996; Rice, 1990; Rice & Shook, 1990), computer-supported cooperative work (CSCW), and computer-supported communication (CSC). These interaction technologies and the social interactions (i.e., those occurring between two or more people) that they enable represent a paradigm shift in computer use, changing the focus from computer as object of action (e.g., an individual using a computer to produce a document) to computer as medium for communicating action and intent. Human-computer-human interaction, rather than human-computer interaction, is the primary focus, with the computer facilitating or mediating human communication and Joint problem solving and decision making. The fundamental goal of these interaction technologies is to support socially distributed cognitive work activities (Hutchins, 1991), such as idea generation, message and information exchange, document preparation, mutual product design and creation, and joint planning, pfbblem solving, and decision making. Supporting team work actually meansrsupgprtmg the cognitive processes that allow or facilitate collaboration among members^ofthe team of which communication or information exchange (which can be considered here as synonyms) is the most basic team process. These technologies may support face-to-face meetings or dispersed groups of people via computer and/or teleconferences. They may be used for synchronous (at the same time) interaction or for asynchronous (at different times) interaction. Because of the capabilities of these technologies to allow distance-spanning and time-bridging interactions, teams can meet even when their members are not all

43 - - v ;

- - in the same place and/or when they are not ^ acting within the same time period. The cost of these technologies is that: communication modalities vary with the technology being used. One or more of the various communication channels - visual, auditory, non-verbal, and paraverbal—are often absent, which may negatively impact the tasks and activities in which the group is engaged. Table 1 2 illustrates the various media used by interaction technologies, the channels those media support, and the time and place that interaction using the media takes place.

\ ^ * T ime ': : Synchronous Asynchronous Media .jT * ' , Channel Media Channel 1 « / 1 Electronic bulletin Visual ( - . 1 X boards (Textual/Graphics) I Same Face-to-Rice All channels available iX Electronic project Visual Place j management tools (Textual/Graphics)

Telephone Auditory Bectronic mail Visual conference (Textual/Graphics) 1 “ ! [ tnteractivc Visual Voice mail Auditory computer (Textual/Graphics) conference

Interactive video Visual/Auditory Non-interactive video Visual/Auditory I- conference

Table 2.2. Distance-spanning and time-bridging media/channels

Face-to-face (i.e., same-time/same-place) meetings are the most common form of team interaction. Tools for teamwork: in this type of meeting range from white boards, flip charts, and overhead projectors to specially built decision rooms. Because so many organizations today are distributed with members working in many different locations, face-to-face meetings can be costly in both time and travel. Therefore, it is often not possible to get a team of people together in the same location and this is when meetings via electronic media are used. Same- time/different-place interaction technologies vary fixjm telephone only (or audio teleconferencing) to high-end, two-way motion video rooms. Conference calling is 44 a critical building block for same-time/different-place meetings, and adding a means of document exchange/sharing may be all that is necessary for a team to have a productive meeting. Different-time/different-place communication is a practical means for business teams to coordinate efforts. Electronic mail and computer conferencing allow participants to contribute to the interaction at different times and to “keep up” with the contributions made by other members of the team. Different­ time/same place meetings are the most difficult to conceptualize. ‘Same place’ seems to imply that team members need to be there at the same time. However, one can think of a common bulletin board where notices are posted to get a clearer understanding of how different-time/same-place technology could work. Currently, the examples of interaction technologies for teamwork that fit this category are electronic bulletin-boards systems and electronic aids of various types to facilitate group memory and enable procedural structure (e.g., electronic schedulers that enable project management). Given the information found within Table 2.2, the present study can be placed in the category of same time/different place with the media being telephone and interactive computer conference. The channels of communications available to the participants are therefore auditory and visual. However, another channel available to the participants in this study was nonverbal (i.e., through the use of the telepointer, the actors could indicate non-verbally where they were directing their attention), allowing fordiectic reference through the computer medium.

2.4.2 Research Findings fo r Groups using Interaction Technologies

Recently, computer science and information systems researchers have begun to pay attention to technological support for work group collaboration (e.g., Greif, 1988; Olson, 1989). Research on the various interaction technologies is diverse and heterogeneous, driven by a wide range of concerns and analyzed under varying frameworks and models (e.g., Johansen, 1988; Suchman, 1987; Ellis, Gibbs, &

45 Rein, ^IBis jresearcR has examined thejnedfatfng effects that interaction technologies have on the com m utation and problem-solving of teams using these technologies as they undertake intellectual tasks that are characterized by cooperation, conflict, oracom bm ^on of cooperation and conflict (i.e., mixed motive). Work began on computer messaging and computer support systems in the 1960s and 1970s (Chapanis, Ochsman, Parrish, & Weeks, 1972; Davies, 1971; Williams, 1977). Studies conducted in the 1980s were largely laboratory experiments designed to compare groups supported by interaction technology with unsupported groups (e.g., Gallupe, DeSanctis, & Dickson, 1988; Hiltz, Johnson, & Turoff, 1986; Keisler, Siegel, & McGuire, 1984; Lewis, 1982; Rutter, 1987; Smith & Vanacek, 1988; Steeb & Johnston, 1981). The 1990s phase of interaction technology research involved more field research techniques to investigate their use in organizations (e.g., Nunamaker et. al, 1989; Shepherd, Briggs, Reinig, Yen, & Nunamaker, 1995). These research approaches also reveal a gradual acceptance of, and movement toward, a more eclectic multi-methodological research approach to study the effects of interaction technology use (e.g., Nunamaker et al., 1993; DeSanctis et al., 1992; Orlikowski, 1992; DeSanctis, Poole, Dickson, & Jackson, 1994). The following review of research literature on interaction technologies is categorized and reviewed by the task characteristics of cooperative, conflict, and mixed motive. This categorization has been chosen to reflect the characteristics that were present in the interactions of the dyad partners in this study. That is, the participants were engaged in a problem-solving task that required cooperation with one another, they had dirierent perspectives and ideas on the causes of the identiried problem (which held the possibility for conflict), and because the partners were from two different organizations with different goals and priorities, the mixed- motive nature of the relationship is apparent.

4 6 Research on the effects of cooperative tasks includes activities of idea generation, decision making, consensus, and information sharing. Research using tasks that involve conflict include the examination of how different media affect negotiation leading to consensus and the development of alternative plans. The mixed-motive task research tends to engage participants in games that include prisoner's dilemma (Luce & Raiffa, 1957) and social dilemma problems (Adrianson & HJelmquist (1999), examining the differences in participant performance using different interaction technologies. The vast majority of research on interaction technologies involves comparing face-to-face groups with groups using some form of technology to mediate their interactions.

2.4.2.1 Cooperative taslcs .... .

Chapanis and his collea^es were among the first to examine computer messaging and face-to-face verbal communication. Chapanis, Ochsman, Parrish, and Weeks (1972) coiïducfèd i study using two-person teams whose task was to solve problems with objectively correct answers (intellective tasks) using either computer messaging, remote handwriting, audio only, or face-to-face communication. Their results indicate that groups using computer messaging and remote handwriting took longer to solve the problems and exchanged fewer messages than those using face-to-face communication. The time in which problems are solved is the same in voice-only modes of communication and in face-to-face communication. Also, communicators in teletype modes of communication are much more likely to share equally in the exchange of information than are communicators in face-to-face and voice-only modes of communication. Chapanis et al. (1972) also report that the quality of the solution was not affected by the difference in communication channel used in these problem-solving experiments.

47

I • -m ' Othérsimilàrstadîes (ÎDaly, 19%; George; Éaston» Nunamaker, & Northcraft, 1990; Hiltz, Johnson, & Türoff, 1986) have found the same results as Chapanis and his colleagues ^ T ^ en ttfeks require objectively correct answers, the communication media the group.qâes,hak no effect on the quality of the answer. Davies (1971; reported in Williams, 1977) and Champress and Davies (1971; reported in Williams, 1977) compared groups interacting using audio-only or face- to-face for problem-solving tasks with objectively correct answers. These researchers found little difference between these media in the accuracy of the solution achieved, but did find differences in the number of solutions discussed (the face-to-face groups discussed more solutions) and in the length of the discussions (the face-to-face groups discussions were slightly longer). Hiltz, Johnson, and Turoff (1986), in their comparison of face-to-face groups and groups using synchronized computer conferencing, also found that in judgment and intellective tasks there was no significant difference in the quality of decisions between the two media types, but did find that groups using synchronized computer conferencing were less likely to reach agreement. These findings of no significant difference in the quality or accuracy of solutions between groups using different modes of communication performing intellective tasks are not consistent overall studies. For example. Smith and Vanacek (1988) studied the effects of computer conferencing on groups working on complex intellective tasks either via a simulated conferencing system or face-to- face. The face-to-face groups deviated less from the correct answer, shared more information, derived more correct reasons for eliminating wrong alternatives, and considered more important case attributes in their decisions than the computer- supported groups. In contrast, McLeod and Liker (1992) found that computer- supported groups performed better on an intellective task than manually supported face-to-face communication goups. Incontrast, Kiesler, Siegel, and McGuire (1984) conducted controlled problem-solving experiments that compared computer- based communication with face-to-face discussion. They found that the groups that

48 used computer communlcatioa took: longer to reach consensus, participated more equally and showed momXvillingness to arrive at conclusions that differed from their initial proposals. Also» the ability for those groups using computers to mediate communication to solve these complex problems was lower than the face-to-face groups. Some of the effects thaf they observed have been attributed to the absence of non-verbal cues that are present in face-to-face discussion and even to some extent in telephone conversation.

Brainstorming or idea-generation tasks have received much attention in the interaction technology literature. Williams (1977) investigated the effect that different media might have on productivity. She studied four-person groups engaged in a brainstorming task. No differences in the number of ideas generated, or in the average originality or quality of the ideas were found between the three media conditions (audio-only, audio-video, and face-to-face). Although some recent research has supported Williams’ findings (e.g., George, Easton, Nunamaker, & Northcraft, 1990), there is much research that reports signifrcant differences in outcomes in brainstorming tasks between groups using interaction technologies compared with groups that did not (e.g., Gallupe, Dennis, Cooper, Valacich, & Bastianutti, 1992; Gallupe, DeSanctis, & Dickson, 1988; Valacich, Dennis, & Connolly, 1995; Valacich, Paranka, George, & Nunamaker, 1994). Gallupe, Bastianutti, and Cooper(l99l) conducted a series of three studies to examine the notion that the ability of group members to work in parallel may reduce production blocking and would then account for the increased productivity of group support system (GSS) idea-generating groups. In their first study, they compared nominal and interacting groups using electronic and non-electronic communication in an idea generation task. The four groups studied were the electronic interactive group (who entered all of their ideas into a computer where they were stored together), the electronic nominal group (who entered their ideas into the computer but they were stored only in each individual’s computer), the

49 nominal face-to-face groups (who wrote their ideas on paper without communicating those ideas to others), and the interactive face-to-face groups (who verbalized their ideas to the other members of the group). The researchers found that the electronic groups generated significantly more unique, high-quality ideas than did the face-to-face groups. However, the productivity of the nominal and interacting groups did not differ. Interacting groups reported feeling more motivated to generate quality ideas, more comfortable with the idea generation process, a greater opportunity to express their ideas, and that they had generated more ideas than they actually had. Electronic groups found the task easier than the face-to-face groups. In Gallupe et al.’s second study, a delay was implemented into the GSS technology to simulate the blocking that occurs in traditional groups interacting verbally. They found that the delay groups did no better than the verbally interacting groups, suggesting a major blocking effect. In Gallupe, Bastianutti, & Cooper’s (1991) third study, the researchers varied the GSS treatment by imposing a strict idea generation process on all of the groups. This process allowed for only one idea being generated at one time in a “Rrst-in” procedure. The results indicated that GSS groups generating ideas with this strict process were less productive than traditional face-to-face brainstorming groups. Research by Valacich, Dennis, & Connolly (1995) corroborates the effects of production blocking in their research on traditional meetings where a group contains eight or more members. They found that larger groups benefit significantly fix)m the concurrent production capabilities afforded by electronic brainstorming.

Deciston-making tasks. McLeod and Liker (1992) investigated the effects of computer support on the interpersonal and task processes, performance and member satisfaction in decision-making groups. Two different tasks were studied, an intellective ranking task (i.e., an objectively correct ranking exists) and a decision­ making task (i.e., no objectively correct solution exists). Both the computer-

50 supported group decision support system (GDSS) groups and the manually- supported face-to-face communication groups were required to reach consensus on the proper sequence of activities forplanning^ organizing, implementing, and controlling a hypothetical project for the first task, and on the response for each piece of correspondence for the second task. Both groups were supplied with paper and a common writing ^ace. i ^ There were no significant differences between the groups in equality of participation. The computer-supported groups showed a higher concentration of task-oriented behavior and performed better on the intellective task than the manual groups. However, they performed worse than the manual groups on the decision­ making task. The manual groups wrote responses that were longer and more completely formatted and that showed a greater awareness of underlying problems on the decision-making task. There was no significant difference between the two groups on task satisfaction. The research on group decision making conducted by Lewis (1982; as cited in Dennis & Gallupe, 1993) contained three conditions: a control treatment that involved no support, the use of a group support system, and the use of a structured paper-and-pencil technique that incorporated the same features of support as the GSS. The results indicate that compared to either the control group or the paper- and-pencil group, the groups using the GSS produced higher quality decisions, generated more alternatives per decision, and reduced domination by single group members. Gallupe (1990) reports two studies that compared the performance of GSS groups, non-GSS groups, and the “best members” of those groups to determine if a support system improves decision quality over that of the group's best member. He found that the GSS groups did not do as well as the best member of their group and that more non-GSS groups did as well or better than their best member. Gallupe suggests that a GSS provides for more equal participation by group members, making it more difficult for the best member to influence the decision.

51 Information sharings In intellectual work, the primary resources utilized are data and knowledge that can be transformed into information. Since information is not consumed as a result of its use, the more information that is shared among team members the greater the interdependence between the individual members, and thus, the greater the need for mechanisms to facilitate information sharing. Therefore, investigating how interaction technology facilitates information sharing is an important research goal. Given the overwhelming evidence in the research literature on group decision making of the common knowledge effect, Hollingshead (1993; cited and discussed in Hollingshead & McGrath, 1995) examined the effect of communication media, group decision task, and access to information in the pooling of individually held information and on the quality of group decisions. Her study consisted of three conditions: communication media (face-to-face versus distributed), decision task (choose best versus rank order), and degree of information access during.the group decision (no access versus complete information access). Results showed tha(.both face-to-face and distributed groups generally did not select the objectively optimal choice, and the information presented during group discussion focused on members’ pre-discussion preferences. There was a significant interaction between the decision task and communication media for decision quality. Groups in the face-to-face rank-order conditions were most likely to discover the better alternative. In addition, there were differences in the decision process between the two media. Face-to-face groups made significantly more comments and took significantly shorter time to reach consensus than did computer groups. In the computer-mediated condition, there was a significantly higher proportion of normative influence attempts, significantly lower proportion of informational influence acts and significantly lower proportion of speculation than in the face-to-face condition.

52 Dennis (1996) examined information exchange and decision-making processes in small groups that interacted verbally with other members or interacted by way of a group support system (GSS)_ Each of the 6-member groups worked to solve a hidden profile taskir&wKch each of the members had different information. In order to reach the optimal decision, the group members had to share their information. The results indicate that only a small portion of the available information was shared in both the GSS and non-GSS groups, with the GSS groups sharing the least. In a study of information processing and code diagnosticity, Howell, Gettys, Martin, Nawrocki, & Johnson (1970) found that team performance was augmented when information was common to more than one member and when integration of complementary information was allowed. Performance was better in dispersed teams interacting via telephone or through written exchange in a decentralized communication network rather than in a centralized network, suggesting that method of information integration could be a source of process loss. The common knowledge effect was evident in these studies, with an even greater effect being observed in groups using electronic media. It could be that the necessity of keying in comments and ideas, as well as the procedure in using the electronic media led to these findings of less ideas and information being shared (Adrianson & Hjelmquist, 1999). This suggests that the type of interaction technologies used to mediate the group discussions were not effective in enabling group members to share uniquely held but critical information.

2 A 2 .2 Tasks involving conflict

When group members have different preferences among options but desire mutual agreement, they must negotiate. Negotiation requires complex problem solving, communication and information search ^azerman, Mannix, & Thompson, 1988). Unlike the lack of differences between experimental groups most often found the research using tasks involving cooperation, research that involved tasks 53 that were characterized by conflict and negotiation has reported media differences. Motley and Stephenson (1969,1970) used two-person groups who argued an industrial dispute using either face-to-face or audio-only communication. These authors hypothesized that in the audio-only condition, the person with the stronger case would do better in the negotiation than the person with the stronger case in the face-to-face condition. Thé results of their studies support this hypothesis. Morley and Stephenson found that in the audio-only condition, which they consider the more formal negotiating system, the negotiators focused less on the interpersonal aspects of the interaction and more on the objective appraisal of the issue and the merits of the case. This suggests that individuals using audio-only technology were able to focus more on the case elements and were less affected by interpersonal factors that might distract from the consideration of critical factors. Arunachalam (1994) examined the effects of communication channels on the outcomes of group negotiations. In contrast to Morley & Stephenson’s (1969, 1970) findings, the results of Arunachalam’s studies indicate that computer- mediated groups obtain lower outcomes, distribute resources more unevenly, deviate more from the integrative agreement, and maintain more inaccurate perceptions of the interaction than face-to-face groups. Computer-mediated groups also take more time to reach agreement than face-to-face groups. Hollingshead, McGrath, & O’Connor (1993) also found that face-to-face negotiating groups outperformed groups supported by electronic communication alone. Anderson, O’Malley, Doherty-Sneddon, et al. (1997) studied groups engaged in a map-following task or in a task of negotiating alternative plans. There were no differences found between the audio-video and audio-only groups, but both of these groups differed from the face-to-face groups. Those subjects in the audio- only groups reported not knowing what was happening when there was silence on the other end. The authors suggest that in the audio-only condition participants are missing the cues that help people determine whose turn it is to talk, which can cause disruptions in turn taking and feedback.

54 Several studies have been conducted to evaluate^ the performance of negotiation support systems ^S S ). Using a comprehensive NSS, Delaney, Foroughi, and Perkins (1997) designed a series of studies to assess the relative value of each component of a NSS, consisting of a decision support system QDSS) component and an electronic meeting system (EMS) component. They compared the performance of DSS-supported dyads with face-to-face groups with no support to assess the value added by the OSS component. They then compared these results with the performance of dyads using an integrated NSS in order to assess the additional value generated by the EMS component. These authors found that the DSS-supported dyads generally outperformed the face-to-face dyads on outcome measures, providing evidence of the value added by the DSS component. They found no significant differences in outcomes between the DSS component and the comprehensive NSS. However, they did find higher satisfaction with the integrated NSS. It appears that tasks that involve conflict and negotiation show differences in outcomes between communications media. It is possible that the relationship between participants may be more important in these situations than in problem­ solving tasks.

2.4.2.3 Mixed-motive tasks

Wichman (1970) had two-person groups play the prisoner’s dilemma game (Luce & Raiffa, 1957) using either audio only, visual only, or audio-video. In the two-person prisoner’s dilemma, participants are given a series of choices in which they have the option of cooperating or competing. If both individuals make the cooperative choice, both obtain a moderate reward. If both individuals make the competitive choice, both suffei;amoderate loss. But if one cooperates while the other competes, the conipetitor obtams a large reward and the cooperative person suffers a large loss. Thus, thisgame captures the essence of a mixed-motive

55 situation (Rapoport, 1985). Results of Wichman’s study indicate that in the audio­ video condition, participants showed significantly more cooperation (87% cooperative responses), than in audio only (72% cooperative responses), and visual only (48% cooperative responses). LaPlante (197 L) also used the prisoner’s dilemma game with confederate-subject pairs, with the confederate giving scripted friendly or unfriendly messages. The media types he used were written messages, audio only, audio-video, pr face-to-face. The results indicate significantly less cooperation in the audio-only, unfriendly-message condition compared to the other seven conditions. * Adrianson and Hjelmquist (1999) conducted an experiment on communication and problem solving in face-to-face and computer-mediated communication. The computer-mediated condition involved participants either writing under their own names or anonymously. The problems were a social dilemma problem (created by a conflict between a private benefit and the public good) and a prisoner’s dilemma problem. The results indicate that the computer- mediated communication group solving the prisoner’s dilemma problem generated more ideas on how to solve the problem than the face-to-face group, but did not follow up these ideas to generate answers. The face-to-face group solving this problem generated less ideas, but more answers. In a variant of the prisoner’s dilemma game, Rocco (1998) found that groups that were able to occasionally talk to each other face-to-face about the optimal strategy for playing the game ended iti achieving benefit through cooperation. Those groups that discussed things only by email defected more often. Another important finding is that those groups that met face-to-face prior to the game and engaged in a team-building activity eventually cooperated even when they were restricted to only email for their discussions during the game. Kmll (1982) created a decision-making simulation using a group support system. The task involved five executives fixim different companies analyzing a business case and making a decision on strategy to solve the problem presented.

56 ■t

Some of Kruirs findings were that group support systems must be designed in such away as to support group interaction, avoiding any factors that may lead to inhibition, and that GSSs may not be appropriate for all types of tasks or for all levels of complexity.

2.4.3 Summary: Use o f Interaction Technologies

We [interaction technology researchers] are. alas, ’technocentric’^ in our belief that GSSs. like the technologies before them, have the potential to brirtg positive change to organizations. DeSanctis, 1593, p. 98

The contributions of researchers investigating the effect that interaction technologies have on group decisions show no consistent pattern of effects on time to decision, equality of participation, decision quality, confidence in the decision, agreement with the solution, or satisfaction with the process (Dennis & Gallupe, 1993; Koop, 1994; McGrath & Hollingshead, 1995). On the issue of decision quality, the findings of some studies show that interaction technologies have a positive influence on the qualitjrof a group decision (e.g., Gallupe et al., 1988), other studies show that these-technologies had a negative influence (e.g., Watson et al., 1988), and still others show, that technologies used to mediate or facilitate social interaction have no effect or a mixed effect on decision quality (George et al., 1990). Given the equivocal results, how are designers of interaction technologies to proceed? It is important to note that the channel of communication for the computer-mediated interactions used in the cited research was text-based. This fact alone raises questions as to effects that may have been found if other channels had been used instead of, or in addition to, text. For example, the present study asks the question of what effect an audio channel of communication, enhanced by a shared tabular and graphical representation, have on the quality and results of an interaction in the context of problem solving. 57 What may be critical to the success of interaction, technologies and is missing from most of the relevant research is a focus on how these tools are situated in the context of activity. Task performance often does not follow a one-size-fits- all, rational, step-by-step goal-achieving process so often prescribed as the necessary means to achieving a successful end. Iristeadv it is a "situated action” that

■V. W ■ . . "occurs in reaction to achangirigénvironment, moving from skill-based activities to knowledge-based reflection aii%l)aclC construing meaning and interpretation of the situation” (Andriessen, 199(5f pi 119).''Ciborra (1996) suggests that “the organizational world [i.e., the situated context] is barely visible in research on the introduction and use of groupware. While existing groupware research has made several contributions, the lack of visibility of the organizational life-world has been a limitation” (p. 8). The research presented in this paper takes notice of this limitation and embeds the problem-solving activity within the context of the organizations of which the participants are members (i.e., the FAA and a commercial airline). Weick and Meader(l993) are critical of the research on interaction technologies that focus on the answers and decisions made by participants rather than attending to the questions and interpretations that are made. They conclude that by putting the primary emphasis on the end result denies the sensemaking process that individuals engage in when problem solving. Thus, from a sensemaking perspective, interaction technology systems need to be designed to support reflexive dialogue, suggesting questions for designers to ask.

1. How can technology aid individuals in representing an understanding of the context in which they are situated?

2. How can technology help those individuals to reflect upon and share with others these interpretations?

58 3. How can technologies assist individuals to grow in their understanding of the world?

Thus, designers need to consider what is required in order to design artifacts that become part of the distributed cognitive system that will improve a group’s ability to represent their interpretations, to reflect upon them, to engage in dialogue about them, and to inform action with them. What factors will provide the conditions for surfacing and challenging important assumptions (Argyris, 1982; Schon, 1983), for ‘complicating the users’ thinking’ (Weick, 1990), and for enabling significant change when it is required (Bartunek & Moch, 1987; Orlikowski & Gash, 1991)” (Boland, Tenkasi, &Te’eni, 1996, p. 251)? There is a growing body of research on distributed cognition that is examining the ways in which artifacts function to support collaborative cognitive work (e.g.. Brown, Collins, & Duguid, 1989; Galegher, BCraut, & Egido, 1990; Goodwin & Goodwin, 1996; Hutchins, 1990, 1995; Lave, 1988; Norman, 1988; Smith, Billings, McCoy, & Orasanu, 1999; Suchman, 1987, 1996). These researchers represent a growing concern within anthropology, psychology, communications, sociology, cognitive science, and cognitive engineering that the impact of interaction technologies is not reduced to simply a study of the specific technology and how group interaction is impacted by that technology. The research traditions found in socially distributed cognition (Flor& Hutchins, 1991; Hutchins, 1988,1990, 1995), activity theory QEngstrom, 1987,1990; Kuutti, 1991; Nardi, Kuchinsky, Whittaker, Leichner, & Schwartz, 1996), and situated action (Lave, 1988; Suchman, 1987), among others, rely on empirical work and ethnography, allowing researchers to arrive at a collection of findings about how people work and think together as they interact through and with artifacts as situated in a “community of practice” (Lave & Wenger, 1992). The present research attempts to add to these findings.

59 Thus, the dîfRcuIty faced by designers of interaction technologies is not deciding what technology best fits which types of tasks, but instead, the challenge is to understand the physical, social, and cognitive environments that need to be met in order to help groups do their work and make good decisions.

60 CHAPTERS

RESEARCH CONTEXT

3.1 Introduction

The investigation described in this dissertation is situated within the context of the United States Air Traffic Management (ATM) System. As such, it is necessary to provide the reader with some background of this domain, its workflow and the work roles of the actors within the various organizations that comprise this system. This chapter gives very broad brushstrokes of the ATM system, providing more detail where necessary for a proper understanding of the particular organizations and actors used in this study.

3.2 Air TbafBc Management System

The Air Traffic Management (ATM) System in the United States is a very broadly distributed system with command, control, and communication responsibilities spread across a large number of FAA and air carrier organizations. This distributed problem-solving system is comprised of a large number of decisiori makers, distributed across organizations that often have conflicting and competing goals, hi spite of these conflicting goals, these problem solvers must come to agreements concerning the management of the ATM system, a dynamic environment 61 where changes occur in rapid and unpredictable ways. The complexity of this environment is characterized by a high level of uncertainty with only partial overlap of data and knowledge among the decision makers. However, it is this data and knowledge that ties the very complex, highly distributed system together (Billings, Smith, Woods, et al., 1997). The ATM system is composed of two primary functions: Air Traffic Control (ATC) and Traffic Flow Management (TPM) (Kerns, Smith, McCoy, & Orasanu, 1999). Table 3.1 illustrates the primary responsibilities of the different facilities within the ATM system. Because the focus of this thesis is traffic flow management, only a cursory overview of the ATC function will be presented.

3.3 Air TVaffic Control (ATC) System

The Air Traffic Control (ATC) component of the ATM system exists to “provide safe, orderly, and expeditious flow of air traffic to its users,” (i.e., the flight crews, passengers, and air carriers) (Kems et al., 1999, p. 1982). The ATC organization provides these services throughout all phases of an aircraft’s flight, and controllers are located within the different fadlities that provide the particular service. The terminal area includes controllers who work in the airport traffic control towers, where the surface movement of aircraft and their landings and takeoffs are controlled. Controllers located in the Terminal Radar-Approach Control facilities (TRACONs) guide flightdonce an aircraft takes off and before it lands (fix)m about 40 nautical miles from the airport). The en route area includes controllers working in the Air Route Traffic Control Centers (ARTCCs) or En Route Centers that manage the airspace environments. This phase of flight may occur across several centers, which then requires coordinated hand-offs between the affected centers. Because the focus of the present research is on events occurring during the en route portion of a flight, some details of the complexity with which controllers at these facilities must deal is provided the reader.

62 System Facilities Controller Traffic Manager ATCSCC and Responsibilities Responsibilities Dispatcher in ATC System in ATC System Responsibilities and TFM in TFM System Systems Towers at Directing Coordinating Airports arrivals and arrivals and departures departures with controllers Terminal Guiding Helping to plan AirTraffic Radar- flights for the and adjust die r Approach first 40 and flow of traffic Control (ATC) Control last 40 miles within their System Facilities o f flight airspace to (TRACONs) simplify and Air Traffic expedite traffic Management flows (ATM) System Air Route Controlling Helping to plan Traffic flights while and adjust the Traffic Flow Control en route flow of traffic Management L within their Centers (tactical) (TFM) System (ARTCCs) airspace and expedite traffic flows ATCSCC Coordinating activities within and between local organizations Dispatchers Pre-flight within planning; airline. , continual AOCs monitoring progress of

K ... flight Table 3.L Brofitfview^of the AirTraffic Management System

3.3 J En Route Environment

The FAA corrently has 22 Air Route Traffic Control Centers (ARTCCs) in the conterminous United States, each responsible for the separation of aircraft traveling between airports. Figure 3.1 is an illustration of the various ARTCCs located across the nation. The En Route Centers that participated in this study are highlighted. 63 Boston Minneapolis Center Center

Mew York Center

Ft. Worth: Center tianta. Center

Figure 3.L Air Route Traffic Control Centers (ARTCC)

En route ATC operations are divided into different ^ e s of sectors, which are classified according to various characteristics. These characteristics include the altitude and phase of flight of the aircraft. For example, high altitude sectors are generally above 24,000 feet and handle departure traffic climbing to cruise, crossing en route traffic at cruise altitude, and traffic descending to a lower level in preparation for arrival. Aircraft within low altitude sectors include those that are filed at a lower altitude and those who are transitioning to another altitude in preparation for landing or in order to reach their cruise altitude. Another classification characteristic of sectors is based upon their missions, and includes en route arrival/departure sectors, transition high and low sectors, and en route high and low sectors. The controllers within the en route centers must interact with many other components within the ATC system. These interactions include collaborating with other controllers in their particular center as they constandy monitor each other’s work, as well as negotiating with controllers of adjacent sectors, TRACONs, and airport towers as to the most suitable altitude and flight path for each aircraft for 64 which they are responsible (Sommetville, Rodden„ Sawyer» Bentley, 1992). These controllers also maintain contact with the pilots of these aircraft, as well through supervisors as center traffic managers. Other components of the ATC system with which en route controllers must interact include the airspace and airport surface layouts, communications links, computer management and. decision support tools, and local and national procedures and regulations. Thus, the work of the controller is one of high cognitive complexity, requiring each controller to build Grom a dynamic, continually changing two-dimensional display, a four-dimensional (i.e., three spatial and one temporal) mental model of the airspace. At the same time, he must interact with the many different components of the ATM system (both other controllers and users of the airspace, as well as other information resources) while doing so within varying time constraints.

3.4 Ttaffic Flow Management System

The Traffic Flow Management (TFM) component of the ATM system is responsible for providing strategic planning and control when necessary in an attempt to avoid situations where potentially safe or inefficient operations are likely to arise (Kems et al., 1999). The TFM system is a distributed cognitive system where a major task is flight planning m an uncertain and dynamically changing environment. It is distributed in the sense that the organizations who are involved in the TFM system are geographically separated across the contiguous United States, making it difficult and unlikely that face-to-face interactions will occur, and impossible when those interactions are in reaction to a currently unfolding event. The information types and sources are extensive and access to them is distributed among the various FAA facilities, as well as the commercial airlines. Also distributed among these members are different types and levels of knowledge and expertise, and different décision-support tools are used at the different organizations, which can encourage different views or perspectives on the data and different cognitive representations of

65 the airspace- Even within the same organizations, tasks, responsibilities, information, knowledge, and expertise is differentially distributed. Traffic flow management has traditionally been a function under the control of the FAA, with traffic managers at various facilities making decisions about what routes could be flown by flights scheduled, by the airlines. Recent changes in the National Airspace System (NAS) have given air carriers greater flexibility with the assumption that the airlines have better information about the costs of alternative methods of operation, and should, therefore, be in a position to make better decisions about the economics of alternative flight plans (Smith, McCoy, Orasanu, et al., 1995). In essence, this shifts the locus of flight planning control without necessarily shifting the distribution of informatioirthat airline dispatchers must consider if, in fact, they are to improve the efficiency th&NAS (Smith, Billings, McCoy, & Orasanu, 1997). The management of traffic flow involves making decisions under a high degree of uncertainty. A major source of that uncertainty arises due to weather conditions (Andrews, 1993), e.g., forecast thunderstorms, airport runway closings due to snowstorms or crosswinds, and low visibility conditions caused by fog (Kems et al., 1999). Traffic patterns are another source of uncertainty. Departing flights often experience unscheduled delays, which can impact traffic congestion somewhere along the filed route. Runway restrictions and controller staffing and workload limitations also impact traffic patterns. Thus, as these factors interact, a complexity arises that can influence the performance of the system.

3,4.1 D^ering Goals and Priorities

Across these different organizations, the goals and priorities are different, yet linked in ways that cannot be separated. The decision-making function is distributed over many practitioners and teams of practitioners, who, while geographically dispersed, must coordinate their information resources and activities in order to achieve their goals. These goals are mixed-motive in nature; that is, there is a 66 mixture of overlapping and competitive interests in a relationship characterized by interdependence. A collectively optimal outcome of particular situations occurring in the NAS requires mutual cooperation, but individual self-interest may provide temptation to not cooperate (Axelrod, 1984; Kelly & Thibault, 1954; Rubin & Brown, 1975). Because the present study focuses on the interactions of en route traffic managers and AOC dispatchers as they discuss inefficiencies occurring in the en route phase of a flight, the following provides the reader with an understanding of the different roles and responsibilities of each.

: " ' . ..

3A.2 En Route Trqffîc Manager ■

The en route traffic manager’s main goals and responsibilities are to help assure the safety of the national airspace by managing the separation of traffic from all sources (i.e., commercial airlines, general aviation, and Department of Defense flights) and to create efficient use of the airspace for which he is responsible. He or she must coordinate air traffic management within a particular part of the NAS. Fora specified block of time, he must make estimations and predictions of the demand (the number of aircraft within a common airspace) of air traffic as well as the capacity (the maximum number of aircraft that can safely be accommodated and controlled) of a facility to handle it (Hoang & Swenson, 1997). Capacity is a dynamic and continually changing variable that is dependent on weather conditions, airport resources (e.g., runway configuration), meter gates (pre-defined transition zones where en route or center traffic is converged, sequenced and spaced), changes in capacity requirements of adjacent facilities (sector or ATC facility), and what the staffing level is at any given time forthat facility. The demand of air traffic changes with the “push.” or peak periods associated with departures and arrivals at the airports. These “push” periods often result in the air traffic demand exceeding the handling capacity of an Air Traffic Control (ATC) facility. When there is congestion and delay, traffic flow management methods are

67 used to ensure the safe flow of air traffic. These strategies consist of a variety of techniques that include the following:

• Pre-departure interventions

> Ground delay or ground stop

• En route interventions

> Rerouting or vectoring > Fix balancing > Airborne holding > Miles-in-trail > Speed control > Metering

3.4.3 AOC Dispatcher

The Airline Operations Center (AOC) component of a commercial airline is responsible for the safe planning and conduct of that airline’s flights. AOC dispatchers, who plan the routes that individual flights should follow, have safety of their flights as the most important consideration. However, within that constraint, their goal is the efricient and effective operation of their own airline’s schedule so that it is competitive with other commercial airlines. The dispatcher authorizes, regulates, and controls commercial airline flights according to governmental and company regulations that emphasize the expedition and safety of flight. Dispatcher responsibilities include the analysis and evaluation of meteorological information, computation of fuel requirements, preparation of the flight plan, authorization to release a flight for takeoff, delay or cancellation of a flight if unsafe conditions are present, and evaluation of the progress of a flight. Di addition to safety concerns, the dispatcher is responsible for factors such as cost, timeliness, and passenger comfort.

68 In an effort to meet their goals and priorities whencapaciQ^-Iimiting situations arise, the airlines may choose to change their plans without a request from the FAA to do so. Some of the strategies they may employ to reduce the risk of negative impacts to their operation are listed below:

• Pre-departure interventions

> Cancel or delay a number of their flights to a particular airport that is expected to have a reduced arrival rate > File their flights along an alternate route or altitude due to forecasts of ' poor weather or traffic along the normally filed route > Choose to file additional flights above the forecast arrival rate for an airport to provide a “reservoir” of flights if the forecast is not realized > Change fueling pfansja accommodate predicted delays (in response to V iT FAA advisories or through their own data sources)

• En Route interventions

> Request flight crews to request rerouting from the FAA if a problem is foreseen further along the route > Divert to designated alternate arrival airport > Request priority handling from AirTraffic Control

3.5 Summary

This chapter has given the reader a high-level overview of the work done by practitioners who comprise the AirTraffic Management System within the United States. This allows for an understanding of the context in which the participants in this study are situated, a cognitively complex environment filled with interdependencies, uncertainty, equivocality, and ambiguity.

69 CHAPTER 4

METHODS

4.1 Introduction

It is becoming increasingly clear that, when engaged in the investigation of the cognitive demands placed on practitioners in complex environments, researchers must use multiple methods of inquiry in order to achieve a “wide-angled lens” view of the joint cognitive system. It is only by interleaving the results of these multiple methods that one can hope to unravel all of the elements that lead to the complexities and interdependencies within these systems. Thus, multiple researchers and methods may come to be employed in a complex environment in an effort to arrive at a point where understanding and knowledge can inform futiue directions for developing cognitive aids to support the practitioners within that, and similarly complex, environments. This chapter describes for the reader the methods used in this descriptive study.

'-V -

70 4.2 Methodology

This section discusses the number of practitioners who participated in the study, from what organizations they belong, and how they were selected to participate. The research design and its setting are described, and the questions motivating this descriptive study are presented.

4.2.1 Participants

The participants in this study were^eight Airline Operations Center (AOC) dispatchers, chief dispatchers, or ATC coordinators (referred to from now on as dispatchers) from one commercial'air carrier and eight Air Route Traffic Control Center (ARTCC) Traffic Management Unit (TMU) traffic managers at four different en route centers. A supervisor at the AOC selected the dispatchers based upon dispatcher availability during the scheduled study session, as well as some level of expertise in their role as dispatcher. Because of practical constraints on access to these individuals, there was no effort made to ensure that they had experience working the city-pair to which they were assigned. However, given that most difficulties found within the National Airspace system (NAS) are not unique to a particular airport, each dispatcher had the knowledge and experience necessary to work on a task involving any city-pair. The traffic managers were selected by a supervisor within their TMU, and these selections were primarily based on availability of the traffic manager during the scheduled session, as well as expertise with the particular city-pair in the scenario. Each AOC dispatcher was paired with, an ARTCC traffic manager at the ea route center for the destination city for each scenario. For example, for the scenario involving the city pair Dallas-Fort Worth, and Minneapolis-SL Paul, a traffic manager fix)m the Minneapolis-St. Paul En Route Center was paired with a dispatcher located at the air carrier’s AOC. 71 The decision to use dyads as the unit of analysis allows fora more focused perspective on the use of the scenario data and the unique knowledge shared because interaction between the participants can be more easily examined and their activities followed than would be possible for a larger team. However, the researcher recognizes that in reality a larger number of people would be involved in the analysis of trend inefficiencies occurring in the NAS and in the problem-solving process as they pursue solutions to these difficulties.

4.2.2 Setting

The study took place with the AOC dispatchers and the ARTCC traffic managers located at their respective work sites. The dispatchers participated in an office cubicle containing a telephone and a computer with a modem. The traffic managers were situated within their Traffic Management Unit (TMU), in an available office, or in a training classroom, depending on the availability of space at each particular en route center. The traffic managers used a laptop computer supplied by the investigator and had access to a telephone. A telephone tape recorder was connected to the telephone that the traffic manager was using, and recorded the conversation between the dispatcher and the traffic manager. A video camera was placed in a way to capture the laptop computer screen.

The investigator was located at the ARTCC with the traffic manager.

4.2.3 Design

The study was designed as a descriptive study where the collaborative performance of dyads on a problem-solving task ia a particular scenario was studied in relation to the psychological questions of interest.

72 I / . ' k

4.23.1 Scenarios

The scenarios used in this research represent a selective capture of salient features of past actual events occurring in the National Airspace System (NAS) as produced by a search using the Post-Operations Evaluation Tool (POET) (http://iwse.eng.ohio-state.edu/phiIsmith/aviation.htm). Each scenario indicates an example of inefficiency occurring for a particular set of flights between two cities. Five different scenarios consisting of five different city-pairs were developed for use in this study. The city-pairs used are the following:

• Chicago (ORD) to Atlanta (ATL) • Dallas-Ft. Worth (DFW) to Atlanta (ATL) • Dallas-Ft. Worth (DFW) to Minneapolis-St. Paul (MSP) • Chicago (ORD) to Boston (80S) • Dallas-Ft. Worth (DFW) to Newark (EWR)

Table 4.1 illustrates the number of dyads that performed the study task for each scenario. The members of each dyad are identified by both scenario number and dyad number (e.g., T n indicates the traffic manager in scenario I, dyad I, and Du refers to the dispatcher in scenario 1, dyad 1).

73 Scenarios Number of dyads

2 Scenario 1 ORD to ATL Dyadu (Tn, Du) Dyadj.i (T 1-2, D1.2)

2 Scenario 2 Dyad 2.t(T2.i, D^t) DFW to ATL Dyad 2.%(T:.2, D2.2)

2 Scenario 3 DFW to MSP Dyad3.t (Tj.!, D 3.1) Dyad3.z(T3_2, D 3.2)

1 Scenario 4 ORDtaBQS . Dyad4.t (Tj.t, D4.1)

Scenario 5 1 DFW tdEW R' Dyadjii (Tg.t, D 5.1)

Table 4.L Study design —Scenarios used and number of dyads per scenario

4Z23.2 Guiding questions

The psychological questions that have motivated this study guided “the construction of the test scenarios, the raw data [that] were gathered, and the kind of concepts [that were] brought to bear” (Woods, 1993, p. 243) in the analysis of the behavior of the distributed problem-solving teams. By formulating these questions, a background frame allowed the researcher to approach the study with a clear idea of the types of concepts for whicirshe was looking (i.e., structuring her ‘looking’), yet allowed for an openness to discovering phenomena not anticipated prior to the study (cf., e.g., Psathas, 1990, 1995). The guidingquestions that motivated the present study include the following:

74 How do spatially distributed, inter-organizational members of a dyad, who have different priorities, perspectives and knowledge, collaborate to build mutual understanding of existing problems, identify alternative solutions to those problems, and evaluate these proposals?

Do team members pool their unique knowledge in order to achieve mutual understanding? What are the elements in the interaction that contribute to or inhibit this knowledge sharing?

How do the team members engage in the process of situation assessment as they proceed in identifying the problem present in the task scenario? Do they jointly assess the situation bringing in the data presented in the shared display, as well as identifying data, information, and knowledge that is missing? How do the partners proceed with their task when data they deem necessary is not available to them?

• How do the cognitive artifacts used in this study facilitate or inhibit the collaborative process between these dyad partners?

• Are there ways in which the shared display reduces the difficulty of formulating what is mutually known? How does it facilitate the search for information?

What does the shared display technology allow the partners to do that couldn’t be done,otherwise? r.:

What kind of support or display tools would make more efScient the communication, collaboration and problem solving in a complex, distributed environment?

75 .-Xr' ' - ' - -

4,2A Procedure

This study examined rather short periods of time (approximately one hour in length) between two people who did not know each other and who had a clearly defined task to do. At the beginning of the session (only one experimental session per dyad was conducted due to the distributed nature of the environment and organizational constraints), the researcher introduced herself, described her program of study, and explained that this study was in partial fulfillment of her PhD. She also indicated that the interactions would be both audio- and videotaped, but that their conversations would remain anonymous to those outside the research team. The researcher then had each partnër introduce himself^ to the other. . V . ■

4.2.4.1 Training - -

Following the introductions, the participants were guided through a training session that consisted of a conceptual presentation describing all of the features and data found within each slide. A different city-pair scenario than those used in the study was used for training. Importantly, the training did not prescribe what data to use to support the dyad’s collaborative discussion. (See Appendix C for a description of the training scenario.)

NetMeeting’s capabilities and how to control them were demonstrated. The participants were invited to practice with the pointing feature of NetMeeting, to exchange control of the telepointer, and to navigate between the slides. (These features are described in the Tools section of this chapter.)

^ Di this study all participants were men; therefore, the preponderance o f the male pronoun is nothing more than a reflection of this. 76 4.2A2 Task Instructions

Following the training, the researcher instructed the conversational partners in their collaborative task. Research has shown that how people view their goals in a particular interaction (i.e., whether it is predominantly cooperative, competitive, or independent) profoundly affects their orientation toward each other (Deutsch, 1985). Studies have documented that people engaged in cooperative interactions share information, take each other’s perspective, communicate and influence effectively, assist and support each other, openly discuss opposing ideas, and constructively manage their conflicts (e.g., Deutsch, 1985; Johnson, Johnson, & Maruyama, 1984). For these reasons, the instructions given to each dyad emphasized the team focus and collaborative nature of the task. The traffic manager-dispatcher dyad was told that their task goal was to jointly arrive at a description of the problem(s) that they found occurring between the city-pair in the scenario. They were to work as a collaborative team as they generated the fullest range of solutions they thought could help resolve the problem(s) identified. These'partners were also instructed to evaluate the alternative solutions generated for their potential of eliminating or alleviating the identified probIem(s). (See Appendix D for the specific set of instructions.) Once the instructions were given and the participants had the opportunity to ask questions about the instructions, the collaborative session began. The dyads participated in a fiee-interaction format in which how the task process was approached and continued was determined by the participants. There was no time limit placed on the discussion by the researcher; however, since this study occurred at the participants’ places of work and was during their work day, other forces may have placed constraints on the duration of the interaction (e.g., supervisors, self, or colleagues). When the participants decided between themselves that they had completed the task, the researcher was informed, the partners said their good-byes, and the

77 connection was ended. Each, participant then completed a demographic questionnaire that described his aviation-related work history, as well as previous experience with computers (see Appendix B).

4.3 Tools

This section describes the tools that were used by the participants as they interacted with one another on the research task. Also in this section is a list of tools that were used by the research fordata collection.

4.3.1 Tools used by participants

The tools chosen to assist/enable the interaction and communication between dyad partners include the language (spoken, rather than text-based), selected slides from a search done with a post-operations evaluation tool, Microsoft NetMeeting (an internet-based tool enabling real-time interactions), and the telephone. The following paragraphs describe these tools.

4.3.1.I Language

Communication, as a joint cognitive activity, is mediated by a variety of tools, and language is the most significant of these (Vygotslqr, 1981; Wertsch, 1991). It is easy to ignore language as a tool, but in fact, it is a tool for collaboration, as well as a medium of communication. ‘'Language must be viewed as a medium to create meaning and shared understanding rather than a simple exchange of information; language should evoke images, impressions, reasons, memories and thought’ (Schrage, 1990, p. 83). The medium used by the participants in this study was spoken language rather than the text-based language often used in computer-mediated communications.

78

'I- ¥ 4.3.1.2 Slideshow

A slideshow of three to four slides for each scenario was developed by capturing relevant data from searches using the Post-Operations Evaluation Tool (POET) and placing them within a slide-building tool. A slide affords the ability to chunk relevant data into a viewable space that allows the user access without requiring the cognitive effort required for searching through multiple displays for data needed for the problem-solving task. For example, in Figure 4.1, the data available are the following:

Data about the search (i.e.. Dates included in the search (Dates); Departure Time (DepartTime); Departure Airport (DptApt); Arrival Airport (ArrApt) ) Filed Route for all flight instances resulting from the search Data about the AirFuel Bum of the Total Number of Instances (i.e.. Average Planned AirFuel Bum; Average Actual AirFuel Bum; Average Difference in AirFuel Burn between Planned and Actual AirFuel Bum; Average % Diffèrençein AirFuel Bum between Planned and Actual AirFuel Bum) Data about the AirFuel Bum of the Total Number of Instances (i.e.. Average Planned AirTime; Average Actual AirTime; Average Difference in AirTime between Planned and Actual AirTime; Average % Difference in AirTime between Planned and Actual AirTime) Data about the AirFuel Bum of the Total Number of Holding Instances (i.e.. Average Planned AirFuel Bum; Average Actual AirFuel Bum; Average Difference in AirFuel Bum between Planned and Actual; Average % Difference in AirFuel Bum between Planned and Actual) Data about the AirTime of the Total Number of Holding Instances (i.e.. Average Planned AirTime; Average Actual AirTime; Average Difference in AirTime between Planned and Actual; Average % Difference in AirTime between Planned and Actual) Data about the AirFuel Bum of the Total Number of No-Holding Distances (i.e.. Total Number of No Holding Distances; Average Planned AirFuel Bum; Average Actual ADFuel Bum; Average Difference in AirFuel Bum between Planned and Actual; Average % Difference in AirFuel Bum between Planned and Actual)

79 Data about the AirTime of theTotal Number of No-Hblding Instances (i.e.. Average Planned AirTime; Average Actual AirTime; Average Difference in AirTime between Planned and Actual; Average % Difference in AirTime between Planned and Actual) A map indicating the filed route as well as the actual routes of the individual flight instances.

The slideshow permits a slide-by-slide discussion format. It also supports easy navigation between slides so the practitioners can move back and forth within the slideshow^ gathering data from each slide and integrating it into their ongoing discussion.

UfBUlBil

i* RicSun Uncm Cb«| ii3i« naao 2475S 2S3SS4 «rmeUneottmn) 27.8 9iiu« taiEa« IJSSO t t s t * . 320

Figure 4.1. Example of how a slide allows relevant data to be chunked.

4.3.1.4 Microsoft Windows®*NetMeeting

NetMeeting is ashared window system that enables existing computer applications to be shared in the context of a real-time teleconference (Lauwers & Lantz, 1990). It allows single user applications to be invoked on a single workstation mm- and then be displayed on any number of other workstations. The NetMeeting application enforces a strict WYSIWIS (What-Ybu-See-Is-What-r-See) interface (i.e., 80 Stefic, Foster^ Bobrow, Kahn, Lanning, & Suchman, 1987). Both partners in the conversation had available to them, a shared “telepointer,” manifested by a small icon on the screen and controlled by means of a mouse. The telepointer is a shared pointer that is controlled by one person at a time, and is visible to the other participants in the shared environment. When a participant wishes to take control of the telepointer, he clicks the mouse, which then transfers control. The person who is in control of the telepointer is identified by his initials that are attached to the pointer icon. The voice channel feature of NetMeeting was not utilized in the present study. NetMeeting, therefore, provides a distributed environment that facilitates access to common tasks by a group of persons in different locations.

43.1.5 Telephone

Because of the constraints of field research, the researcher must depend on the resources available in that field. The telephone was chosen as the medium for the audio part of the interaction (rather than the voice channel feature of NetMeeting, between the dyad partners because of the technological limitations of using NetMeeting via modem (which was what was available at the study sites) rather than a higher bandwidth connection. Even though the telephone is the primary electronic medium for interpersonal communication occurring between people in distributed environments, a question rarely asked is how telephones affect communicative interactions (Hopper, 1992). fn spite of the fact that parmers communicating via the telephone cannot see one another, do not share a common physical space, and their conversation is constrained to sounds divorced from the rest of observable action in their conversation, studies have shown that this form of dialogue remains more like face-to-face conversations than different. For example, Rutter (1987) reports on research that has contrasted face-to-face speech events with audio-only events and found the mediums are remarkably similar in such features as turn taking, interruptions and pause lengths (see Cook &Lallijee, 1972; Rutter & Stephenson, 1977; Sellen, 1995; Short et al., 1976). 81 Because much of the problem-solving communication among members of the Air Traffic Management (ATM) System occurs over the telephone and is seen as an integral part of their work environment, it was anticipated that how the participants in this study interacted through this medium would be reflective of their everyday use of it.

4.3.1.6 Summary: Tools Used by Participants

By combining the telephone for voice communication, NetMeeting for its real-time WYSIWIS and telepointer capabilities, and POET slides for providing a firarae of reference for conversation, asynchronous, technology-mediated communication support system was provided to the dyad partners. This system was used to mediate the collaborative problem solving and knowledge sharing between individuals from two highly interdependent organizations collaborating on a complex task.

43.1.7 Tools used for data collection

The following tools were used to aid the researcher in collecting data found within the interactions of the participants (botli the verbal conversations and the pointing behavior via NetMeeting).

• Telephone tape recorder • Audio tapes • Video camcorder • Video tapes • Transcripts of verbal protocols

With the audio recording equipment, data was obtained to capture traces of the data acquisition and knowledge-sharing sequences via the verbal interaction as the parmers engaged in situation assessment, hypothesis generation, and proposal and

82 evaluation of alternative solutions. Records of reference by use of the pointing device via NetMeeting were gathered &oni videotaped recordings of screen actions. The use of audio- and videotapes is important for this study because they enable repeated observations of the interaction behavior between the participants. As Heritage (1988) points out, detailed analysis cannot be done without repeated viewings, and “is indeed already analysis in itself.” Repeated viewings by the researcher of the tapes and transcriptions made from the audio tapes allowed the investigator to attend to domain-significant events and details that may have been missed in in situ observations and early on in the analysis. “Transcription works as a major ‘noticing’ device....alldw[ingj the analyst to build an accessible data archive” (ten Have, 1999, p. 77-78). That is, transcription helps the researcher to focus attention on the cognitive behaviorof the conversational parmers. Thus, verbal and nonverbal (e.g., the pointing behavioc).protocols were built from a variety of data sources, leading to inference? about the'cognitive activity of partners engaged in a complex, collaborative problem-solving task.

4 .5 Task

The characteristics that led to the selection of the cognitive task used in this study included that it be challenging, realistic, appropriate for participants, not too large, feasible in the time available, within the sphere of knowledge of the investigator, relevant for the aviation domain, as well as serve to extend the research literature. Thus, the task selected was one that would engage the participants in collaborative problem-solving, requiring that they use data provided in a scenario of a particular city-pair (a departure city and a destination city), as well as knowledge shared through interaction with them partner. The activities suggested by the researcher in accomplishing the task included ident%ing any problem(s), generating alternative solutions for the identified probIem(s), evaluating those alternatives, and selectingthebest solution fixim among those proposed (see Appendix I for the instructions that were given). Di short, the task is one of problem discovery and 83 divergent cognitive activities (e.g., generating ideas, alternatives, explanations, proposals, solutions, and other creative intellectual inputs), and is carried out through task-relevant dialogue. The problem identiffcatioa part of the task can be seen as an abductive reasoning, or inferencing to the best explanation (Tosephson, 2000). The participant- pairs were presented with data of events that have occurred for particular flights, for a specified time period, for a specific city-pair. Using and sharing other relevant data and knowledge that each participant may have, the partners were to generate a set of alternative solutions that would eliminate or reduce the situation(s) found in the scenario. This task can also be seen as one of sensemaking, or making sense out of connections among sequences of events after they have occurred (Rsher, 1985; Weick, 1995). The decision makers start out with an outcome (the result of a particular flight from one city to another over a specified period of time) and then attempt to make sense of that outcome by constructing a plausible causal model to explain the available facts. Because the data provided in the scenario are complex, the participants must not only assess what of that data is important to attend to, but also must determine how to integrate that data with the knowledge that they share with one another through their discussion. Once integrated they must then combine it to make the necessary inferences and arrive at a probable solution to the identified problem(s). This task can be viewed as a “wicked problem” (Conklin, 1987) as it has as characteristics the making of a lot of assumptions, educated guesses, and decisions under conditions of uncertainty and equivocality, where information available to the decision makers is incomplete and ambiguous. It involves collaborative interaction witfi another, looking for a solution that considers both airline and air traffic concerns and priorities. This task requires decision making under uncertainty (Kahneman, Slovic, & Tversky, 1982), which has been defined in various ways, fiom the lack of a discernable pattern among multiple alternates (Farace et al., 1977), to the absence of requisite information (Weick, 1979), to the lack of attributional relationships (Berger 84 & Calabrese, 1975). Each participant alone does not possess the set of data and knowledge needed to assess the situation. Only by gathering what is relevant to the decision, from the scenario and from each other, can they reduce that uncertainty. Not only does this problem involve uncertainty, but also equivocality. Equivocality refers to the existence of multiple interpretations for a given set of information. “Under equivocality, decision makers may not know how to interpret the information they have at hand, or what information to gather to resolve the problems they face” (Galegher & Kraut, 1990, p. 7). To reduce this equivocal situation, the conversational partners must involve themselves in a process of generating shared interpretations of the problem and proceed to proposing and evaluating potential solutions based on those interpretations (Daft & Lengel, 1986).

4.6 Summary

This chapter has outlined the methodology used in this descriptive study, providing the reader with an understanding of who participated, where the study occurred, and the research design. Also presented was a description of the tools used by the participants as they worked and those used by the researcher for data capture. The research problem-solving task was described to allow the reader a better understanding of what the participants were undertaking.

85 -

CHAPTERS

RESULTS AND DISCUSSION

5.1 Introduction

The goal of this chapter is to present assessments of the cognitive process of problem solving and collaboration between two experts with different, as well as over­ lapping, knowledge and expertise as they jointly work on a common task. Another aim of this analysis is to examine how the distributed cognitive process was influenced by the artifacts that mediated and facilitated the interaction (i.e., the telephone and the shared display). Finally, this chapter aims to take the highly context-dependent analysis and convert it to a description that is concept speciGc and domain independent (Woods, 1993). The following analysis is a descriptive account of collaborative interactions between members of a dyad as they work on a problem-solving task in a complex domain*. Eowever^one cannor minimize the iinportance of descriptive analyses as they can be used to direcrand mjprm future empirical and analytical investigations that are focused on particalar; variables of interest. The analysis meAodpIb^ u ^ d in this research involved a sequential examination of the transcribed tape recordings of the interactions between the members of each of the eight dyads. The audio tapes provided the content of the transcripts, which then became descriptions of the actual verbal behavior of the dyad, and the video tapes were viewed to map any relevant non-verbal behavior (e.g..

86 pointing) to the appropriate place in the transcript. The process of finding patterns in the data was realized by moving iteratively from observation to theory and back again. The abili^ to articulate themes and categories was made possible as familiarity with the data grew and was continually re-evaluated against those data Because the interaction of individuals within groups creates a certain degree of interdependence, each interacting dyad was treated as a unit of analysis. However, because each member brings different expertise and knowledge to the distributed system, some distinction is made in parts of the analysis, where relevant, as to who contributed what to the interaction.

This chapter includes analysis and discussion of the following:

• The sharing of uniquely held knowledge (Section 5.3) • Use of the shared display (Section 5.4.2) • Use of analogy and storytelling (Section 5.4.3) • Dealing with absence of data (Section 5.4.4) • Errors in situation assessment (Section 5.4.5)

The transcription scheme used in this study is described in Table 5.1.

where T represents the traffic manager in the pair; S ts the scenario number from I to 5; P (either a 1 or a 2) indicates what dyad it is in scenario S; M is Ts-pN the number of the turn in the discussion; for example, Ti.%5 turn 5 (N) for the traffic manager (T) in scenario 1 (S) of Dyad 2 (?) Ds.pN represents the same as above except D is for dispatcher

(?) mdicates a missing, maudible, or incomprehensible utterance •••• indicates words or utterances in the transcript omitted by the researcher if deemed not relevant for the current discussion {action} indicates some action taken by the speaker during an utterance (e.g., [pause} or [pointing} [inferred word] indicates word(s) inferred by the researcher for those uttered by the speaker but unclear m. the recording

Table Transcription Scheme ,

87

J1 ....

- 5.2 Scenarios

The five scenarios used in this study are described below, fii these descriptions, a “flight” is defined to be a particular combination of an origin, destination, and scheduled departure time that can occur on a daily basis. Therefore, a “flight instance” is one particular aircraft departing on one particular day with a specified origin, destination, and scheduled departure time of the flight being studied. Each scenario description is organized in the order that the slides appeared in each slideshow with a verbal description o f the data found on each slide, as well as an illustration of that slide.

52.1 Scenario 1. Chicago to Atlanta

This scenario consists of three slides and describes flights from Chicago to Atlanta scheduled to depart at 1115Z. The first slide consists of all flight instances, and each of the next two slides consists of an individual flight instance.

Slide I (Figure 5.1):

During the month of May 1998 for all Chicago to Atlanta flights departing Chicago at III5Z with the filed route ORD.ÆON.JDNV..TTH..BWG.RMGLATL, there were 27 total flight instances. Of these 27, five instances (18.5%) involved airborne holding (circular/èllipfical patterns in the sky) and 22 did not. On average for the 27fIighE.instances, the planned Air Fuel Bum was 9,128.0 pounds and actual AirFuel Ftrm w à^0,446 pounds, which was 1,318.0 pounds (14.4%) more than was planned. The average planned AirTime for these flight instances was 80.1 minutes, with the average actual AirTime being 95 minutes, or 18.6% longer than was planned. On average for the five flight instances that experienced airborne holding, the planned Air Fuel Bum was 9,192.4 pounds, and the actual Air Fuel Bum was 11,668.0 88 pounds. This resulted in an actual AirFuel Bum that was 26.9% higher than was planned. The average planned AirTime for these five flight instances was 80.4 minutes, with an average actual Air Time of 108.2 minutes, 34.6% longer than was planned. For the 22 flight instances that did not experience airborne holding, the average planned Air Fuel Bum was 9,113.4 pounds, and the average actual Air Fuel Bum was 10,168.4 pounds, a difference of 1,055.0 pounds, or 11.6% higher AirFuel Bum than was planned. On average, the planned AirTime for these 22 flight instances was 80 minutes, and the actual AirTime was 92 minutes, 15% over what was planned. The map for these flight instances indicates that, for all 27 instances, the same route was filed by the airline (depicted by the gray line). The black lines in Figure 5.1 illustrate the actual routes that the 27 flight instances flew. It is clear from this display that, in addition to airbome holding, there is frequent vectoring to the southwest as the flights approach Atlanta. This combination of vectoring and holding is shown more clearly for the individual flight instances in Figures 5.2 and 5.3.

89 Al FueButn Uncon; Obtl 9.13Z* n^sao 2.475-6 2E35:A A«r»neUneacfm«il aa« ioa2 27.8 34.6 % A Ai FudBuni Uncott. Ob>) 9 .1U 4 1 0 .1 6 6 4 IjIK O 11.6% A. AtTins uncon: 1 2 0 1 5 0 % A

Figure 5.1. Slide I of Scenario I: Chicago to Atlanta

Slide 2 (Figure 5.2):

This flight instance was of Aircraft Type SuperSO that departed Chicago on May 10,1998 with a scheduled Departure Time of 1115 Z and an actual departure time of 1113 Z (Out Time). The planned Off Time was 1128 Z and the actual Off Time was 1122 Z. This indicates that the actual Taxi Out time from pushing off from the gate (Out Time) to getting off the ground (Off Time) was 4 minutes less than was planned. The actual AirFuel Bum was 343% higher than was planned. AirTime was planned for 79 minutes, but the actual AirTime was 115 minutes, 45.6% longer than was planned. The actual Total Fuel Bom for this flight instance was 13.1% more than the planned 10,700 pounds.

90 The time the aircraft was estimated to land (On Time) was 1259 Z, and the actual time it landed was 1317 Z, a difference of 18 minutes. The actual time of arrival at the gate (In Time) for this aircraft was 16 minutes later than planned. Therefore, the actual Taxi In time was 2 minutes less than was planned. The map for this flight instance indicates that it experienced airborne holding close to Atlanta but otherwise flew the route as filed.

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unUrcon. assio M5W10

Figure 5.2. Slide 2 of Scenario I: Chicago to Atlanta

Slides (Figure 5.3): -.I,

This flight instance was an Aircraft Type SUPERSO that departed the gate (Out Time) at Chicago on May 19; 1998 at 1115 Zasscheduled and left the ground (Off Time) at L128Z as planned. The actual AhrFuel Bum was 12.0% higher than was planned, and the actual AirTime was 20.5% longer than was planned. However, the

91 actual Total Fuel Bum for this, flight instance was 1.8% less than the planned 11,100 pounds. The time the aircraft was estimated to land (On Time) at Atlanta was 1258 Z, and the actual time it landed was 1302 Z, a difference of 4 minutes. The planned time of arrival at the gate (In Time) for this aircraft was 1305 Z, but it actually arrived at 1309 Z, a difference of 4 minutes. The map for this flight instance illustrates the vectoring to the southwest that occurred as it approached Atlanta.

AitFueBunUnctnr.[la| 9J1S0 10.101.0 IJ850 UOX

r»djn(ng5| OvtTmeg] 1 Offuw0 unnmeg] tnTifnegi I H i i a i i i i i

Figure 53. Slide 3 of Scenario 1: Chicago to Atlanta

9 2

....

- V 5.2.2 Scenario 2. Dallas-Fu Worth to Atlanta

This scenario consists of four slides. The first slide consists of all flight instances, and. each of the next three slides consists of aa individual flight instance.

Slide 1 (Figure 5.4):

During the month of May 1998 for all departures with the filed route DFWJDALL4MEI.LGC7.ATL from Dallas-Fort Worth to Atlanta, there were 314 total flight instances. Of these 314, forty-two involved, airbome holding (circular/elliptical patterns in the slqr) and 272 did not. On average for the 314 flight instances, the planned Air Fuel Bum was 9,088.5 pounds, and the actual Air Fuel Bum was 10,006 pounds, ora 10.1% increase in AirFuel Bum than was planned. The average actual AirTime for these flight instances was 4.2% longer than was planned. Of the 42 flight instances that experienced airbome holding, the average planned Air Fuel Bum was 9,309.8 pounds, and. the average actual AirFuel Bum was 11,411.9 pounds. This results in an average of 22.6% higher actual air fuel bumed than was planned. On average, the actual AirTime for these 42 flight instances was 20.7% higher than was planned. On average for the 272 flight instances that did not experience airbome holding, the planned AirFuel Bum was 9,054.3 pounds, and the actual AirFuel Bum was 9,788.9 pounds, an 8.1% increase in fuel bum than was planned. The average actual AirTime was 1.7 minutes over what was planned. The map for these flight instances indicates that there was a great deal of unplanned vectoring and rerouting while en route to Atlanta (depicted by the black lines). The flown routes for son&flight instances varied from the Bled route (illustrated by the lighter gray line) immediately out of Dallas-Fort Worth while others experienced variations later in the flight.

93 a

42 AirueBunUneacds) ajoae n.4na 21021 228% & AtTiiieUncemtiiiiil __.»5__ 120L1_ 2 0 6 207% t 272 ArFwSunUncoicd»! &054.3 17803 734.6 01% A. A>TimeUncai:rn«il 314 101.1 1.7 1.7% A

Figure 5.4. Slide L of Scénario 2: Dallas-Fort Worth to Atlanta

Slide 2 (Figure 5.5):

This flight instance was an Aircraft Type SUPERSO that departed Dallas-Fort Worth on May 15,1998 with a scheduled departure time of 2(K)0 Z and an actual departure time of 2005 Z(OutTûne). The planned Off Time was 2016 Z and the actual was 2023 Z. This indicates that thé planned taxi time firom pushing off from the gate (Out Time) to getting ofr^th&ÿound(Off Time) was Idminutes, but actually took 18 minutes, a 2-minu%(üfrêfeiicé: The planned AirFuel Bum was 11,794 pounds, with, the actual being 1618% higher. Airlime was planned for 100 minutes but the actual AirTime was 116 minutes, or 16 minutes longer than was plarmecL The

94 actual Total Fuel Bum for this flightinstance was I4>700 pounds, 5.8% higher than was planned. The time the aircraft was planned to land (On Time) was 2201Z, and the actual time it landed was 2219 Z, a difference of 18 minutes. The planned time of arrival at the gate (In Time) for this aircraft was 2208 Z, but it actually arrived at 2224 Z, a difference of 15 minutes. The map for this flight instance indicates that it experienced airbome holding close to Atlanta but otherwise flew the route as filed.

1 AiFueBuRtUncoitObt) U J94.0 13.7800 1 J8 6 0 168%

______14.7000 ____ m o 58% AitTimeüncoir.tr

ToiiMnaml •20 •266% TaôOul(irè«l ISO 18.0 2 0 125% Outr«ne£Zl m i abs SO ONTirnem 2016 2023 r.o .. . Onr«ie(21 2201 _ _ 2 2 1 £ L 160 ...... rn r« M 0 2208 .. m 160

Figure 5.5. Slide 2 of Scenario 2: Dallas-Fort W brt^o Atlanta

Slide 3 (Figure 5.6):

This flight instance was anFlOO that departedDallas-Fort Worth on May 29, 1998 with a scheduled departure time of 1643 Z and an actual departure time of 1704 Z

95 a , ^ wAr-,-.

(Out Time). The actual OffTirae was I716,Zil8^minutes later than planned. The planned AirFuel Bum was‘S,276 pounds and the actual was 10,150 pounds, or a 22.6% increase in Air Fuel Bum over what was-planned. Actual AirTime was 4 minutes longer than was planned. The actual Total Fuel Bum for this flight instance was 10,600 pounds, or 15.2% more total fuel bumed than the planned 9,200 pounds. The time the aircraft was planned to land (On Time) was 1848 Z and the actual time it landed was 1905 Z, a difference of 17 minutes. The planned time of arrival at the gate (In Time) for this aircraft was 1854 Z, but it actually arrived at 1908 Z, a difference of 14 minutes. The map for this flight instance indicates that the flown route deviated from the filed route about one third of the way into the flight. It deviated north of the filed route, arriving at a different arrival fix than was filed.

ln3lonc»:l?U2yUJ2S)

Ait Fuefiun Uncottff»] 8.27R0 10.1500 1.87*0 22.6%

Total FudBuirdal l o m p 1.4000 152% Airme Uncotrlmml 1050 1050 *0 18%

Taa WminjI 50 10 -10 -500% Ta»OufRiral 150 110 •10 -200% OutTioaEI 1843 170* 21.0 OKTinaiZ] 1658 1716 150 QnTinem 1848 1305 17.0 ...... rm eP l . J n 185* 1308 U Q ...... - ...... - — ------

Rgure5.6. Slide 3 of Scenario 2: Dallas-Fort Worth to Atlanta

96 * r - y %

SIide£(Hgure5J): ^ . V î '

This flight instance was an FlOO that departed the gate at Dailas-Fort Worth on May 27,1998 at 1732 Z (Out Time) as scheduled and left the ground (Off Time) at 1742, five minutes earlier than scheduled. The planned Air Fuel Bum was 8,330 pounds and the actual was 10,450 pounds, or a 2,120 pounds (25.5%) difference. AirTime was planned for 103 minutes, but the actual was 129 minutes (25.2%) longer than planned. The actual Total Fuel Bum for this flight instance was 18.5% higher than the planned 9,200 pounds. The time the aircraft was planned to land (On Time) at Atlanta was 1930 Z, and the actual time it landed was 1951Z, a difference of21 minutes. The planned time of arrival at the gate (In Time) for this aircraft was 1937 Z, but it actually arrived at 1956 Z, 19 minutes later than planned. The map for this flight instance indicates that it experienced airbome holding prior to entering the Atlanta airspace, but otherwise flew the route as filed with only minor deviations.

97 ïîSjËOini c3 3

Ait FiidBum UncantObs) 8J3aO 154500 21200 235%

Total rudBunflbsl 9 ^ 0 lOjOOO 17000 105% AitTmeUncon.lminl 1020 1230 230 232%

TadlrWwl 7.0 30 •20 -206% TaiiOultiMnsl 150 100 •50 •323% Qi*.T«ne0 1732 1732 00 QIMineZl 1747 1742 •30 OnlineSl 1330 1951 21.0 . , _ . InTMZL ...... 193T 1953 130

Figure 5.7. Slide 4 of Scenario 2: Dallas-Fort Worth to Atlanta

98 5.23 Scenario 3. Dallas-Ft. Worikto Minneapolis-St. Paul

This scenario consists of four slides. The first slide consists of ail flight instances, and each of the next three slides consists of an individual flight instance.

Slide 1 (Figure 5.8):

During the month of May 1998 for all departures with the filed route DFW.TEX5.TUL J25. MCWJCASPR2MSP from Dallas-Fort Worth to Minneapolis- St. Paul, there were a total of 136 flight instances. On average, the actual AirFuel Bum was 11,331.3,6.4% higher than the planned Air Fuel Bum of 10,653.7. The average planned AirTime for these flight instances was 118.4 minutes, and the average actual AirTime was 118.8 minutes. The map for these flights instances indicates that the actual routes (illustrated by the black lines) for many of them involved deviations from the filed route (illustrated by the gray line), some deviating immediately out of Dallas-Ft. Worth, while others deviated later in the flight. It appears that the arrival fix for some of the flight instances was also changed.

99

- - V .. - .. ^ ‘m i L ï . w m :

Rgure 5.8. Slide 1 of Scenario 3: Dallas-Fort Worth to Minneapolis-St. Paul

Slide 2 (Figure 5.9):

This flight instance was an FlOO that departed Dallas-Fort Worth on May 18^ 1998 with a scheduled departure time of 0015 Z and an actual departure time of 0103Z, a 48-minute difference. The planned Off Time was 0032 Z and the actual time off was 0112 Z. This indicates that the actual Tim Out time was reduced by 8 minutes. The planned Air Fuel Bum was 9,702 pounds and the actual was 14,110 pounds, or 45% more fuel burned than was planned. AirTime was planned for 120 minutes but actually was 182 minutes, 62 minutes (51.7%) longer than was planned. The actual Total Fuel Bum for this fli^ t instance was 14^500 pounds, 36.8% more than the planned 10,600 pounds. The time the aircraft was planned to land (On Time) was 0229 Z, and the actual time it landed was 04142^ a difference of 105 minutes. The actual time of

100 arrival at the gate (Di Time) was also 105 minutes later than planned, suggesting that the planned and actual Taxi hi times wer&the same^ The map for this flight instance indicates that for most of the flight it flew as filed. However close to Minneapolis airspace, it encountered airborne holding and then jogged a little to the west of the filed route on its approach into Minneapolis-St. Paul.

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hlim«g| a za

Rgure 5.9. Slide 2 of Scenario 3: Dallas-Fort Worth to Minneapolis-St. Paul

Slide 3 fRgure 5.10):

This flight instance was a SIJPER80 that departed Dallas-Fort Worth on May 24,1998 with a scheduled departure time of 0123 Z and an actual departure time of 0121Z. The planned Off Time was 0144 Z and the actual Off Time was 0133 Z. This indicates that the planned Taxi Out time ftom pushing off from the gate (Out Time) to getting off the ground (Off Time) was 9 minutes less than what was 101

. . .. -,ç, planned. The planned Air Fuel Bum was 13,426 pounds, and the actual was 14,280 pounds. AirTime was planned for 113 minutes, but the actual AirTime was 120 minutes, or 7 minutes (6.2%) greater than planned. The actual Total Fuel Bum for this Prght instance was 300 pounds (2%) more than the planned 14,700 pounds. The time the aircraft was planned to land (On Time) was 0334 Z and the actual time it landed was 0333 Z. The planned time of arrival at the gate (In Time) for this aircraft was 0338 Z, but it actually arrived at 0339 Z, a difference of 1 minute. The map for this flight instance indicates that the flown route deviated early in the flight to the east from the filed route, and then rejoined it shortly before entering the Minneapolis-St. Paul airspace.

g

/UFweunUncatgi»! UCSO I«att0 854.0 &4X

roUiFtaSurdiil «4.7000 1SDOOO 3000 20% A>r>MUncaK(m| 1110 1200 7.0 02%

rcdMminil 40 00 20 500% TcaOulmral 21.0 120 ■30 -423% Outrmeg] 0121 0121 ■20 ORrmdZt 0144 0133 ■11.0 OnTineg] 0334 0333 ■1.0 [ InrmeH 0330, ..... 0333 , 10

Figure 5.10. Slide 3 of Scenario 3: Dallas-FortWorth to Minneapolis-St. Paul

102 Slide 4 (Figure 5.11):

This flight instance was an FlOO that departed Dallas-Fort Worth on May 09, 1998 atlSlO Z as scheduled and left the ground (Off Time) at 1326Z, five minutes earlier than planned. The planned Air Fuel Bum was 8,544 pounds, and the actual was 9,670 pounds, or a higher fuel bum of 13.2%. AirTime was planned for 114 minutes, and the actual AirTime was 115 minutes. The actual Total Fuel Bum for this flight instance was 6.2% higher than the planned 9,700 pounds. The time the aircraft was planned to land (On Time) was 1524 Z, and the actual time it landed was 1521Z, arriving on the ground 3 minutes earlier than what was planned. The planned time of arrival at thé*gate (Eh Time) for this aircraft was 1528 Z, but it actually arrived at 1526 Z, arriving at the gate 2 minutes early. The map for this flight instance indicates that the route flown was as filed for the initial two-thirds of the flight with a dramatic western deviation as it entered the Minneapolis-St. Paul airspace.

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M i i É B l o i InslancctlQib/rJ/) DepdrtwcOi D«p*jML»A*PQit%DgvweMaS

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Figure 5.11. Slide 4 of Scenario 3: Dallas-Ebrt Worth to Minneapolis-St. Paul

103 5.2A Scenario 4. Chicago to Boston

Slide L (Figure 5.12):

During the month of May 1998 for all departures with the filed route ORD.ÆLX..CRL.J554JHW.J82.ALB..GDM.GDM2.BOS from Chicago to Boston, there were 25 total flight instances. Of these 25, eight encountered airborne holding (circular/elliptical patterns in the sky) and 17 did not. On average for the 25 flight instances, the actual Air Fuel Bum (15,496.3 pounds) was 12.8% higher than what was planned. For the eight flight instances that experienced airborne holding, the average actual Air Fuel Bum was 19% higher than the average planned Air Fuel Bum. On average for the 17 flight instances that did not incur airbome holding the actual Air Fuel Bum was 9.7% higher than the planned.

2J6&0 17 AmFweumUmcwzM 13l3U3 T4Æ4T iTXA.

Figure 5.12. Slide 1 of Scenario 4: Chicago to Boston

104 . - 1^-... c-i?' SlideJ (Figure 5.13):

This flight instance was a B757 aircraft departing Chicago on May 7,1998 eighteen minutes later than the filed departure time (OutTime) of 1930 Z. The planned Off Time was 1947 Z, and the actual was 2008 Z, 21 minutes later than planned. The planned Air Fuel Bum was 17,547 pounds, and the actual Air Fuel Bum was 20,293 pounds, an increase of 15.6%. AirTime was planned for 129 minutes but actually was 156 minutes, 27 minutes (20%) longer than planned. The actual Total Fuel Bum for this flight instance was 21,500 pounds, 7.5% higher than the planned 2 0 ,0 0 0 pounds. The time the aircraft was estimated to land (On Time) at Boston was 2159 Z, and the actual time it landed was 2244 Z, a difference of 45 minutes. The actual time of arrival at the gate (In Time) of 2251Z was 44 minutes later than planned. The map for this flight indicates that it was rerouted immediately out of Chicago and flew a route north of the filed route until around Albany where it rejoined its filed route. This map also suggests that this flight instance experienced airbome holding in two places before landing at Boston.

105 Fliqhl lnslcinci:(l 7flB433?)

A»FueBunUneoir.m»| 17347.0 20293.0 Z74&0 1S6X

rotetFueBumBal ZUmO a S lttO «nMUnoKW 27.Q z a s _ jMlrCœ«l____ w TadOutfiiwal 17.0 PutJniegL- ■,.. ISa O«riw0 1347 PirmegL InTineÉI

Figure 5.13. Slide 2 of Scenario 4: Chicago to Boston

Slide 3 (Figure 5.14):

This slide describes the flight of aB757 aircraft filed to depart Chicago on May 8 ^ 1998 at 1820 Z with an actual departure time (Out Time) of 1818 Z. The planned Off Time was 1838 Z and the actual Off Time was 1835 Z, three minutes earlier. The planned Air Fuel Bum was 15,263 pounds, and the actual was 18,480 pounds, a 21.1% increase over what was planned. AirTime was planned for 111 minutes, but was actually 140 minutes, o r 29 minutes longer. The actual Total Fuel Bum for this flight instance was 2,000 pounds higher than was planned, an 1U % increase.

A..

A: % 'A' ' The time the aircraft was planned to land (On Time) was 2032 Z, and the actual time it landed was 2055 Z. The aircraft arrived at the gate (In Time) at 2101Z, 2 2 minutes later than it was planned to arrive. The map for this flight instance indicates that it flew the route as filed until it around Ithaca, where it was vectored, and then encountered airbome holding as it neared Boston airspace.

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P w w lu i

A»FudBunUncortllb«| la jSaO 3L2170 21-1X

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Slide 5.14. Slide 3 of Scenario 4: Chicago to Boston

Slide 4 (Figure 5.15):

This slide provides information on a B757 aircraft departing Chicago on May II, 1998. It was scheduled to leave the gate (Out Time) at 1820 Z with, an actual Out Time of 1829 Z. This flight instance left the ground (Off Time) 37 minutes later than, was planned. The planned Air Fuel Bum was 15,181 pounds, and the actual was 19,720 pounds, or an increase of 29.9% fuel bum. AirTime was planned to be 114

.107 « r , . .

minutes, and the actual was 162 minutes, 48 minutes longer than planned. The actual Total Fuel Bum for this flight instance was 24.6% higher than the planned 17,500 pounds. The time the aircraft was planned to land (On Time) was 2035 Z, and the actual time it landed was 82 minutes later at 2157 Z. The planned time of arrival (Dr Time) at the gate in Boston was 2042 Z, but it actually arrived at 2203 Z, arriving at the gate 81 minutes later than was planned. The map for this flight instance indicates that it flew as filed until it entered the Boston airspace where it encountered airbome holding and vectoring.

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Air Fue6umUnccrt(bs __

Our meg: QftUMgl

Figure 5.15. Slide 4 of Scenario 4: Chicago to Boston

108 5.2.5 Scenario 5: Dallas-Ft. Worth, to Newark

This scenario consists of three slides. The first slide consists of all flight instances, and each of the next two slides consists of an individual flight instance.

Slide I (Figure 5.16):

During the month of May 1998 for all departures between I600Z and 2400Z with the filed route DFWX>ALDt.SQS JT2ATL..AHNJ208ÜPW.J19LPXT...EWR from Dallas-Fort Worth to Newark, there were 55 total flight instances. Of these 55, frve (9.1%) involved airbome holding (circular/elliptical patterns in the sky) and 50 did not. On average for the 55 flight instances, the planned Air Fuel Bum was 23,191.7 pounds, and the actual Air Fuel Bum was 25,207.9 pounds, or an 8.7% increase in Air Fuel Bum than was planned. The average actual AirTime for these flight instances was 7.7% longer than was planned. Of the five flight instances that experienced airbome holding, the average planned Air Fuel Bum was 23,869.8 pounds, and the average actual Air Fuel Bum was 28,808 pounds. This difference results in an average of 20.7% higher actual air fuel bumed than was planned. On average, the actual AirTime for these five flight instances was 28.3% higher than was planned. On average for the 50 flight instances that did not experience airbome holding, the planned Air Fuel Bum was 23,123.9 pounds, and the actual Air Fuel Bum was 24,847.9 pounds, a 75% increase in fuel bum than was plaimed. The average actual AirTime was 10 minutes over what was planned. The map for these flight mstances indicates that there was a great deal of unplanned vectoring and rerouting while en route to Newark (depicted by the black lines). The flown routes for some flight instances varied from the filed route (illustrated by the lighter gray line) immediately out of Dallas-Fort Worth, while others experienced variations later in the flight.

5a MFusBunUncoKllbtl 2iJU73 1.72«.0 7.5XA. AilineOncciKliiwiI 17SL0 igso WO__ 5 AirueBumUncoKllbit 23.8668 28.8060 *33tZ 2017% & A

Figure 5.16. Slide I of Scenario 5 -Dallas-Ft. Worth to Newark

Slide 2 (Figure S.LTI: ■

This flight instance was of Aircraft Type 727-B that departed Dallas-Ft. Worth on May 5,1998 with a scheduled Departure Timedf 2037 Zand an actual departure time o f2038 Z (Out Time). The planned Off Time was 2053 Z and the actual Off Time was 2054Z. The actual Air Fuel Bum was 20.5% higher than was planned. AirTime was planned for 172 minutes, but the actual AirTime was 212 minutes, 23.3% longer than was planned. The actual Total Fuel Bum for this flight instance was 12.6% more than the planned 32,600 pounds.

no The time the aircraft was estimated to land (On Time) was 2353 Z, and the actual time it landed at Newark was 0026 Z, a difference of 33 minutes. The actual time of arrival at the gate (In Time) for this aircraft was 36 minutes later than planned. The map for this flight instance indicates that it experienced airbome holding over the western part of Virginia in the Washington DC airspace. Once it was taken out of the holding pattern, it flew north of the filed route and then near Newark, it resumed filing the filed route.

C S L A N t

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Figure 5.17. Slide 2 of Scenario 5 -Dallas-Ft. Worth to Newark

Slide 3 (Figure 5.18):

This flight instance was an Aircraft Type SUPER80 that departed the gate (Out Time) at Dallas-Ft. Worth on May.9,1998*at^08 Z, one minute earlier than

i i r scheduled and left the ground (Off Time) at 2017,48 minutes later than planned. The actual Air Fuel Bum was 15.2% higher than was planned, and the actual AirTime was 54 minutes longer than planned. The actual Total Fuel Bum for this flight instance was 15.3% higher than, the planned 22,900 pounds. The time the aircraft was estimated to land (On Time) at Newark was 2227 Z, and the actual time it landed was 0000 Z, a difference of 93 minutes. The planned time of arrival at the gate Çn Time) for this aircraft was 2235 Z, but it actually arrived at 0007 Z, a difference of 92 minutes. The map for this flight instance indicates that it was vectored to the north shortly after departing Dallas-Ft. Worth but resumed flying as filed before arriving in the Atlanta Center airspace. This instance incurred airbome holding around Raleigh, NC before resuming the route as filed.

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Rgure 5.18. Slide 3 of Scenario 5 -Dallas-Ft. Worth to Newark

:• à} 5.3 Knowledge Sharing: Distributing the knowledge hase to match the locus o f control

5.3J Introduction

Because of the complex nature of the National Airspace System (NAS), there is only partial overlap of knowledge and data among decision makers. The decision making is distributed over many practitioners and teams of practitioners who must coordinate the sharing of uniquely held data and knowledge among members of the team in order to achieve both the individual and common goals of these practitioners. The sharing of uniquely held knowledge increases the ability for conversational partners to establish common ground and progressively build upon it (Clark, 1996). One way that common ground becomes possible is by creating schema similarity (Rentsch and Hall, 1994). The concept of schema similarity builds on the idea that individuals organize their understanding and knowledge of the world within a complex knowledge structure or schema. These schemata can be acquired not only through direct experience but also through conversational interaction with, others. Schemata are not fixed. Rather, they are continually evolving and changing as new situations and experiences arise, becoming increasingly more complex. As members of a team work together and share knowledge with one another, they are likely to achieve schema similarity, or commonality among the individual team member’s schemata. By supporting the members of each dyad with a shared cognitive artifact, their ability to reach a higher level of schema similarity is increased. They are able to view the same data and information to which they can add each individual’s knowledge as they go about making sense of what they see. This enables the partners to more quickly build a common understanding or common ground for the problem at hand. Poole and McPhee (1985) introduced the concept of co-orientation, which refers to the amount of perceptual agreement and accuracy that exist between individuals. They describe perceptual agreement as the degree to which agreement

113 exists between partners on what they are perceiving. Perceptual accuracy exists when the partners are able to describe the other’s perception accurately. Rentsch and Hall (1994) suggest that a high degree of perceptual agreement and accuracy, or co- orientation, is a form of schema similarity and is likely to be related to high levels of team effectiveness. Schema similarity is akin to other concepts introduced in organization literature, including schema consensus, (Walsh, Henderson & Deighton, 1988), shared internal frames of reference ^ tc h e ll, 1986), shared mental models (Cannon-Bowers & Salas, 1990), and teammind (Klein, 1991). These concepts all involve some degree of shared understanding among individuals. This research indicates that the greater the amount of data and knowledge shared among team members, the more effective the team will be. Other research, as described in the Review o f the Literature chapter of this paper, has consistently found that decision-making teams often fail to use their entire pool of information resources and that information unique to one team member has a much lower probability of being shared than information that is common to all members of the decision-making team (Grigone & Hastie; Stasser, Taylor, & Hanna, 1989; Wittenbaum & Stasser, 1996). Along with the existence of differing goals and constraints for each party, there may also be a mixed-motive aspect of the relationship between the members of each dyad in the present study, which could affect what is shared (Amason, 1996; Jehn, 1995). There are characteristics within the roles of the traffic manager and the airline dispatcher that appear to be mixed-motive in nature. Traditionally, the FAA had control of planning and managing traffic flow in the NAS and thus, made decisions based on what would be most beneficial to the involved FAA organizations in achieving their goals of efficiency and safety in the NAS. The air carriers cooperated with the FAA, which often resulted in significant costs in terms of increasedfuel consumption and airtime. This can be seen as the compete/cooperate paradigm within a mixed-motive task. This motèl of interaction did not require knowledge sharing as the necessary knowled^^resideff with the agent who had control of making the decision orsolvingthe problem." . ^ 114 Di recent years, the changing architecture of the Air Traffic Management (ATM) System has resulted in giving the air carriers greater flexibility in making alternative flight plans. If the organizations choose to compete, they disregard the choice of cooperation, and both may suffer losses. An example of this is when an dispatcher files a route, taking into consideration what will bring the greatest benefit to his airline without taking into account other conditions occurring in the airspace (e.g., congestion over certain arrival fixes and the impact on organizations managing that airspace), and at the same time the FAA traffic manager amends the route in order to maximize benefits to his organization without considering the impacts such a change will have on the bottom line of the affected air carrier (e.g., putting a flight in airbome holding rather than moving it to another less congested arrival fix). In this compete/compete paradigm, both organizations will suffer losses. Because these organizations have unique knowledge and different perspectives as well as different goals and constraints, it is understandable how they could make decisions that appear to be in competition with one another. Currently the organizations represented by the participants in the present study are engaging one another in collaborative efforts to manage the NAS. This cooperate/ cooperate paradigm of mixed-motive tas^s^based on the premise that both parties are able to realize benefits. However, forithese benefits to be realized, the organizations need to provide access to the requisite knowledge and processes to enable the sharing of that knowledge so that it is also located with the individuals who have control of decision making. It may be that because of this mixed-motive nature, cognitive conflict, or controversy due to differing perspectives over the best way to solve the problem identified in the scenario, is an inherent characteristic of these groups. Tjosvold (1985) suggests that this type of conflict increases the members’ desire to describe and justify their perspectives and strategies for achieving the task goal (Amason, 1996; Jehn, 1995). The cognitive conflict that occurs naturally in the dispatcher- traffic manager dyads can contribute to an increase in shared knowledge, and the possibility of the common knowledgeeffect occurring may be reduced. 115 Because most of the research on this common knowledge effect has been conducted in laboratory settings where the information needed to solve the task was controlled by the researcher, it is difficult to know how the findings adequately generalize to decision making situated in the domain of activity. It is also difficult to measure what knowledge each individual participant in the present study possesses, as well as the difference in level of knowledge that exists between the individual dispatchers and traffic managers (e.g., difference in levels of expertise). Therefore, an accurate assessment of what is shared and what remains unshared is difficult to bound, and is not pursued in this study. Another limiting factor of making generalizations from the laboratory research literature is that there were few studies reported for two-person groups. These research findings suggest that those in charge of managing the NAS need to be concerned about what data, information, and knowledge are consequential to ensuring safety and efficiency in the NAS and how that information is made accessible to all those who are in control of flights. As changes occur in traffic flow management that give the airlines greater flexibility in making decisions about what routes can be flown by their flights, resulting in changes to the locus of control, the sharing of that knowledge among traffic managers and airline AOCs becomes increasingly critical. In the present study, many types of domain knowledge need to be shared in order to do the experimental task. One type of knowledge is facts that are directly accessible from interactions with objects and data found within the slides (e.g., data found within the table and objects found in the map). A second type of domain knowledge is the inferences from the presented data drawn by the dyad parmers (e.g., the extra fuel bum in the flights that held must be due to airbome holding). Other types of domain knowledge that need to be shared are the different strategies and procedures in which the participants engage when they encounter situations similar to the events observed in the scenarios. Explaruiti^ and reasons why traffic management and dispatch engage in these strategies and procedures also need to be shared. This knowledge has to be grotmfed asTthfe, d^ d proceeds through their task ' ‘ LI6 . y goals of Identifying problems, generating and evaluating alternative solutions, and arriving at the best solution for the identified inefficiencies. This grounding process is accomplished by verbal and artifact-derived representations as the interaction unfolds. This section illustrates the knowledge sharing that occurred within different dyads as the members engaged each other in the problem-solving task. Some of the knowledge that was shared between the members of a dyad arose as they were proposing and evaluating alternative solutions to problems they identified in their particular scenario. Other knowledge that was shared and described in this section was not directly associated with a particular solution but contributed to the building of schema similarity or common ground. This analysis of the knowledge shared is organized into the following categories:

• Airline/Center Collaboration

• Arrival Flow Management strategies

• Arrival Flow Management constraints

• Airline Considerations

• Tools Used by Participants

5.5.2 Airline/Center Communication/Collaboration

Over the past several years the air carriers and various FAA organizations have begun to communicate about issues that are of concern to them and collaborate together on how to resolve those issues so that both the air carriers and the FAA can benefit as they work to maintain the goals and priorities of each, hi the present study, six of the eight dyads discussed the importance of communication and collaboration between the airlines and the En Route Centers (see Table 5.3). Five of these six offered improving communication and collaboration between their organizations as one of their proposed solutions to the problems they found in the scenario (see Table 117 5.2). Following is a representative sample of the discussions about improving communication that took place between dyad partners.

In the following exchange about the Chicago to Atlanta scenario (See Section 5.2 J for a description and illustrations of the scenario), the traffic manager (T,.,) of the first dyad encourages the dispatcher (D^,) to call the Center directly when he runs into problems with particular flights.

T n 6 8 : ....I get a lot of phone calls from dispatchers everyday where their pilots are saying that they’re low on fuel and they’re requesting the EEC [Expect Further ClearanceJ that they were given, you know, is that a realistic time? And I’ll look at it, and I can look at it from the meter scope and tell how many turns in the pattern they’re going to make, and do a more realistic time. Also, if I know they’re minimum fuel, a lot of times I’ll call up to the supervisor and say ‘Hey this guy doesn’t have a whole lot of fuel.’ You know, uh (pause} sometimes we can get them in there. Di.168 : ....we normally call [the Command Center] because they’ve asked us not to call individual centers. Would you rather have [during] your volume tight period— does that bother you if the call is to the Center directly?

[utterances omitted]

Tn70: I personally would be glad to work with you and help you as much as I can. Dt.t70: Okay. Thanks very much, [T].

The second dyad of the Dallas-Ft. Worth to Atlanta scenario (refer to Section 5.2.2 for a description and illustrations of this scenario) offered only one solution during their problem solving session: improved communication and collaboration between the airlines and the en route Center, as well as with the airline and the Command Center.

The dispatcher (D 1.2) attempts to view the situation from the Center’s perspective while also sharing with the traffic manager (Tz.j the perspective from which a dispatcher works. This allows the traffic manager the opportunity to share knowledge of how traffic management works with the air carriers and the Command Center when coordinating coded departure routes.

118 Di.224: Yeah. Well froiaa dispatcher's point of vfewr^and here’s the problem as I see it. that the Center works in real tune right now. r ve got an airplane on mjr scope and it’s going to occupy space with, someone else. I need to move them. Where, as dispatcher I’m looking 3 hours out, and I’m trying to guess what the Center’s going to do, and so in that respect we do need better conununication as far as {pause} uh {pause} if I knew ahead of time that something might be happening, I can plan accordingly and put the extra fuel on. so that these flights won’t have an actual fuel higher than my planned fuel. And that only happens when things happen that E didn’t plan for, otherwise, then what E have to be concerned about is will they have that extra fuel that it’s goingto take to go down to College Station and down, or get {pause} or E was (?) planned on a LaGrange arrival, but E’m coming in over Rome. Things like that. But E would think that’s real hard for the Center because you don’t know until{pause} unless you know ahead of time you’re losing a comerpost, or arrival route— Tm24: Right. And that, as far as traffic management, you were talking just a second ago about the coded departure routes, those...what we do with that here in the Center, we coordinate well ahead of time, not only with the Central Row {the Command Center}, but with the local carriers, like Delta and Air France, and whoever else on the line says we are getting ready to go to coded departure routes....and then you can plan on fuel and that...

The dispatcher (D 1.2) of the second dyad working the Chicago to Atlanta scenario (refer to Section 5.2.1) describes to the traffic manager (T 1.2) an example where better coordination between AOC dispatchers and FAA traffic managers could improve the dispatcher’s ability to better prepare the flight if it is going to be re­ routed.

Di.jl9: A lot of times here, and more often than not, when a flight has a re-route before he departs, the dispatcher doesn’t find out about it until the flight is called for its clearance and gets his re-route, and then he, the cockpit crew contacts the dispatcher and advises the dispatcher of the re-route. If there was a way perhaps that the dispatcher could be notified as soon as you make the decision at the TMU that the flight is going to get a re-route, there could perhaps be better coordination between Dispatch and you guys. T[.zl9: Yeah. That would be good. You need to know that Fm amending, because obviously....You gotta know what, where you’re going and dispatch it correctly. Dt.220: RighL You know sometimes if the dispatcher wasn’t expecting a long re-route, he may not have planned enough fuel totake re-routes. Other times there’s flights that already have full tanks of gas, cah(tput anymore in, and the only way to get it to fly long or farther would be to reduce payload. And if they need to do that, they need to know that as soouas pos^le. ' ". Tt.%20: Ri^L And that’s when, possibly, you say. Edon’thave that option.” You can’t put enough fuel on.^which we’ve run intb;. Then Fd say. “Okay, well then,

EE9 can you take a 20-minute ground delay?” And we’d work something else out. That would be good.

And later in their discussion, the traffic manager summarizes his thoughts in the following utterance,

T1.235b: There again, you communicating with me, you know, ‘This flight historically gets delayed.” We know which one’s always running the same delay, ‘cause it happens probably six to eight [times a] week.

When discussing the issue of re-routing aircraft, the traffic manager (T 3.1) in the first dyad working the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3) suggests to the dispatcher (D 3.1) a way that the dispatcher could help traffic management, and the dispatcher agrees that it could help.

Tj.116: And this might just be a side benefit that, as a controller who’s assigned to tell the pilot he’s going the long way, it’s kind of nice if he’s already heard it from his company. Something that they’re onboard and agree that it’s a good idea, and so if we call Northwest and tell them what the problem is over Eau Claire, that there are too many aircraft coming in, we need ta move a couple of them, do you have a preference who it is? And they have some input,.thea they usually send an AGARS message to the airplane and the pilots knows and is expecting a reroute, doesn’t bawl out the controller when he gets It_ Just, it’s an added benefit. That he hears it from the other side. Dj.tl7: Yeah. That sounds like a good plan.

The traffic manager (T 4.1) working the Chicago to Boston scenario (refer to Section 5.2.4) suggested that there does not appear to be any good solution for eliminating or alleviating the holding and extra fuel bum. He proposes that improved and more frequent communication between the Center and the airline may be the key to coping and making the best of the situation.

Tj-tSSa: I guess the other thing is just getting all the holdings, extra fuel, there’s nothing much we can do about that except more Just better communication as to a— T4.157: ....like I said, you can call us directly. I don’t know if you have our number here. Dj_[57: fri Traffic Management? T^_t58a: Yeah. D4.i58: Yeah, we have it. In fact...your button is one of the auto-dial buttons. 120 T4.t58b: Good, good. T4.i59 a: ....I know most things are supposed to go through the Command Center, but if there’s Just an individual quick thing we can handle, and believe me we can deal with things right away, you can just give us a call anytime.

Later in the conversation the traffic manager again encourages the dispatcher to call Boston Center whenever he has a flight in the Boston airspace with which he needs some coordination from the Center.

T4,|83ar ....like I said, in the future, I mean any dynamic situation, any individual thing you need help with. D4.i83b: Okay. T4,i83b: We’ll be glad to do anything. Everyone here, like I said, we are on your side.

Thus, this dyad talked about situations in which a dispatcher working with a traffic manager at the involved En Route Center may provide benefits to both parties. One such situation is when an airplane is holding but does not have as much fuel as another of the carrier’s airplanes that is closer to the arrival queue. The airline can request that the fuel-constrained airplane be traded with the more adequately fueled airplane. This not only benefits the airline by reducing the chance of the pilot diverting to an alternate, but also benefits the traffic manager who will not later have to make room for a priority landing due to low fuel.

5.5.5 Air Traffic Management and Airline Considerations

In pre-flight planning, how to utilize restricted area airspace must be given consideration. What prompted the following exchange was a call into the Traffic \Tanagement Unit (TMU) on the military phone. This was a serendipitous event that allowed the partners to discuss the difficiildes.thejr Bave both encountered when dealing with restricted airspace, enablingperspective and knowledge sharing that might not have occurred in the course of .wdfKngoin* the task problem.

121 b^i48a: Now there are some fellas [the milltaryL if they were to release airspace, sometimes would help a lot. Not so much by you, but the Washmgtou Center, and offthe coast there. T^i48: Oh that*^s a giant killer down there. They always have the warning areas active. Dj.i48b: And there’s nobody there a lot of times. T4_i49 ar You know we have really been workmg on doing a real time basis, and in fact in warning area 105, although we do do that now. We’ve worked it out over the last two years, because right it sat idle and no one was there, and it would have been moving aircraft all the way around it. But we are doing it. D4.[49: Is 107 Just east of it? Right? T4.i4 9 b: 107 is just southwest of that. And that^s a big factor, but see Washington is in charge of that. And I’m not sure how they are doing the coordinating of that. But you can give them a call and find out if it’s going on more of a real time basis now. And I know they are moving towards that. And we still do have a lot of military agencies who are requesting things. They block a 7-hour period and they are out there for an hour or two. And it’sjustnotfahrto anyone. D4.15O: Well, we work very closely with the people at Edwards and White Sands. Which are big military flying and restricted areas in New Mexico, out in the southwestern part of Nevada, and there’s a lot of routes that go through there, that if we can use them we’ll save hundreds and hundreds of pounds of fuel and time, although sometimes they put restrictions on us that we have to be 31 and below or 31 and above, and if we can comply with that, they say “Come on through.”

The dispatcher relates how his airline has dealt with the airspace over White Sands and Edwards Air Force Base, and how successfully working with the military has allowed more access to this airspace.

This knowledge may allow the traffic manager a different perspective on how to approach the difRculties with restricted airspace faced by Boston Center.

5.3A Arrival Flow Management Strategies

There are several strategies that are used in Arrival Flow Management to achieve optimum use of the National Airspace System (NAS) and to minimize the effect of air traffic delays on the user without an. appreciable increase in controller workload. As the problem-solving pairs in this study progressed through their assigned task, they proposed a number of such strategies as solutions to the identified problems and shared knowledge about those and other strategies used to eliminate or

122 minimize such problems. Among the strategies they discussed are arrival fix balancing, ground delays, time-based metering, alternate routing, delay vectoring, and altitude separation.

5.3.4.1 Arrival fix balancing

One of the factors that can contribute to air traffic congestion is the volume of traffic over a certain arrival fix in any given time fiame. A strategy used to reduce that congestion is arrival fix balancing, which is a process whereby aircraft are evenly distributed over several available arrival fixes, reducing delays and controller workload. In the following discussion the traffic manager (Tm) in the dyad states that if volume over a certain fix is overloaded, a fix balancing strategy might be used. Figure 5.19 is a picture of the slide that this dyad had available to them for reference during the conversation that follows. Figure 5.20 is an illustration of the same slide labeled with the geographic locations discussed by the dyad parmers.

Figure 5.19. An illustration^ of the map portion, of slide I of Scenario I - Chicago to Atlanta

123 . ' Ç:r^j#lb.W

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Figure 5.20. Slide 1 of the Chicago to Atlanta scenario with of geographical locations labeled.

Ti.iS: ....What we do is, uh, we would pull off maybe somebody for fix balancing. But 27 with a 90 to 98 arrival rate, we should be able to handle that, no problem. Well, we’ve got 27 over Rome and they have 40-42 over on the northeast corner, and possibly 27 to 30 on the two south fixes. Di.iS: What effect does traffic coming in from other places like DFW have on Chicago traffic, when you have volume problem ia Chicago? T n6 t There’s one push every afternoon. Eastern Time it’s 3 p.m. to 4 p.m. All West Coast traffic comes in and we also get a lot of traffic coming down from Chicago, and there’s like 42 arrivals over Rome durmg that hour. TrafKc is coming from Dallas, a lot of times we will reach, out here, say around even west of Dallas and maybe pull 4 to 6 aircraft south to Meridian La Grange. What we’re doing is not that they can’t handle them over Rome, but there’s such a volume issue in this one sector; it's called Rocket Sector, which is 24 to 43. It’s just more volume that they can evidently blend to get in trail to go to Atlanta terminal areas. Dn6 : What if, say, what’s the fîx that comes in over northeast? T[.[7: Northeast. That’s Macey, Macey arrival. Dn7: Is there anyway they could route some oftRattrafric from Chicago in over that fix, or do you have too much, coming itf over the northeast? Tt-tS: There’s about 41-42 that comes in ovet;MaœÿZ If they come in in front of this bunch that comes in over Rome. So - Di.i8 : So would it be possible to route sorhe of thattraffic over Rome, to re-route it over Macey? . . -

[utterance omitted}

124 Dt-i9: What if you took, lik& 3 aircraft and run all those over Macey, rerouted thetn over Macey rather than give them those vectoring delays. The vector’s up there in Lady Center. Just reroute them - let them fly the planned route ‘til they get down in the Memphis air space, and then have Memphis route them over to Macey. T n 10: The problem is that the air space that they’re cutting across here is real busy that time of day. Departures going northbound and Cincinnati is becoming such a hub, they’ie departing south off Cincinnati going to Florida, and traffic coming northbound to Chicago {pause} there’s a lot of traffic going this way but they have to cut across,{pause} uh, that’s what we were talking about just before I came in here. The sector right around Volunteer Fix, Victor, Xrray Victor. There’s so much crossing traffic right in that area that we’re trying to avoid that area as much as possible. Traffic comes into Charlotte, comes into the west, northwest, comes in over Volunteer. We’ve got traffic climbing off Cincinnati southbound over Volunteer. You’ve got traffic climbing off northbound off of Atlanta, over Volunteer, plus all your traffic out of Rorida going to Detroit.

The traffic manager (Ti.t) has explained that re-routing aircraft over Macey would impact the Atlanta departures that are northbound, overhead traffic from Cincinnati to Florida, overhead northbound traffic going to Chicago, and traffic from Rorida to Detroit. The knowledge shared by the traffic manager (Ti.i) with the dispatcher (Dt.t) allows Dt-i to better understand ho W traffic flows interact in the Atlanta Center airspace and how those flows place’Constraints on flights between Chicago and Atlanta. This provides the dispatcher with a bigger-picture view of what needs to be considered when planning flights between city-pairs. The conversation continues as the dispatcher asks for more knowledge about the traffic flows as he continues to pursue his proposed solution of changing arrival fixes.

Di.i 10; Okay, so the traffic that’s inbound to Atlanta would have to cross a departure route, from Atlanta northbound? T nII: Right. Transition areas {pause} they come up basically to the Volunteer and then they turn either north or go to the northeast, and also they come up to Chattanooga Choo-Choo, and then Nashville they turn west. D u ll: Well, if there were only three aircraft doing that, would that then be something that might be manageable? Tt-i 12: There’s like a Volunteer transition for the Macey arrival right now. We’re in the process of trying to get that taken out of the STAR. Dm 12: Well, where exactly is Volunteer? Can you point to that? T(.[13: It’s right here. Volunteer is right here.

125 DnI3: Okay. So that really wouldn’t be that much.. J mean if they could find a way yon could do that with, like three airplanes. T n 14: Theproblem is they’re going to do away with that transition and you’d have to come all the way over here to probably-uh, probably going to have to come more like into this area. Di.i 14: Oh, that would be way out of the way.

Based oa the previous mteraction, the knowledge shared by the traffic manager makes it clear to the dispatcher that re-routing to the northeast arrival fix, Macey, is not economically feasible. The dispatcher (Di.t) continues in the next exchange with the proposal of changing the arrival fix but this time suggests using a fix other than Macey.

Di.i 15: What about going over the top of Atlanta and coming in from the southeast? Stay at altitude as long as possible and then coming in from the southeast. T[.i 16: We had done that in some severe weather type scenarios where a fix may be blocked off. We’ve taken them across the top and then a 1” tier drop and brought ’em in. A couple of years ago, I used to see it a lot more common than now. -« There’s Just so much volume. It used to be we’d have on a push, you’d be heavy on maybe a couple of fixes and light on a couple of others, and we could do stuff like that. B ut this particular push in the afternoon, it’s heavy from all four comers, and like I said we would take 4 to6 aircraft off of Rome and bring it to the south of LaGrange and bring ’em in, but we had to be real careful which ones we picked because they had to (?) in front. LaGrange is pushing, let’s see Macey’s push hits first, and this one comes in right behind it, and then LaGrange and Seneca, two south fixes bring up the rear of a push and they usually get a trail called out a lot greater than what they have on the north side. So we have to be careful what kind of volume we put down there, because they’re going to go with a holding situation pretty quick.

When ± e dispatcher suggested re-routing over the top of Atlanta, to come in from the Southeast, the traffic managerexplai^d that the two south fixes bring up the rear of a push, and they usually get mileS-in-trail called out that is greater than the restrictions put on the north fixes. He thenTfiormed the dispatcher that the amount of volume put on the south arrival fixes mdstbê carefufi^ managed because they can get into a holding situation fairly quickly. So, irt'tbis exchah%^the traffic manager shared his knowledge about traffic flows iahd constraints that occur in the Atlanta Center

126 airspace, which allowed the dispatcher to share the traffic manager’s perspective that going over the top of Atlanta is not a viable alternative. This conversation points out the importance of sharing with the dispatcher knowledge that the traffic manager has regarding the multiple constraints and uncertainties that are involved in managing the traffic at the arrival fixes and about the interrelationships among the fixes. Without awareness of what constraints exist with respect to the volume of traffic in the sectors surrounding Atlanta for particular times of the day, the dispatcher could easily, with the flexibility given the airlines under the National Route Program (NRP), file a route that would allow his aircraft to arrive at one of the other arrival fixes, resulting in possibly greater negative impact not only for the rerouted aircraft, but also for the overhead and departure traffic routinely scheduled into that airspace. This issue is of particular importance when determining what data and knowledge is necessary for those who have control of planning the routes of aircraft between city pairs.

In the following exchange the traffic manager (Tt-i) indicates that some fix balancing is done at certain times of day, sharing with the dispatcher ^ n ) why it is done and what constraints need to be considered.

T n I9a: See, that’s pretty much what we’re doing now. We are looking at a certain period and notice there’s an overage, and instead of calling the airlines, basically we’re taking it upon ourselves Just to reach out and move a couple of aircraft to a different fix that’s not quite so heavy. DulSbr You mean a different arrival fix? T n 19b: A different arrival fix,yes sir. D(.[19: Okay. Well, that works too, ifyou cando.it. That’s what I’m talking about. Maybe moving some of them to Macey and that, but maybe that’s not possible {pause}

[utterances omitted]

Tn25: To tell you the truth, to really understandthe Chicago to Atlanta flight, you Just probably have to look at the whole push; and you can watch how [pause} You’re talking about 40 to 42 airplanes coming in from the northeast, anywhere fiom Cleveland all the way across,and there’s also some international flights we have to take into account. And you kind of got to favor this northeast fix. You know, once

127 you start talking about the international, then your talking about fiiel, what they’ve got on board as far as fuel. Dn25a: Yeah. Well, that’s why I was trying to, \ih:[^usef at first they’re going to go around fpause} you have 4 arrival fixés, is-that nght? Tu: Right. Du25b: Yeah, that’s what I’tn. trying to [do]; kind of go around to see if there’s anyway that we could get some of the traffic that was coming in over Rome, to come in over another fix that wasn’t as full of traffic coming from DFW into the different complex, then maybe the arrivals that come in over the southwest fix that would be not be being used quite as much, unless you have a departure push that’s going west at the time these arrivals are coming in. Ti.i26: If we are going to do fix balancing, we have to do them a good ways out, like if we’re going to fix balance Chicago, we’d have to drag him up here and he would have to come across probably over here to come down. Du26: But what about the southwest fix? Where do you have to send them in order to get them down to the southwest fix? Tu27a: Coming out of Dallas? Probably somewhere around the Mississippi River or somewhere right in here. Sometimes Memphis Center, I think that boundary’s right in here. Sometimes they’ll grab them right in here and bring south to Meridian. They’d come all the way to Meridian. They can’t come any farther north than Meridian to be on the LaGrange arrival, because all the west departures from there. Dn27a: Yeah, that’s what I was wondering. So, at the time when you get this bottleneck that we’re talking about right here...you still have the west arrival, or the west departure? Tt.t27b: Yes. Dn27b: (?) also? Tn27c: Right. Tui28: Well, this particular push that Fm talking about in the afternoon is what I call a four-comer push. AH four arrival fixes are impacted by volume and if you can see this Rocket sector is basically—we’re getting a red alert on it, and also to LaGrange high sector, which means the LaGrange arrivals. I’m getting a red alert on it also. Dt.t28: Okay. So then they’re all heavy. Tn29: Yeah. And there’s en route traffic in there with it. Traffic coming out of Florida, going up to St. Louis. And traffic coming out of northeast going to Houston and Dallas.

In this interaction the traffic manager has painted a more complete picture of the Atlanta airspace during the particular timeframe they are discussing. The constraints that are presented include traffic that is crossing over the Atlanta airspace, traffic that is arriving from the northeast, and arriving international traffic. As a way of helping the dispatcher understand that it is not in his airline’s best interest to file over another arrival fix, he uses the shared display to hidicate where the flight in

128 question would have to be re-routed in order to change arrival fixes. As a result of this knowledge exchange, the dispatcher is able to understand what the impacts would be if he filed over another arrival fix. At this point the dispatcher ÇD w) abandons the possible solution of fix balancing. The traffic manager (Ti.i) has been successful in sharing enough knowledge with the dispatcher about the constraints that exist at Atlanta to indicate that he does not consider this to be a viable solution.

The Dallas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3 for a description) indicates that several flights were re-routed to another arrival fix. In the following conversation, the traffic manager (Tj.t) shares his knowledge of reasons for fix balancing.

T3.i3 a: ....going in from the southwest, I can see a couple of reasons for fix balancing, and basically what that is is that there’s just too many aircraft scheduled to come in on one fix. Both for safety control and workload. So if it’s more than they can handle, you gotta [move] some of them out. But also if it looks like a stream coming in on a particular fix {pause}. Well, if you can imagine several of them spaced out evenly, and it looks like they’re going like clockwork, and to throw one wrench into the beginning of the stream, and you know how this works— Dj.t3b: Right. TuSb: —then everybody else behind them gets backed up, and they might work to Just take the wrench out and let the rest of the stream run like clockwork, and put the wrench in on another side of the airport.

[utterances omitted]

T].|4d: Whether sequencing for the O’Hare arrivals into Minneapolis (?) and sometimes that sector gets a little too bit busy, which might be the reason why some of the stuff moves out to the west— % ' ^ Dw4e: Okay. v ' T3.i4e: —and it’s Just, uh, it’s two pushes. It’s an O’Hiue push and a Minneapolis push that are overlapping. Some of those sectofs'aie j^ing td%et buried, and I’ll have to ofier a little relief and have to move some aîrplânês'fôfthat reason. -j| » ■ - ■ . - - - i . V -.' • -■••i f ’ -..i [utterances omitted] ’ :

Dj.1,8 : Do yon file them that way or do you guys. Just as they bunch up. Just take a couple of them out on your own? T3.18 : We take a couple of them out, but we generally if you could see a big cluster of them coming, and you can see that either it’s gomg to be too much work for the sequencingcontroUer, that he’s going to be buried with (?). Or if it’s going to be 129 the situation where there’s a wrench in the system at the beginning, and the rest of the stream is going to have to get delayed, it would make sense to pull somebody out. And for those two reasons.

The traffic manager (T 3.1) shared two reasons why a flight might be re-routed to a different arrival fix: ( 1) traffic congestion at a particular fix, which if not corrected could result in safety and workload issues, and (2 ) one or two flights that have the potential to interfere with a smooth flow of traffic are taken out of the stream and moved. The traffic manager indicates that arrivals at certain times of day from other airports other than Dallas-Ft Worth (e.g., from Chicago) may add to the congestion at a particular fix, which then leads to other aircraft being rerouted. The dispatcher (D 3.1) also learned about the strategy that this Minneapolis-St. Paul Center traffic manager uses when congestion occurs in the airspace, i.e., taking one or two aircraft out of the stream and moving them to another’arriyal fix. ■■ ' V >

Dyad 2 of the Dallas-Ft. Worth to Minneapolis-St. Paul scenario also discussed fix balancing in order to explore how using this strategy might help to avoid the lengthy airborne holding they found in this scenario. It appears that the dispatcher who was in charge of this particular flight instance (pictured in slide 2 of the scenario; see Section 5.2.3 for a description) was aware that the delay was going to occur (by the amount of fuel that was planned), so the dispatcher suggested to the traffic manager that one solution would be to re-route the flight to another fix earlier than appeared to be done in this instance, and thus avoid the holding. Although this might be a viable solution, the pair did not explore it further.

The conversations between the dyad parmers described in this section are rich examples of how the knowledge of traffic flows is critical m making decisions, fii the current architecture of the NAS, it is the traffic manager who has the knowledge to needed to make efficient decisions on whether to re-route a flight to another arrival fix if the filed fix is congested with traffic. However, it is the dispatcher who has initial

130 control of filing the flight plan that, when intending to file a route to avoid congestion might instead make a decision that has wide and perhaps cascading negative effects on other areas of the airspace. By sharing his unique knowledge, the traffic manager in Dyadu is able to create an environment where a mutual understanding and common perspective between the dyad pair is established. What is accomplished between the partners in Dyad;.! is a common understanding of the factors that must be considered when a decision is made to re-route an airplane to another arrival fix. Distributed work brings with it the possibility that those who have a decision- making role may not have sufficient knowledge to support his or her decisions. Through collaboration and knowledge sharing with those who have that requisite knowledge, the probability increases that more well-grounded solutions can be realized.

5.3.4.2 Ground delays and ground stops

Another strategy that the airlines and FAA have available to them when the volume of traffic is, or will be, exceeding capacity at any point in the national airspace is the ground delay. This is accomplished by delaying certain aircraft on the ground at the originating airport in order to allow for adequate spacing of airplanes in the airspace, and thus, controlling the number of aircraft in any one sector at a given time. Limiting the number of aircraft in anyone?sector of the airspace may minimize the amount of vectoring an aircraft will need ÙLO^érto position it for miles-in-trail spacing, and airborne holding at the destinafion may be reduced or eliminated. This solution of "mini grounddelays” or,“intemal groundstop^’ or other ways labeled by participants in the study is one that arose as a possible solution by both dyads working the Chicago to Atlanta scenario and by one dyad working the Dallas-FL Worth to Minneapolis-St. Paul scenario.

131 la the followiag exchange about the Chicago to Atlanta scenario (refer to Section 5.2.1 fora description), the dispatcher (D u) suggests the solution of delaying aircraft on the ground at the originating airport as a way of alleviating the volume of traffic occurring at the destination. The dispatcher and traffic manager (T|.[) share knowledge, previously unknown to the other, that results in a shared understanding of how this ground delay solution would benefit both parties. The transcript below begins with the dispatcher introducing the possible solution of having all of the airlines flying from Chicago to Atlanta during the time in question keep a certain number of aircraft on the ground in Chicago for a specified period of time in order to alleviate the excess volume in the airspace.

D n l6a: ...ask the airlines to....take it to Delta, American and whoever flies—United— whoever else flies from Chicago to Atlanta, just coordinate with ourATC coordinators of which Tm one, as far as keeping one of our aircraft on the ground, almost like a mini ground stop, or you wouldn't stop everybody, but if you take one airplane for each carrier and delay that,, and call and ask me which one I want to delay, I might have an aircraft that goes down there and Just sits on the ground for two hours before we need it again. Tt.|: It's a volume issue. Du 16b: Yeah, I know. So if we delay it in Chicago, hold it on the ground in Chicago— one airplane for American, one for Delta, and one for United—there’s your 3 airplanes there. And then maybe you need more. If you need six, then you need two per carrier, or maybe two successive flights. Ti.i 17: So what you’re telling me, you’d rather do that rather than do a fix balance? Du 17: Well, ifthe fix balancing means that they are going to give a lot of vectoring delays, for instance on this one showing the actual flight plan, was uh, airtime was 18.6 minutes over planned, well that’s percent over planned, and 14.4 over on the fuel bum, and the ones that held wece^fi^ minutes, that’s a little more than a quarter of the total fuel bum, more than should have [pause/ more than platmed. If that’s going to be the case, and ifypuknow it far enough ahead of time that you’re going to have that many [pause/. Do you all use FSM [Flight Status Monitorl? , : T n 18: We just got that in jhefacOity a couple of months ago, and yes, we are using that now. Di.i 18: Okay. Well, we think that’s a real valuable tool, because[pause/ on a planned basis, and you can pretty much, see what you’re going to have at any given hour during the day. But you can look at it and see it’s (?) and you can do it by fix, look at it and say, “Well, I’ve got more than lean handle in this particular 15- minute period, r m. going to call the airlines and see if they can delay some of their flights into the next 15 minute period, where I’ve got a lot more capacity available.

132 Tnl9a: See, that’s pretty much, what we’re domginowu We are lookiag at a certam period and notice there’s an overage, and nistead of calling the airlines, basically we’re taking it upon ourselves just to reach out and move a couple of aircraft to a different fix that’s not quite so heavy. Dj.il9a: You mean a different arrival fix? T[.[ 19b: A different arrival fix, yes sir. D n 19b: Okay. Well, that works too, if you can do it. That’s what I’m talking about. Maybe moving some of them to Macey and that, but maybe that’s not possible [pause}

At this point the traffic manager (Tt.i) has indicated that the way he currently deals with an overload of traffic during a certain period is not to call the airlines, but to move a couple of aircraft to an arrival fix that has less traffic. This piques the dispatcher’s interest, since it is what he had been trying to propose at an earlier time in their conversation (see Section 5.3AJ for their arrival 5x discussion). However, rather than try to resurrect changing arrival fixes as a potential solution, he continues exploring the ground delay alternative.

Dt.i I9c: ....[pause} but if you can’t do that kind of thing [i.e., moving aircraft to another arrival fix], and you know far enough ahead of time and...then you can coordinate with us, or I’m sure [the Command Center] with us, and just keep on the ground for 10 additional minutes, rather than have them vectoring all over the place, then take a chance of, you know, if they have to hold, taking a chance that somebody may have to divert because they don’t always plan on a good weather day to have enough fiiel to hold that long. Ti.t20: Yeah. The problem with putting like 15 to 20 miles-in-trail on the arrivals coming from our first two facilities, a lot of times you may delay somebody with a vector, that you really didn’t need to delay. On the front end of a push they would have been able to take ’em in there at minimum in-trail, and if you didn’t see things in the first tier, you can’t get’em in-trail and you’ve delayed them unnecessarily. Dt.[20: But we’re just talking about from Chicago to Atlanta now, aren’t we? Ti.[2Ir Right. Di.t21: Okay. And let’s (?) say you have other traffic coming in over that fix, for instance maybe something like — If you saw that you’re getting all that much traffic over that sector that you’re pomtmg at there, you cart do like maybe internal first tier ground stop to keep some of that trafffc on the grotmd for say 15 minutes. T[.[22: We do that, but you know if it warrants a ground stop, I mean, we’ll do it for 30 minutes and a lot of times ittakes45 maybe even 60 minutes. It’s just because of the volume. On a VFRday, we won’t have to do aground stop and you’ll get holding right there still. You’re talking about 124 arrivals trying to get in here within a 60 minute period, and most of them are trying to get in there within a 30 minute period, and you’ve got to spread them out. 133 Dm22: Yeah. Well it sounds like the best way of domg that ia that situation is if the major bottleneck is that one sector there, and neither sector balancing or internai ground stop [will help}., .or coordinating [pause} things through [the Command Center] is to have the airlines delay a flight for like 10 minutes, at one per airline or two per airline. Tn23: It helps on the fuel bum. Dn23: Right Like I said, the situations that we don’t want to get into is where we’re coming down there oa a good weather day with, minimum fuel, and then get into a bottleneck in that sector, and have somebody divert because they didn’t have enough to hold for whatever time was necessary.

The traffic manager (Tm ) explains why he thinks that delaying aircraft at their origin is not a good, solution, hi the next exchange the dispatcher G^ut) expands the number of aircraft involved in the mini-ground stop from those flights departing Chicago to those departing airports closer to Atlanta. He suggests this as a possibility if too many airplanes have already left the ground in Chicago before the traffic volume situation is realized. The traffic manager responds to this suggestion by sharing knowledge about how the “internals,” or those airports closer to Atlanta are handled when volume is high. He does not, however, address the dispatcher’s suggestion to involve those airports in a mini-ground stop.

D,.[23: Especially when you could have had, uh, when you saw that problem, then you could have put out an internal ground stop and maybe held some of those airplanes that are close in, on the ground, if the problem develops later on, after the flights in Chicago had. taken off. They’re already in the air but you can still stop some of the closer in, say commutersor traffic coming from Memphis, or something like that . . ^ Tm24: We have all our internals on a high (?) Basis, and when I say internal what Tm talking about is as far out as Roanoke to the^northeast Lexington, Cinciimati, Stamford would come out of Indy Centerand once they get off, they’re kind of in a no-man’s land right here, in which way would they go either over to Macey or over to Rome. They coordinate with Indy Center as to which way we want them to come. They may have to detour. Sometimes we detour them over Volunteer, Macey. Sometimes we (?) down (?). Chicago very seldom gets moved, unless there’s some weather out there. Normally Chicago’s going to come in over Nashville, to come in. Basically because they are straight down the arrival.

The evaluation of the ground delay solution is abandoned by this dyad while other potential solutions are explored and then re-surfaces when the dispatcher asks

134 the traffic manager for his suggestion on how they cm help alleviate the volume issue. Even though, in a previous part of the discussion the dispatcher (Dm) explained that holding oa the ground was preferable to holding in the air, the traffic mmagerClM) has a difficult time chmging Ms mental model of what the airlines would prefer. He suggests to the dispatcher that Ms understmding is that the air carrier prefers getting off the ground on time rather than reducing airborne holding. The dispatcher again corrects the traffic mmager^s understanding, stating that it is getting out o f the gate on time that is important not getting o ff the ground on time. For the airlines, what is m important consideration is arriving at the destination airport’s gate at the scheduled time (In Time). The reasons for backing out of the gate on time at the originating airport cm be two-foÙ: ifirsf, there may be a penalty imposed on the airline for not leaving the gate on time (a*Fate Out Time), and second, the gate may be needed for m arriving flight. So, the dispatcher md traffic manager engage in a discussion that allows furtherexploration mdevaluation of ground delays as a possible solution.

Di.i29: Okay. So what are the different options that we have, as far as smootMng this traffic flow? T[.|30: The mentality that we have right now is, — and correct me if Fm wrong, but the airlines tell us that all they want to do is get off on time. They don’t mind holding as long as they can get off on time. They’d rather get off when they want to— Dn30: Well that’s not exactly true. We want to get off the gate on time. Tn31: Okay. So, if I had called you and asked you to hold somebody off Chicago, you would get off the gate on time but you may— Dn31: We may wait ten minutes for departure. Tm32: ....Okay. Fve been in tMs business for 17 years, and in fact I’ve spent 10 years working this particular arrival coming in from the northwest, and if s just die mentality of Me controller. Nine times out of ten they’re going to vector you for their space and use speed control versus going into the holding pattern. Up to a certain point. Once they get to a certain point of volume, then they have to go to holding. Di.i32: Yeah. Well, that’s what Fm trying to getaway ffom, md I think with FSM [Flight Status Monitor!, k would be a lot easier to acMeve because you cm see, based on the latest informatioaffom the airlines, you cm see how many arrivals you’re going to have for my 5 minute period, or 10 minute period, or 15 minute period. And it seems like we ought to be able to space them out, as you’ve got more volume thm you cm hmdle, we ought to be able to space them out, md this is...we’re talking about all fixes. Or you cm do it by individual fix. So if you j'ust

135 want to look, at this Rome fix. and see how many arrivals you have over Rome. You can do that, and if you have more than you can handle, then we need to do something to spread them around a little bit more, and the way to do that, and Tve done this before with [the Command Center] where they\e {pause} here at DFW where they said we’ve got, uh, the arrival rate is 90, saying we’ve got 105 arrivals. So if you pick out four flights and delay them into the next 15-minute period, then we can do that. T[.[33: Okay. I have never done that. We have talked about it and from my end it’s harder to determine which 5 planes I delay. So like I said, if 1 delay 5 flints early in the push. It’s very tricky to decide which 5 delay; if you delay the wrong 5 you’ve just made the situation worse. Because you don’t want to delay anybody in the front part of the push because you’re going to be running minimum in-trail at all four fixes. What I call front-loading the airport. Getting them in there and get the final pushed out, and getting maximization out of the airport. D[.[33: Well that’s what I’m saying. If you use FSM and look at our arrival fixes. You can look at the flights that are getting in at the front end; so you overload the airport at the front end, and you won’t ever need it at the back end. So if you have any delay where you have to do some spacing vectors or something like that, you want to unload the back end of the push, so those are backed up into the next hour. T[.[34: 1 see what you’re saying, I just uh— D[.[34: And we have the capability of looking at the same thing that you’re looking at. So if you called us, or if [the Command Center] called us. We have the capabilities to look, you know just like you and I are looking at the same thing here, we can look at the same thing that you are looking at on FSM [ETight Status Monitor], and if you say, “Well, in this 15 minute period, we need to move some of these flights back into the next 15 minute period.’’ We could look at that and we could tell you which ones we want to delay.

The traffic manager expressed concern about his uncertainty concerning which aircraft to delay on the ground because oPthe dynamic and unpredictable nature of the airspace near the destination airport and explained what difficulties can arise if the wrong airplanes are delayed.'Di response to this concern, the dispatcher proposed that using the Flight Status Monitor ^SM ) (refer to Section 5.i.5. J for a description of this tool) will help overcome that uncertainty and offered that the AOCs organization can aid FAA Traffic Management in the decision of which aircraft to delay.

fit the following interaction, a second dyad working the Chicago to Atlanta scenario (refer to Section 52 d for a description) discusses ground delays as away to reduce airborne holding. 135 Ti.25: Well, we’ve got a couple of ways we can reduce the holding and here’s what steps out. You’ve got 22 instances of no holdmg, which that’s (?) and demand at the airport. Not knowing exactly whatthe weather’s doing,....Ground delays. How do you feel about backing o^ the gate in 15-20 minute ground delays? Dn6 : Well, going out of Chicago like any of our big hubs, we are restricted on the number of gates we have. We need the gates to bring the inbound flights into, so we typically will push them off the gate pattern near departure time, and take the ground delay hold on the ground, so if there was any kind of ground delay program, they would take it on the ground. T 1.26: Good. In our thinking, ground delays, you know, it’s strictly volume, depending on your ETA [estimated time of arrival] into Atlanta. To us a 20-minute ground delay does better than 20 minutes of pattern. Because once we start holding, it’s going to take us probably 20 or 30 minutes of volume holding to clear that (?) demand out.

{utterances omitted}

T1.28 ; ....about the only thing I can do to cut down on holding time is having you take a 15-minute ground delay, actually spacing you coming into Hartsfield in a different rime span. Most of our arrivals, we look at 15-minute increments, and that’s where the miles-in-trail restrictions, and everything, comes from. And what we have seen in the past, even that 15-minute rime frame. So, that’s why I wondered, how much fuel are you going to bum sitting on the ground for 20 minutes extra. Du29 : Yeah. I normally, not that much, sitting on the ground. T 1.29 : Then the other thing is, you are competing with all the other carriers out of Chicago that want to comedown to Atlanta also. I can’t arbitrarily say “American don’t take a ground delay.” So usually, that’s where we use miles-in- trail.

Unlike the first dyad whose traffic manager was initially resistant to the idea of using ground delays at the originating airport to manage arrival flows into Adanta, it is the traffic manager (T 1.2) of this pair who asked the-dispatcher (D 1.2) how he feels about backing off the gate in 15-20 minute ground delays. The dispatcher responded by sharing that due to the limited number of gates at Chicago, pushing the airplanes off the gate and taking a ground delay is an option the airline would be willing to consider.

The following interaction between the dyad discussing the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (referto Section 5.2.3 fora description) presents a different perspective of considerations that weigh oa the preference between airborne 137 holding and ground delays. After listening to a story shared by the dispatcher about busy arrival pushes in Chicago that resulted in ground delays in Minneapolis, the traffic manager (T 3.1) asks the dispatcher (D 3.1) whether he would prefer to take a ground delay or take the delay in the air. The dispatcher and traffic manager then explore the positive and negative aspects of both types of delay.

T3.[57: What would you like to see? Would you like to keep most of your airplanes on the ground? Do you prefer a ground delay program over airborne delays? Dj.i58: It depends on the certainty of the event. With a [pause} if we know(pause} if we can predict with pretty much certainty that we are only going be able to handle x- number of airplanes per hour, then agrounddelay program makes more sense. But if it’s a little bard to predict, whether the weather is going to dissipate, or whether it’s actually gomg to be there, then we would tend to go for a little bit more airborne hoId^g, just so that if the weather does not materialize, or they can increase the amvab rate; that there’ll still be some airplanes in the air. And this is the thing where we have areal hard time, especially when the ground stops. Some kind of weatherevent will come along and they’ll put out a ground stop and they’ll go for an hour after hour after hour with a ground stop, and then all of a sudden they look up and there’s no more airplanes in the sky, and the weather moves, and now all of sudden it’s clear, and there’s no airplanes in the air, because they seem to keep the ground stops going too long sometimes. And that tends to drive us nuts. T3.|58a: So they dry up the system?

In the previous exchange the dispatcher shared that it is the predictability of the airspace that will determine whether he would choose to take a ground delay or opt for airborne holding. In situations of weather where predictability is low, he would rather have the airplane in the air to take advantage of breaks in the weather when they occur. In the following conversation, the dispatcher uses an example as a. way of providing an explanation to the traffic manager about what he means regarding predictability.

D3.1: Uh {pause} TtiSSb: Basically if it came out of a ground stop while the, uh {pause}, you know if they are concerned about a thunderstorm at the airport, once the thunderstorm is over the airport, you know it’s going to move on—

138 . ': ' : :--=;.: ■ - ■ '" ': "

D3.t5 9 : Right Ahdrthey'vestüLgot3-houror4^faourIongrfIîgfatsthatarestillstuck:oathe ground ia Seattle goingto Chicago^ when the thunderstorms overhead, you know that 3 hours &om now that thundentorm. is going to be long gone. And they are very slow to come off of those sometimes....

In summarizing his position on ground delays, the dispatcher stated that his preference would be to take airborne holding rather than a ground delay when the status of the airport at any given time is uncertain.

D3.166: Yeah. Go easy on the ground delay programs unless you are fairly certain that tlie weather is really going to be there (pause }— Tj.166: So that you don’t end up taking a delay on the ground {pause} either for no reason or— D3.167: Or for something which winds up not being there when the flight finally arrives. Tj.[67: Or it is there when the flight arrives and you take a double delay. D3.168 : Well, you know, I think we would rather, in some circumstances, take our chances on some airborne holdings in order to keep some pressure on the airport, so that if the weather is not there, then they can keep the airplanes moving, as opposed to letting them sit on the ground. And then maybe the weather is not there, and they are not running it {pause} they don’t have enough auplanes to achieve the arrival rate that they are really capable of.

Interestingly, the dyad conversations presented in this section regarding the issue of whether a ground delay or airborne holding is preferred by the airline result in differing preferences by actors (i.e., dispatchers) within the same organization. The dispatcher in Dyadi.i stated that a ground delay would be preferred over airborne

holding. The dispatcher in Dyadt.% also supported ground delays as a way of

reducing or eliminating the time spent in airborne holding, hi Dyad]., the dispatcher maintained that more information is needed about the uncertainty of a particular event before he could make the decision on what would be preferred. What seems to be the cause of the apparent difference in response between

Dyadt.t and Dyad 3_i is the context in which they are applying their preference. The dispatcher of Dyadu is usin^die context of a clear weather day where minimum fuel would be planned for a flightt'Ih this situation, airborne holding increases the chance that the airplane will divert rather than get into a. minimum fuel situation. Diverting to another airport would result in greater costs to the airline than would delaying on 139 ■ .^1P -V r^,-,-- '* .? the ground at the originating airport, hn contrasty the dispatcher of Dyad 3.i is considering the context to be thunderstorm activity occurring at or near the destination airport. Because weather is a dynamic and uncertain event, delaying at the originating airport is guaranteeing a delayed flight, whereas taking a chance that the weather passes before the flight arrives at its destination provides some possibly that no delay will be incurred. Several of the traffic managers in this study raised the question of the airline’s preference of ground delay versus airborne holding. Given the different responses by the dispatchers in these dyads, it is understandable why the traffic managers have a difficult time developing an accurate mental model of airline preferences for different traffic flow management strategies. The traffic manager of Dyadu sums it up by stating, ‘This holding scenario is a tough one. I really think that goes to more politics, and you know how it goes back and forth almost one year to the next...a few years ago you’d prefer to keep airplanes on the ground....but then that’s going to back up all your time....” Organizational pressures also affect what strategy is preferred. In Section 5.3.6.5 the dispatcher reveals how even within the same organization the priorities placed on on-time performance and fuel bum are different.

5.3.4.3 Time-based metering

The traffic manager (Tj.i), when discussing sequencing into Minneapolis-St. Paul, brings up metering as a strategy. Metering is a method of time-regulating arrival traffic flow into a terminal area so as not to exceed a pre-determined terminal acceptance rate. He explains that Minneapolis-St. Paul does not use the more widely used miles-in-trail restrictions to space aircraft, but instead uses time-based metering.

T3.18 : —If we are metering it in Minneapolis, and Minneapolis uses a time-based metermg....che controllers at the sectors are given a time that the airplanes are allowed to cross the fix into the terminal area....the computer calculates how much time each auplane needs to lose in order to only feed the (?) and the traffic that they can handle. We front load the system and once the system is full we only put the amount of traffic into the terminal that they can land on the runways. And, so what 140

- "T T ■ — ^ / --iL'

■ V - ' we do, when we offload an airplane^ we freeze in their time, so that basically instead of one or two turns in a hold, they are going the long way and they don’t incur any greater delay. Or it might be a couple of minutes, but basically we freeze in their time so that the reroute eliminates that delay, or they would get a reroute and a delay.

This knowledge allowed the dispatcher to learn about a strategy that may not be as widely used as other traffic flow management strategies, and serves to update the dyad’s common ground as the members strive to understand the roles they each have in efficient use of the airspace.

S.3.4.4 Alternate routing

Another strategy used in managing the volume of arrivals into a particular part of the airspace is by re-routing some of the traffic into less congested areas. In the case where weather is the mitigating factor, a Severe Weather Avoidance Program (SWAP) is implemented by the Air Traffic control System Command Center (ATCSCC). This program provides pre-planned alternate routes that are designed to accommodate arrival, en route, and departure traffic, often using coded routes to simplify coordination.

In the following interaction, one dyad working the Chicago to Atlanta scenario (refer to Section 52.1) considers whether or not using alternate routing would reduce the airborne holding situation.

Tm6: What about routing? - Dn7: E was Ipqlang at that. There’s no-hoIding:ones now, so it still looks like we have to bum more fuel,.so .they were gettihg soine reroutes and they are, looking at the display too, gomg d o ^ there, eveii when they weren’t holdmg, and you take that with any—you know, È they had any problem (?) going through the other centers and volume through mem'centers.

[utterances omittedi

Tt.27b: You are real close to a boundary out there, in that one route to the west, and then, thunderstorms or whatever. Yougetdown by Evansville and you are inside L4I Memphis^ airspace, andcoming over Bowling Green everything is pretty constant. But look out to the east: of that. See those two....you know what I’m talking? Southeast to Evansville. The two routes that swing towards Chattanooga? Dm: Yeah. Tm7c: Alright. That's a shortcut we use on the (?). To send aircraft over direct (?). That usually improves your bum and your time, and it helps us. And looks like Memphis did some of that because that’s just outside the Center airspace. All the black to the southwest of Chattanooga is the holding pattern out there where they...where you got into that. Di.z: Okay. Ti-zTd: Alternate routes? I don’t think you come out any better flying east out of O’Hare, then say, coming down over Cincinnati. That would be a big balance to bring in on Macey [the Northeast comerpostj. If Macey runs, instead of like more, or most of the day, there’s only two times of the day when normal routes really blow up and it’s late afternoon. The West Coast push. Dt-iS: So you are saying, even if we had filed a different route to stay away from center boundaries, that there probably would have been a problem? Tm8 : Right. I don’t think that’s gonna improve anything significantly....

The traffic manager (T 1.2) suggested looking at alternate routing as a way of avoiding the airborne holding that some flights in this scenario experienced. The dispatcher (Di.i) indicated that even those flight instances that did not hold (see Figure 5.1) had a higher actual AirFuel Bum than was planned and hypothesized that this is a result of being re-routed. He also wondered if they encountered problems in other centers. The traffic manager shared knowledge of center boundaries and particular re-routing strategies that are used by the Center. However, he added that

re-routing to stay away 6 0 m center boundaries probably would not have improved the fuel bum. The dispatcher then raises the topic of Severe Weather Avoidance Plan (SWAP) routes. SWAP is normally implemented to provide the least dismption to the ATC system whea flight through portions of airspace is difficult or impossible due to severe weather. A SWAP routers an approved route to minimize the effect of severe weather on traffic flows in impacted terminal and/or Air Route Traffic Control Center (ARTCC), or En Route Center areas.

142 D n 11 : Any thoughts on SWAP routes, if, you know, if any of these were possible SWAP routes? Or what we could have done difierently? T1.2I la: Usually on a SWAP route, if we’re going to send airplanes, at least the way we handle Atlanta.departures, we don’t delay them. We’ll get them off, and try to get them running on a SWAP route, knowing you’re going to fly a little longer. That’s what I’m saying...if you came out of O’Hare to the east and then came down over Ft. Wayne and into Cincinnati, and then come in, basically you are flying over (?) or an obstacle there. Depending on what time of day, or the time in the rush, I could possibly eliminate your holding time. Again, it depends on what the northeast thing is doing, and it would be interesting to see if I told you, I said “Okay, I either need...you know, you’re going to be 30 miles-in-trail traffic off O’Hare, second to your restrictions which we wouldn’t do, rarely, but I’d give you a SWAP route to the east[pause} with a better than average chance of not holding {pause}. Let’s say you are, usually they are about 100 miles longer. Du: Right.

The traffic manager shared how Atlanta Center handles SWAP routes for departures out of Atlanta, and iterated how an alternate route out of Chicago might be handled, but in this exchange he suggested that using an alternate route to the east might result in elimination of the. airborne holding. The traffic manager then asks the dispatcher how much fuel would be used with more flying time and the dispatcher supplies that knowledge.

Ti.illb: I’ve not seen them much over 120 miles on anything we move. How much, I don’t know if you know how much bum you have for. what10 more or 12 more minutes flying time? D,.zl2: Yeah. 10 or 12 minutes, you may need between 500, depending on the equipment, between 500 to 1000 pounds additional bum there.

This conversation about fuel use indicated to the dispatcher that the traffic manager is taking into consideration the concerns that airlines have about fuel efficiency, and the traffic manager learned more about how much cost is associated with the miles added by a re-route.

The following exchange results in the traffic manager gaining knowledge about how airline dispatchers plan their flights when, there is weather occurring m the airspace through which they will be flying. The dispatcher, in turn, learns about how traffic managers at Atlanta Center handle airplanes when there is adverse weather. 143 Dt-2l4 : ....that’s just one of those things that the dispatchers here are always trying to do. You know, if [ATCSCC] Is putting out SWAP routes, we are planning our flights an hour and fifteen minutes minimum before departure time. On bad weather days, dispatchers try to stay ahead of their releases by at least two hours In case they have a physical problem there. They don’t get behind on their releases. So, if there is bad weather there, they are planning It two hours out before departure time, and then two hours time In the springtime, the thunderstorms could move quite a bit, so they are always looking for the best route when they are planning it to avoid the thunderstorms. If they’ve got a line, you know, that was In between Chicago and Atlanta, if the volume was (?) at Atlanta, they might try to come out to the east and down the eastslde of the thunderstorms, but If the line is moving fast they may go ahead and plan a route like this, planning the line of thunderstorms to move on east of Atlanta by the time they arrive there. It’s kind of a timing thing for us, as far as the planning goes, on which routes we select and also what you guys are putting out on the SWAP routes. T[.zl4: Usually we don’t move airplanes until they start flying through the weather really, and then we’re always a little behind the crew. And which can be good and bad, and you know, if there’s weather out there, you’re right. You should file out to the east and come on a different route, on a SWAP, and that’s gonna improve your fuel bum and everything. And that’s something two hours ahead, you all probably have a better idea of what’s going on. We are concerned more with real time.

This exchange points out the differences in how the dispatcher and traffic manager work in bad weather situations and how each way can be problematic. The dispatcher plans the flight two hours ahead of time, but with the unpredictability of how the weather conditions will progress, his plans may not be adequate as the weather event unfolds. The traffic manager, on the other hand, waits until the flight is encountering the weather event before moving it. This creates problems if it means that the flight is given a less efficient route than might have been possible if planned earlier.

While^Dyad 3.t is having a dialog about grpund delays and event certainty (refer to Section 5.J.4.2 for thisrinteraction), the dispatcher is reminded of how re­ routing due to weather can result m unnecessary delays because of how quickly the weather situation can change & d hcg^v'response to that change is slow.

144 Dj.159 : ....Same tbingkwith reroutes too. You’ll have a {pause} there’ll be a deviation on a partlculac rgutébecause of some weather out there and they’ll publish a reroute, and then they’ll just stick with that reroute after the weather moves on, and we have a real hard time getting them to go back to the primary route after the weather moves. They’re [ATCSCC] sometimes slow to move (?) off of the route when the weather is moving In, and then they are very slow moving the traffic back on the route after the weather moves.

The dyad working the Dallas-Ft. Worth to Newark scenario (refer to Section 5.2.5 for a description) proposes the possibility of using alternate routes rather than the filed route in this scenario. The traffic manager introduces this idea in the following utterance while looking at slide 2 (see Figure 5.17).

T5.114b: You know, this guy on a normal day, you know, might call ATC in August and say what’s going on and stuff, and they go from there....If you take a northerly route going up by Evansville or something like that, who knows, you know?....

The pair then moves on to slide 3 (see Figure 5.18) before they resume talking about this alternative solution, hi the following exchange, the dispatcher 5 )5.1) continues with the proposal of re-routing the flights in order to avoid the delays occurring in the Washington DC airspace. The traffic manager (T5 . 1) puts a prerequisite on this proposal, suggesting that prior to re-routing, the airspace where the flights would be moved needs to be evaluated for capacity.

Dj.| 17: ....Once again, you know, that’s Just an overflow from normal DCA, like we said before, you know, uh— T5.t 18: Well, this is the next logical step when you’re full overhead Charlottesville or something. Start holding around Raleigh. Ds.tl8 : Yeah. Like I said, you know, and this Is where I’d be looking at gomg up over ftidy. (?) something (?) that way, because you know, 9 times out of 10 this just looks like a typical DCA center scenario. That’s what I’d be looking at If I had to reroute, or you know, if I could anticipate these type of delays and etc., etc...fuel bums, and they probably would warrant myself to re-file these guys up over, like 1 say, ftidy coming In that way. Ts.tl9: Yeah- Or you’d at least want to know that the traffic Is moving In firom that direction. That would be my mam pomt, as to how are the other planes that are going to Newark coming over dl&rent arrivals fixes and how are they making out kind of thing.

145 03.(2 0 : That’s normally what we^you know^ once it starts^ scenario does start» it’s a snowball effect. We’ll get the mfbrmatioa from the ATC coordinators and stuff» and it just filters right down to us, and we’ll take (?) actions of (pause/ We’ll have our (?) guys contact you and find out the detailed information and go with that. If this is a normal day occurrence, you know, like I said. Like I know what [the researcher] was saying before [referring to the Training scenario; see Appendix Q, they worked it out between [the two airlines] where they’ve now, uhfpausej here in DFW, I think it’s like six: flights a day,[ both, of the airlines] have tsüœn the southerly arrival fix. to alleviate that, you know, dog leg or delay, so it works both better for us and better for the system. Tjii21: At least you’re planning for it, so it’s not, you know, some adjustment you’re making in route kinda thing.

The dyads that explored the solution of alternate routing discussed several issues that can be useful knowledge for the members. These include the following:

• The impact of strategic and tactical re-routing • The necessity of understanding what the traffic situation is on proposed alternate routes • The benefits that might be realized by using trend data for better flight planning.

5.3.4 J Delay vectoring

Delay vectoring is an arrival flow management strategy used to sequence and separate arriving flights during the en route phase of flight, fri the following interaction, while the dyad is assessing the situation illustrated on slide 3 of the Chicago to Atlanta scenario (see Figure 5.3 in Section 5.2,1), the dispatcher ^t-z) asks the traffic manager (Tt.a) about the vectoring that this flight instance experienced. , . -..i

Tt.j43a: Well, the Jog up by N^bvilFè is gomg to be Memphis doing that. Yeah, we’ve probably had some miles-iq-ttaiToii this because Td say if they are out there turning, ’cause that’s^retlyj^ to show up on this scale, that’s a bigger turn in traffic. That’s probably ÿi^es-m-trail turn. And then right where it takes that southwesterly turn, JûSt'norÜi’bfETuntsville. That’s right on the western edge of 146 our airspace, and what they dîd was take the aircraft, run it to the southwest, hook it ia a gap from the other transition forces off of Memphis, and uh, (?) and it sits right there at (?), and then they ran it straight on in. So there, there*^s not a whole lot, to me, not a whole Tot to do because it's real time.

[utterances omitted]

T t.243c: ...And in that case it was most likely controller's choice, instead of going to the pattern to (?) for the arrival spacing. And he very well could have gotten a 40 or 50-mile, 60-mile vector to go down and hit the gaps. When he goes from Huntsville straight in, uh, there you see the normal route over in Nashville, to hit its point outside of Atlanta, and that's (?), so you know the way you run miles-in- trail, you make a (?) triangle, that's what we call them D,.z43d: Right. Right.

The traffic manager shared knowledge about what probably was occurring in the airspace at that time and hypothesized what was the reasoning behind the action taken that resulted in the vectoring.

The dyad partners working the Chicago to Boston scenario (refer to Section 5.2A for a description) discuss vectoring in the following exchange. The traffic manager provides an explanation to the dispatcher about the vectoring that is illustrated in slide I (see Figure 5.12).

T4.112b: Cleveland. We don't usually give them too much, too many miles-in-trail restrictions, but once they get into that sector, that's our Area A sector, they are going to start vectoring to go in trail to Boston. That's when all the flows are coming together because Cleveland will hand us aircraft at 28,000; 35,37, all on top of each other, and then that sector's going to start spacing them. D4.[12c: Right. Okay. T4.tl2 c: Even if it's 5 miles-in-trail, they have to do something, as you know, because as they descend down they have to be in some sort of line or it' sjust not going to work. So that's conceivable why they are zig and zagging right there. That would be the spot. You don't want to do it as they are coming down to 11,000 feet, getting ready to hand off the approach control, and they are suddenly getting a quick spin to get m there.

In both dyads in this section,^ the traffic manager explained the traffic management rationale behind the vectoring that occurred in the scenarios. The dispatchers learned that vectoring normally is used for the purpose of sequencing 147 aircraft for arrival into their destination airport. In both cases, the traffic managers did not identify vectoring as a problem, and after their explanations, the dispatcher in each dyad did not explore it further in their problem solving.

53.4.6 Altitude Separation

On slide 3 (see Figure 53 in Section 5.2.1) of the Chicago to Atlanta scenario, the dispatcher (Du) begins a discussion of another solution - that of altitude separation as a way of managing the volume of traffic. He does this by asking the traffic manager if they can space the traffic out using altitude rather than miles-in- trail.

Di.v44a: Altitude wise. Do you guys know what your traffic is coming in at certain altitudes? And you know, going back to the previous question on the last display, can you space them out altitude wise? You loiow, vertically as opposed to horizontal spacing, which it looks like they did here? T1.244a: Well, we restrict, say put arrival restrictions for Atlanta out. They are put out in the range of altitude, and that’s figured 24,000 and above. Dt.244b: Okay. T|.244b: That’s usually what we figure. And it’s done that way fora reason. Because if get two stacks, one at 31 and one at 35, we haven’t accomplished anything to space the airplanes out, [to] provide the transition. So, at that point, coming in at a particular altitude, you may still get a turn, but your traffic may be overhead, you know at 35 or 39,000. Altitude really is, unless you’re down low where there’s a great variance in the speed and the wind, altitude is not a big concern on what we’re looking at here. Dt-244c: Right. Right.

The intent behind the question asked by the dispatcher appears not to be understood by the traffic manager as he explains that when they put miles-in-trail restrictions on the arrivals into Atlanta, they do include altitude. He goes on to say that for the scenario they are currently working, altitude is not something that needs to be considered. The misunderstanding is not pursued by the dispatcher and there is no further exploration by this dyad of altitude separation as a possible solution.

148 In the following discussion of the Dallas-Ft. Worth to MinneapoIis-St. Paul scenario (refer to Section 5.2.3 for a description), the dispatcher CD 3.1) proposes to the traffic manager the possibility of altitude separation or Low-Altitude Arrival and Departure Routing (LAADRing), The LAADRing strategy offers a way to dynamically decide what flights should be held at lower altitudes and thus can increase airspace capacity by reducing controller workload in any of the affected sectors. Initially, the trafRc manager (T 3.1) is resistant to this proposal, but as the discussion progresses, and the dispatcher continues to share knowledge and explanations, the traffic manager finally agrees that altitude separation may be a workable solution to the delays that the airline is experiencing in the Minneapolis-St. Paul airspace.

D3.184 ; ....And they don’t seem to use a lot of altitude separation either. And it would seem like maybe you could have, you know, if the northeast is open and the east is closed off, maybe some arrivals come in at one altitude and departures at a different one, or something like that, over the same area. T3.[84: Well, you’re right. They don’t like to do that because that usually requires you to (?) departures. Nobody seems happy with that. I mean, your departures are pushed down, and everybody’^s looking for higher. Dj.t85: That beats sitting on the ground, seeing as you’ve got to go with low altitude. Do you guys have LAADRings in any of them? Tj.[85: Yeah, we do have LAADRing, but uh— D3.i86 : That seems like something that’s only starting to get phased in in most areas. Tj.t86 : Yeah. Well, it’s under a new name anyway. But still they don’t normally like that, r mean, you could LAADR to get your departures out and if the overhead stream is full, you can ladder them into a low altitude sector, but I don’t see that you’re normally going to be running arrivals and departures in the face of each other because, well [pause} I’m trying to figure out how that would really work. I mean, that’s [pause} the arrivals still have to get down. D3.t87: Yeah. They’d have to be all set somehow or another, I guess, so they can [ apply} and descend. Tj.t87a: And a controller at a sector doesn’t step, you know, 1000 foot at a time all the way down from 39,000 feet. You know, they give you an [introduce} on clearance. They’re not going to step you down with another guy head on climbing up- D3.1: Yeah. = ‘ Tj.i87bt ■ It jusbwork^a lot better ifyomhaye thetnseparated. Arrivals come in one way anddepartutes go mother. M d you can ted the whole stream to descend to an altitude and just A^tdhtheiriall go in a profile decent Dj.,: Yeah.

'■ ' 249 ^ â ' P jtV \ " Tj.i87c: And likewise it just wouldn’t work to have departures Just start climbing them at a different, (pmise} you know, because when you run in a stream of departures, some airplanes are climbing at a faster rate than others— Dm: Right. / T3.i87d: —so yoitcan’t really be climbing out at standard rate of climb, and right on top of them having a^qfile^escent stream, because they are not all climbing and descending at the same rate. D3.188 : Well, like an en route line of thunderstorms whereas maybe one hole in this huge big long line, and a lot of times they’ll only be doing arrival, or they’re only doing departures through that hole, would it not be possible in that kind of a scenario that you could do two-way traffic at two different altitudes? Tm88 : Uh, yes. I think that would work. D3.189 : That would be really nice.

This dyad did not pursue this topic any further, which may be a result of both the complexity of the concept of LAADIUng and of the apparent difficulty the traffic manager had in conceptualizing exactly how this strategy would work. It is important to note here that the traffic manager was new in his position and still in training.

Among the strategies used in Arrival Flow Management to achieve optimum use of the NAS and minimize the effect of air traffic delays are the following:

• miles-in-trail restrictions (i.e., instructing pilots to maintain a particular distance between leading and trailing aircraft) to space aircraft

• balancing arrival fixes to allow less congested fixes to absorb the overflow from other fixes

• speed control or slowing the airplanes en route

• delay vectoring

•- alternate routing

• ground delay programs (i.e., holding flights on the ground for a period of time).

150 The knowledge sharing that occurred between the dyad partners In the present study includes discussions of the possible benerits and potential costs of using these strategies. Even though traditionally it has been the FAA organizations that have imposed which strategies are used in what situations, it is apparent from the interactions described here that the members in each dyad viewed the problem of when to employ the strategies as one of collaboration between them. They shared knowledge with one another, which enabled their common ground to build as they moved toward a shared view of the problems that each strategy could cause or solve.

5.3.5 Arrival Flow Management Constraints

Understanding the constraints that exist in the National Airspace System (NAS) is essential if the airlines are going to plan their flights to fly as efficiently and safely as possible without incurring a possible re-routing penalty by traffic management. The constraints discussed by the dyads in the present study include the configuration of the runways at the destination airport and how weather impacts the configuration, the time of day, the airport arrival rate at the time the flight is arriving, and the traffic that is crossing the airspace en route to other destinations.

5.3.5.1 Runway configuration

In the following exchange the traffic manager shares with the dispatcher some of the constraints that exist in the Minneapolis-St. Paul airspace (see Section 5.2.3 for a description of this scenario). The knowledge shared with the dispatcher by the traffic manager during this interaction includes the constraints imposed on traffic management because of arrival and departure schedules (airport capacity), the runway configuration at the airport, the penalty a flight might incur if re-routed to another arrival fix, and where.flights are held when sectors are at capacity due to holding flights and overhead riafiic.

151 TmS : . ...You know, some of the constraints that [ would see, and I'm sure you are familiar with, is the time of day....you are contending with ail the Northwest Jets ....it would depend on which runway we are landing at Minneapolis. We have I2’s or 30’s, and the Casper arrival gets very busy. I've worked that myself high/low altitude, and if we are landing 30's, if we were to fix balance, meaning swapping to another gate like the northwest—or actually, it would be the southwest gate, which would be the Redwood Falls Gate.... Landing 30's, that would be a pretty good penalty. It would— D^S: Yeah. It's pretty significant re-route off of the flight plan. T3.24: Obviously the earlier we catch, it, it looks like there were some that were caught that were re-routed basically like dead center of Iowa, just north of Des Moines, and then this bend right here that fm pointing at, that's basically where Redwood Falls ends. That's one of the transition points for the Redwood Falls [Skeeter] arrival. That's what it’s called. So then they'd have to go, uh, basically if you are coming in here, they tty in on the Casper route when they come to Farmington. Usually they depart Farmington on a southeasterly heading to land 30's.. ..So coming from over here, it's going to be a bigger penalty....So, from what's seen, if we would Rle this routing, and like you said earlier, it's a pretty direct shot, and it's Just on the time of day we don't offload or try to fix balance, move the gates, and move the aircraft around the different entry points unless we absolutely have to. Obviously during the rush periods there will be some speed reductions, some miles-in-trail. And possibly we would (?) without holding, but if there's going to be any significant holding....

5.3,5.2 Arrival rate/crossing traffic

The traffic manager (T 3.2) of one dyad working the Dailas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3 for a description) shares knowledge in the following exchange of the constraints that airline trafffc crossing through the Minneapolis-St. Paul Center airspace places on the arrivals into Minneapolis-St. Paul.

And we would bold aircraft there (Mason City] if the rate at Minneapolis, and you know, obviously the weather is going to be a big factor in this too. But if the landing rate, let’s say it's like today, blue, clear and we have a 6 6 rate. That's pretty much optimum landing atMinneapolis. It really doesn't get much better than that. If the weather was down for some reason and we anticipated a lot of holding, the sector gets pretty busy holding aH the aircraft plus overhead flight traffic, then we'd move it up'maybe into the Redwood Falls and hold it over there, and thenit wouldcome inhere:...

- 152

« S t- This increase in traffic results in sector overioad and arriving aircraft must be moved to other sectors that have less trafSc as they wait for sequencing for arrival.

5.3.5.3 Peak arrival times.

During their discussion of slide I of the Dallas-Ft. Worth to Atlanta scenario (Figure 5.4 in Section 5.2.2), the traffic manager (Tm) of this dyad hypothesizes in the following exchange that the major factor contributing to the airborne holding delays is that the flights are arriving at peak arrival and departure times for Atlanta. On slide 4 of the scenario (see Figure 5.7), the traffic manager’s hypothesis is supported, and he shares knowledge of the air traffic situation at Atlanta during the time of day that this particular flight instance arrived.

T2.i4 9 : This particular flight held at Montgomery, and he was trying to arrive here, would be 15, that’s another busy time, right at 3:37 in the afternoon. That’s another flight. Like I was saying between 3:30 and 4:15 is our peak time during the afternoon. D2.i49 a: Yeah. It looks like the same thing. They held them out there for a while. It looks like they just moved them around a bit to space them out a bit maybe. At the time period, that’s really a peak period too, right?

[utterance omitted]

02.(50: I would think that most of the—really of the 42 flights that was delayed, that was probably because of the peak period times at the Atlanta Center. T2.i5 lb: Because 3 o’clock is without a doubt the busy time, or 3:30 to 4:15 is the busiest block of time that we have all day long in Atlanta.

5.3.6 Airline Considerations

Air carriers have goals, priorities, and constraints that need to be considered during pre-flight planning. These considerations include:

• pilot strategies

• fuel consumption

153 Federal Airline Regulations CFARs)

# ground delay versus airborne holding

• priorities of different organizations within the Airline Operations Control Center (AOC)

• flight scheduling

The following text provides examples of the interactions that occurred between different dyad pairs as they discussed particular airline considerations in the context of the scenario on which they were working.

5.3.6.1 Pilot Strategies

One of the factors that an airline dispatcher must consider in planning and monitoring a flight is what strategies the pilot might use in reaction to changes that occur en route in his or her filed flight plan, hi the following interaction, one dispatcher (D,.i) working the Chicago to Atlanta scenario (refer to Section 5.2.1 for a description) shares knowledge about the impact putting an airplane in airborne holding can have on whether or not a pilot decides to divert to an alternate airport rather than risk getting into a minimum fuel situation.

Di.i38a: .... like I say, on a good weather day when there’s no traffic problems, no en route problems, no turbulence the dispatchers are trying to release these flights with minimum fuel— Ti-t: I see. Dn38b: —and if they do that and you have 15 minutes to hold, these pilots are only gomg to hold for 15 minutes, you know if they’re getting to their minimum fuel, they’re not gomg to stay around for that, saying, 'Tm going to my alternate.” T[.(39: I understand your problem. Isee it quite often.

In the following conversation about the Chicago to Atlanta scenario, the dispatcher (D 1.2) of the second dyad working the raises a concern with the traffic manager (Tt.j) about the difficulty his airline runs into with pilots who are given a

15+

.

■■ certain Expect Further Qearance (EFC) and want to go to their alternate instead of waiting out the defay.

Di.237: ....one of the things we run into, that the pilots give us a call [about], is they're given an EFC [Expœted Further Clearance] of, you know, sometimes 45 minutes into the future or something like that„ and we’ll give [the] Center a call, and you guys are, after takmg ^second look at it, able to give us a more optimistic EFC that we can pass on to;the flight and hopefully get ’em to hang around for a turn or two in holding, and get on in. But a lot of times, if our flights don't give us that opportunity [by contacting us], they'll assume that that EFC time is set in concrete and they' II say there’s no way they can hang around for that amount of time, and they'll (?) off right away and divert on. T(.:37: A. lot of times, E would say, what gets done by most controllers is, you started in EFC. You know, the aurport shuts you off for whatever reason, and you start with, say it’s zero zero. Well, if you're gonna go in five minute increments, some keep it fairly simple. So the next one, okay, you're gonna see no five, ten, and if we just go right up the stack [pause/ Then that's how you can be seven or eight airplanes up and have a 40 or 45 minute EFC. In reality, it's not gonna take you that long for, once you start the traffic back. Then usually once that airport, you know, if we overload them a little and they digest it, then we can, or if, one of the fixes empties out real fast, because they are not balanced fixes at all. You may have 30 airplanes on one side and 20 on the other, and once one fix empties out, then that holdkg stack may actually run in at 5 miles-in-trail, even though the airport's cleaned up, there's not a demand on it, so we'll empty the stack out real fast, and we make every effort to, but usually this happens in 5 minutes all the way up. And once they issue with EFC and let the pilots coming up on it, they're probably not going to go back and revise that as the planes come down through its pattern.

During this discussion, the traffic manager learned about how Expected Further Clearances (EFCs) that are issued for a longer period of time than necessary can have a negative impact for the airlines and the passengers of those airlines as a result of the pilot's reaction to the EFC, making a decision to divert to an alternate airport. He also gains knowledge about what role the dispatcher plays in persuading a pilot not to divert to his alternate airport. The dispatcher has learned about the constraints with which the traffic manager has to deal due to the unpredictability of how fast or slow the airport will be able to absorb the overcapacity situation. He has also learned that if the arrival fixes in Atlanta are not balanced, and if an aircraft happens to be holding at a fix that is more congested, the EFC will be longer than at a fix that has fewer aircraft.

155 : S’’-'

In the following conversation the traffîc manager, while considering slide 2 (see Figure 5.9 in Section S.2.3), suggests a way that he might be able to reduce the flight’s airborne holding time.

T3.1I8 : ....that 62 minutes of holding—uh, you know, it always seems like we could come out of holding a little bit earlier, and if you work hard at it as a controller and a supervisor and aTMC, we could cut maybe 10-15 minutes off of that, but that would be at the very outside. You know what I mean? D3.2I8 : But r II tell you, a lot of times that 10-15 minutes makes a big difference when these guys are holding, particularly if they’re getting towards the end of their holding fuel. Ifl give them 60 minutes, it’s a rare occurrence, where I’ll actually get 60 minutes of hold out of all pilots. And there’s always a unique group, you know, where should they, they hold for 75-90 minutes, you know. I’m trying to figure out why is he not dropping out of the sSy? But generally most pilots from my experience at my airline, have been, uh, they, ifl give them 60 minutes, I should get maybe at least 45 out of them, unless they’re getting sequenced inbound. And if they know that the light’s at the end of the tunnel, then they’ll keep motoring in. But if your fellows give them some wild ass EFC for like two hours, it’s, you know, they’re getting ready to jump ship after five minutes. And then I’ve got to get on the radio and talk to them, and bring them up to date, and say, okay, you know? Basically, I’ve got to hold their hand for the next45 minutes.

The dispatcher has informed the traffîc manager know that even a minimal amount of time savings can have a beneficial impact for the airline. He then shares knowledge about pilots’ thinking when considering how long to hold and when to divert.

When discussing the flight instance in slide 4 of the Dallas-FL Worth to Minneapolis-St. Paul scenario (see Figure 5.11 in Section S.2.3), the traffîc manager shares, in the following excerpt, knowledge about when fix balancing is used (i.e., “only...if we really need to”). The dispatcher then explains to the traffic manager about the strate^ dispatchers use when deciding whether or not to list an alternate airport. He also shares that different pilots have different philosophies about the amount of holding fuel they need to carry and what the dispatcher does to make the pilots feel more comfortable.

-

O s . - : Tj.237a: It looks like we just fix balanced....We only use these fix balances if we really need to. D3.237a: I think as long as the captain feels that he’s still motoring inbound, and fuel’s not really an issue. I mean the voice of doom is when they expect to go into the hold, and I will [puU] an alternate on them, and maybe I Just have 22 minutes worth of hold fuel. Because for us we use so many minutes of hold fuel if we don’t have an alternate. And then if I do list an alternate, that amount of hold fuel will go down. So like what I’m trying to say is if I’m using Rochester, Mirmesota for Minneapolis as an alternate, 1 might only put on 10 minutes of hold fuel. But if r m going alternate none or not carrying an alternate for Minneapolis, the system may default to maybe 22 minutes. So, and that was one thing that we suggested from Dispatch is that there’s a pilot psychology out there, you know, some guys just want to feel, or they feel a little bit safer if they have an alternate. 1 mean, if I’m carrying an alternate, 1 don’t need to carry 22 minutes of hold fuel on a good weather day. I’ll cut him back to 5 or 10 minutes. So, 1 guess, really all they want to see on the paperwork is "Okay, 1 need 3,000 pounds to go from Minneapolis, from missed approach of Mitmeapolis to Rochester.’’ So they can see the numbers and they feel more comfortable with it.

This interaction has helped the traffic manager understand the perspective that the pilot and dispatcher have concerning airborne holding and how holding will impact the fuel situation. This shared understanding can now be a consideration by the traffic manager when airborne holding needs to be imposed.

5.3.6.2 Fuel consumption

As the dispatcher (D 3.2) of the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3 for a description) shares with the traffic manager (D 3. 2) about some pilots’ desire to carry more holding fuel than conditions dictate, the traffic manager questions what is the problem with having more fuel than is needed on board the airplane.

T3.239 : What would be negative about having too much fuel? D3.239 : Well, basically the company’s standpoint is that you’ll burn about 10% more of whatever you are carrying. So ifl carry a thousand pounds more than maybe what 1 should, i’ll burn 100 pounds of that to carry iL So, I really don’t carry a fiill thousand pounds from Dallas to Minneapolis. Yon know, Fm going to end up burning some of thalL And it’s Justaninnbers game with us doing 2500 trips a day

157 or there abouts^ you. know^ the corporatioa^ the beaa counters, as we would say, you know, they say “Well, if we can save a thousand pounds over 2500 trips, that’s what, 2,5 million pountk of fuel a day, and if you can save 10% on that, you’ve save 250, you know, a quarter of a million pounds. So, I mean there’s some truth to that.

This interaction allowed for more knowledge dissemination, adding to the traffic manager’s schema about what is important to the airline and how something so seemingly innocuous about carrying 1 ,0 0 0 extra pounds of fuel can have a great impact to the airline’s bottom line when considering that 1 ,000 pounds multiplied over several thousand flights a day,

53,6,3 Federal Airline Regulations (FARs)

Federal Aviation Regulations (FARs) are federal rules under which flight operations are conducted. In the following interaction, the dispatcher (D 2-2) working the Dallas-Ft, Worth to Atlanta scenario (refer to Section 5.2.2 for a description) discusses the FAR 121 section that states the rules under which aircraft can be released when there is. weather. .

02,233: ....another problem we have, and this is mosdy Ft. Worth than Atlanta, is even though [the Command Center! will put out that a SWAP [Severe Weather Avoidance Programfrbute’s in effect, the Center, from what I understand, really doesn’t want us to file that way because if they switch ffom a Texarkana or Shreveport routing, and based on sending guys over north, over McCallister, and we start filing that way and then the weather cuts off'McCallister, we can have an East Coast flight wind up going over Abilene. So they keep switching the departure case. And I’m trying to tell the dispatchers that, although they have a problem because. ..the FARs say they’re not allowed to release a flight into known weather, and we don’t change the routes. So we are kind of going around about that. We understand why the Center does it: We’re trying to come up with a happy solution, you know, somewhere so we can. all be on the same page as to what we can do about it. TmSS: Well, 1’m not familiar with that FAR. thing there, because it has been, especially on the ffont end, a big educational process with the dispatchers and the airlines here in Atlanta where they have departure route; we can relay on teleconference this is what we’re going to do. The Center will make the amendments. Tower will give them the coded clearances to the aircraft, and we move them. But that’s not saying we can move everybody. If we can get 30% of the airplanes on the normal routing, 158 ' ^ I - f ,r r^ r -

(?) want us to move 30% of them that way, then we’ll take the other 70% around the weather because we got, you know, we’ve got some portion of the airspace that we can use to get limited amount of airplanes per route, you know, some holes in the weather. So that’s the Center perspective anyways as far as traffic goes. Dz.z34: Well, it sounds like Atlanta Center has a better handle on it because of the coded SWAP routes, but right now since we don’t have any in effect here at the Ft. Worth Center, it’s pretty much, you know, even though there’s a Level 5 over Texarkana and we know that the Center’s not going to let them go that way, they’d re-route and send them over McCallister. They don’t want the dispatcher filing over McCallister, leave them over Texarkana. And the dispatcher’s saying well I can’t ifl know there’s a Level 5 there, and E think we're kind of understanding, I think we’re Just going to put extra fuel on it at that point, and with the understanding that the Center will, of course, route the area around the weather. So, ah I think that’s pretty much, you know, it’s just sharing information and trying to take your dynamic situation and kind of meet me half-way with our 3-hour out planning situation so we kind of have enough fuel to complete the mission for us. We’re not going to plan every flight for worse case scenario, but when we know there is weather out there, to try to have the fuel for it.

The dispatcher has suggested that collaboration between the organizations when considering re-routing due to weather conditions will allow the airline to plan better with respect to fuel requirements for an aircraft. This collaboration will also allow the airline to be in compliance with FAR 121.613. The traffic manager has learned that he needs to become familiar with the FARs in order to understand the constraints under which the dispatchers must operate.

53.6.4 Ground delays versus airborne holdin;

The traffic manager (T 4.t), working the Chicago to Boston scenario (refer to Section 5.2A fora description), begins the following conversation about airborne holding versus ground delays and how it seems that the airlines continually change their positions on which they prefer.

T;.tlO: This holding scenario is a tough, one. I really thmk that goes to more politics, and you know how it goes back and forth almost one year to the next. How, I think a few years ago you’d prefer to keep the airplanes on the ground, and then when everythmg opens up then you let them go. Then obviously you are going to save in fuel, but then tha^s going to back up all your time and all your—

159 D^-illa: Exactly. That’s why E know where you’re going. And we opted to say, let’s make it our call if we want to put the fuel on and hold^ as long as you folks can handle that. And I think that’s what most of the thought is here. T4.1 lia: Yes, absolutely. Most ahlines are saying, we are going to put our aircraft on hold, and then the second the clouds open up for even a minute or two, we are going to jump down there and land. Because it helps your schedule all the way around. And it actually does make sense. We Just have to monitor our holding stacks to make sure we don’t have too many airplanes. We Just can’t overload the system.

The traffic manager’s statement about the changing preferences of the airlines regarding holding on the ground versus airborne holding allow the dispatcher (D 4-1) to suggest that the best thing to do would be for the decision to be left solely with the airlines. The traffic manager was open to that approach but only as long as leaving the decision to airlines does not result in congestion of the airspace. What is important for the traffic manager to realize is that the decision that the airline makes regarding whether ground delays or en route holding is the preferred action is dynamic and prone to change. The certainty of the event that requires such a decision is one factor that the dispatcher needs to consider when deciding whether ground delay or airborne holding is the preferred strategy. In

another dyad the dispatcher (D 3.2) expands on this topic while discussing the Dallas- Ft. Worth to Minneapolis-St. Paul scenario. (Refer to Section 5.2.3 for a description of the scenario and Section 5.3.4.2 for this interaction.)

5.3.Ô.5 Airline Intra-organizational differences in priorities

Di a discussion about the Air Fuel Bum and Air Time performance metrics found in slide I of the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (see Figure

5.8 in Section 5.2.3), the traffic manager (T 3.2) asks the dispatcher (D 3.2) which metric is more important to keep as close as possible to optimal levels. The following conversation ensues, and the dispatcher is able to share knowledge about his airline, and how even within different parts of the organization the emphasis on what is important to optimize varies. The dispatcher also shares knowledge about the flight 160 planning tool that dispatchers use and the dîRërent parameters that affect flight planning.

D3.2IO: ...I think headquarters likes to see the on time dependability, butas far as my managers are all concerned here in the Dispatch, they’d rather see thefiiel numbers come out as planned, so I think maybeeven within the corporation here, there’s a—I don’t know if I would say a battle, I would say a difference, but you know, headquarters people want to see the on-time dependabiliQr probably, regardless of how much gas we are burning. But here in our department the managers try to sensitize the dispatchers more towards planning the fuel and trying to keep the fuel bum as close as [possible] to what was planned. T3.211: Is there an end of year type evaluation on dispatchers? Is there a tolerance that is looked at for fuel bum? D3.211: ....the flight department looks at the fuel bums. What my department looks at is how much fuel is the dispatcher putting on the trip initially. You know, if one dispatcher is always carrying Fargo, North Dakota [as an alternate airport] from Minneapolis, while everybody else is always going alternate none, or carrying, you know, no alternate required, you know, based on the weather conditions in Minneapolis. Our computer system defaults to a pre-programmed amount of minutes pulled for Minneapolis, depending on the city pair, depending on the type of airplane and time of day. They pretty much have this, or what they think is to be fine tuned that, you know, a trip that leaves Dallas and goes to Minneapolis and arrives there maybe at 1500 Z, our flight planning screen might be pre-set with 13 minutes of hold, where a flight that arrives maybe around 2300 Z might be pre-set for 21 minutes of hold. Particularly if we are coming in at the same time the hub airline’s push might be coming in. So my dispatcher managers do a monthly critique on whether the dispatcher followed the plan that’s provided to them on their flight-planning screen. And our flight-planning screen allows us to modify the alternate’s hold, time, additional fuel, made for weather deviation or for de-icing coming out of Minneapolis in the wintertirae....[T]hey watch what we call discretionary fiiel figures, where the dispatcher can go in and modify numbers, hold times, alternates, one alternate, two alternates, additional fuel figures. That’s generally what they critique every dispatcher on every month. And we are not critiqued on time, flight-planning time. That’s more of an element from headquarters, you know....

With this knowledge, the traffic manager is able to add to his schema of airline operations and allows him a fuller perspective with which to view the constraints within which dispatchers work when planning flights.

161 S.3.6.6 Flight Scheduling

The arrivals and departures of flights into a hub airport are scheduled in clusters or banks. The rationale behind this is to allow passengers to catch connecting flights to other destinations without incurring long waits between connections. However, this type of scheduling can lead to flight delays caused by air traffic or ground congestion.

In the following interaction, the dyad working the Dallas-Ft. Worth to Atlanta scenario (refer to Section 5.2.2 for a description) proposed only one class of solutions, that of adjusting the air carrier’s schedule for arrivals into Atlanta in order to avoid the greatest traffic volume periods, hi order to do this, the pair discusses what they would need to do and what data would be required in order to better understand how the arrival schedules needed to be adjusted. Early in the assessment of the situation, the traffîc manager (T 2.1) focuses on how he would approach arriving at a problem solution.

T2.16: So if we wanted to analyze this problem, it would like that, uh—... Jt looks like if we wanted to solve this problem, we would identify the times when these 42 aircraft were holding, and 1 would guess that they’re all during the busy time periods, which is 8 o’clock, 3 o’clock, 5 o’clock, To’clock, and adjust some departure times would be the best way to resolve this.

The traffic manager shared with the dispatcher (T 2.J knowledge about the busy time periods at Atlanta. This knowledge is important if the decision is made that avoiding the peak arrival and departure times is the best way to avoid airborne holding delays. The discussion then moved into an assessment of the 272 flight instances that did not encounter airborne holding (see Figure 5.4 in Section 5.2.2). Following this assessment, the joint decision was made that it was the 42 flight instances identifled as incurring airborne holding that needed to be the focus of the discussion. The pam

162 then return in the following interaction to their proposed solution of adjusting arrival schedules.

T2.[2 0: Well, like I said, if it were me on your end, I would look at these 42 flights and see if they were duplicated or if they were holding at the same time on a daily basis. And If they were entering the holding pattern at the same time every day, and maybe flights were being duplicated holding everyday, that’s where we would address the problem, and try to do something there with a schedule reduction or whatever during those time periods to eliminate, if we wanted to look at eliminate, the additional fuel bum.

[utterances omitted]

T:.i22: Yeah. I would guess that it would be a demand problem at the airport, which is what we run into here at Atlanta. And the best way to address something like this is to look at the demand on the airport at that particular time, and determine the times when you were doing the holding, look at the demand during that time, and see what might be better. Sometimes a 5 to 10 minute change in a flight arrival time could impact whether or not that flight had to hold or noL

Again, the proposed solution is to change arrival times of flights into Atlanta. The dyad then moves to slide 2 (see Rgure 5J), and after partial assessment of the situation for this flight instance, the traffic manager suggests that, had this flight had a different arrival time, it would have avoided the airborne holding delay.

T:.i42a: He held 16, or he was 16 minutes late anyway. That’s what I was saying, if he had delayed or got here probably 15 minutes later, he might not have held at all. That particular flight Is getting in here at a time during the day when he’s probably going to holdjf he arrives at that time, day in and day out. So that’s probably one of the ones that’s hit on a routine basis.

This dyad focused only on the solution of changing the time these flights arrived into Atlanta. The assumption was made that it was the arrival time that was the cause of the increase in air fuel bum, even though there was no way of verifying this with the data given in the slideshow. However, neither the traffic manager nor the dispatcher has control over scheduling decisions, which are the responsibility of the airline marketing departmenL

163 The following interactîbn occurs during a discussion of fix balancing between the traffic manager (T;.;) and dispatcher O^s-i) of the first dyad working the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3 fora description). The traffic manager introduces the proposed solution of the airline adjusting the arrival schedules of its flights into Minneapolis-St. Paul in order to avoid the hub airline's arrival pushes, and thus avoiding re-routing for fix balancing and the delays that appear to be causing the high fuel bum.

T3.i7a: Sometimes, you know, if you were to change your scheduled arrival time by just a few minutes, you might actually make it right in. By missing the [hub airline], uh, the push, the arrival push, through (?) traffic. Uh, I do know that when we choose to off-flow, we consider the runway configuration in Minneapolis, which runways they're using, and we typically would not take somebody out over Redwood Falls and bring them in from the southwest unless we're landing—At Minneapolis they use runways one-two [12] and three-zero [30] are the primary [runway}. They wouldn't take them out to Redwood Falls if they're landing runway t^e-zero [30]. Because it just makes it....much more of a penalty that way. D3.1: Yeah, right, I can see that.

Interestingly, the traffic manager does not inform the dispatcher as to what the peak arrival times are into Minneapolis-St. Paul, and therefore, the dispatcher really hasn't gained knowledge that will allow him to understand what are the times of day that his flights are likely to encounter delays and/or fix balancing.

5.3.7 Unique proposals

Following are two proposals, each of which were offered as an alternate solution by only one dyad. The first proposal is to utilize airports close to the airport where flights are currently scheduled to arrive and depart in order to alleviate congestion. The second proposal is one that is perhaps more conceptually complex and involves the ability to dynamically redesign the airspace to adjust to the demands of traffic.

164

■ j i i -■ 5.3.7.1 Utiliz& other close-in airports

A solution that was proposed only by the dyad working the Chicago to Boston scenario (refer to Section 5.2A for a description) involves using other airports that are close to Boston as the origin and destination of flights rather than the busier inain airport^^The Boston, airport experiences diminished runway capacity quite often due to weather and winds, and with fewer operating runways, arrival rates are reduced, andjn route delays are encountered. The following conversation between the traffic manàgérCT-R) and the dispatcher (D 4.1) illustrates a unique : . % > proposal as a way of redûiÜhg the volume of air traffic in the Boston airspace and, in turn, reducing delays encountered at the Boston airport.

T4.i23b: You know, if you want, ...let’s see, in fact you do run O’Hare to Manchester. D4.t23b: Yeah. T4.i23c: I think it’s like 12:30[flightJ that comes in chat way. Manchester, there’s rarely a delay. Now I hate to take anything away from Boston, but supposedly Manchester and Providence have off-loaded many passengers, but Boston says they are keeping the same number of passengers, so it’s just an increase in demand, you know countrywide, in air travel which is good. Di.t24a: Yeah. I know we have had on occasion when your delays were because of weather or whatever were excessive, we’ve set airplanes up to go to Providence and bus people. T4.t24a: Absolutely. D4.(24b: I mean that is something we can do in the late evening where we’re not having to pick up a load of people, and then we can ferry the airplanes over the next day or at a time where we can do it, and that we have done on several occasions. It’s not a good thing to do but it does get people, when you are looking at a two, three, or four hour delays sometimes under real adverse conditions, and you can get a bus, or two buses a day, when you are talking 48-50 people a bus, you've got to really think about it, as to whether that’s a good option or not. But if, in effect, you can land at Providence without a delay or anything, put the people on a bus, and what is it, about an hour—an hour and half? T4.i24b: No, not even. D4.t24c: So, and have them in Boston in effect two hours before they would have gotten there, it’s not a bad deal probably. It does cost money, but— T4.125: Now do you have routine flights into Providence? 04.(2 5 : We norinally do. We have Providence/Chicago. That’s about the only ones we normally have. T^(26: I mean, Manchester is really about the same distance. Pin not even sure if it might not even be a little shorter trip mto— 04.(26: The only thing with Providence is we have people there. Ground Support. 165 / m i m :: ^ ' •

11(27: You dou’t have grbunc^supporrstaffiu Manchester? 04.(2 7 : No. Nobody. ^ 14.(28 : Okay. So you’ve contracted our. 04.(2 8 : Yeak [The commuter airlme] might have somebody there. But when you start dealing operationally with an outside or contractor, somebody you called on the phone and say “Hey we’ve got an airplane with 140 people that’s going to be landing there In 20 minutes, can you deal with that, get them off the airplane and find buses?” That’s the hard thing to do. And In effect you may not be doing the best thing for that passenger. Where Is we can put them Into [one of our] stations, whether it be [the commuter ahllnel or [our airline’s] people, because they have access to certain things on a dally basis, whether It be ground transportation. They know what they can handle passenger-wise. 14.(29 : Yeah. I mean, I see when you are that close, ground transportation Is the way to go. 04.(2 9 : Providing you are not Into a blizzard or something like thaL T4.(30b: Yeah. You know, the other option areas, you know you have It already at Providence, but Manchester you know eventually staffing the facility, or Pease, I don’t know If you are familiar with Pease at all? D4.(30b: No. l4.(30c: But that was an Air Force Base, and that Is just due north of Boston. You can see the screen, let me Just move over to Pease. That’s PSM. D4.(30c: Yeah, I see It. T4.(30d: That Is right on 1-95 that goes directly to Boston. And Pease Is an old Air Force base and they are landing all sorts of Jets In there. You know that [another airline] Is flymg out of there. D4.(30d: Oh, are they? l4.[30e: There are a few other airlines that are flying In there, and It’s a huge facility with huge runways, but it’s not utilized. 04.(3 la: Okay, now I can’t answer this because we, well [the commuter airline]’s a part of [our parent organization] and stuff, but I don’t deal directly with them. Does [the commuter airline] have anything Into Manchester? I’m not that aware of It, but not to say— 14.(3 1: Tm not sure off hand. L’d have to look Into IL 04.(3 lb: Cause I know we’ve used Bangor as an alternate when we’ve had to. It’s not a good deal but they are more than able to handle us up there. 14.(32: Absolutely. I mean Bangor Is a similar area as Pease. It’s an old Air Force base with huge runways. 04.(32: That’s correct. Di fact, several people here were stationed there are one point 14.(33: Maybe that’s why they prefer to send them up that way, familiar territory. 04.(33: Well you know. In all honesty, sotnetimes when we’ve had diversions to Hartford or to Providence for a right landing Boston, the ones that went to Bangor got In faster....out of Bangor into Boston faster than the guys at Bradley ®r at Providence.

So at this point, the traffic manager has been exploring with the dispatcher what other airports within the Boston Center airspace the air carrier flies. He has

156 shared knowledge of some airpîÉts close to Boston, that are currently being used by other airlines. Up to this point, the traffic manager seems to be setting the stage for the solution he proposes a littie further on in the interaction. After exploring other solutions to the problems identified in the scenario, the traffic manager again champions the proposed solution of using other airports near Boston.

T4.i92: Wetlands and noise, and so on, like you said. I truly think you guys should just forget about further developing Boston, and spread out. LDceyousaid, in the Bangor area, Manchester. Manchester is a very good one right now, no delays at all. You’ll get in and out of there with, you know— Di.i93 : r m going to go look at their airport here when I get off the phone and see what they’ve got up there. Maybe Til make a suggestion. T4.i93 : Well, you know. Til tell you this. Fm sure that the big officials are aware of this, but right now, you know, it’s a pretty basic airport but they are doing a runway extension on both of their runways, and in about two years the place is going to be phenomenal. You’re going to be able to land any type of aircraft there, and it’s, you know, even when you think of New Hampshire, believe me, this place is a regular metropolis. I mean, it’s all suburbia. It’s really not the sticks because we are right outside of Boston. We are like Long Island In the old days, where it’s all spreading out from Boston and going all the way up. Dt[94: You know what, I would venture to say that if you had a good portion of our people going to Boston, it may very well head up that way. But because of no service, non-stop service from Chicago or the West Coast for instance, might make a viable deal and we could probably put enough people in the airplane to make it profitable. T4.i94 : I’m telling you, it’s just getting the word out. You know, Manchester [is] really without traffic, it’s just 50 minutes to downtown Boston. So it’s really not that far. D4.[9 5 : What is it from the airport now to downtown, roughly, with traffic? Without traffic? It’s probably only, what 20 minutes, 30 minutes? T4.i95 : What do you mean, from Manchester to— D^.;96: No, from Logan to downtown? T4.i96r Oh yeah, 15-20 minutes.

[utterances omitted]

T^.[ll6 : ....Where else do you have crews in the northeast area? I mean, you say you have them in Providence— D4.1117: Now, we have crews in Boston, depending on what type airplane too. That’s very specific. New York, Washington, Miami— T4.tlL7 : Okay, I mean, you don’t have anything in say Syracuse? D4.tI18a: No, no crews there. What crews go in there, take an airplane in, bring it out, or go in spend overnight, and another crew take it out, or the whole airplane and crew spends the night. There’s no crews per say there. TltllSa: Right. Okay. 167

•a' . D4.t 118b: But we used to have some at Buffalo 30-years ago, but that’s a long time ago. No more. We used to have some at Nashville. No more. T4.1118b: No more. So you really are trying to centralize things a little bit more. D4.1119: Yeah. And then [it’s a] very specific type of crew we have at certain places. T4.1l 19: Well, I mean, what about having flexible crews that can handle the Boston area, between you know Providence to Manchester, Boston, Pease, I mean it’s all within an hour. D4.[ 120: Well, if we had a crewr problem in Boston and we had to get a crew to Pease or Manchester or Bradley, yeah, we could do that with a Boston crew. We’d have to set up, since they are Boston based, we’d probably have to set up a taxicab or something to get them to where the airplane is. T4.1120: Yeah, but it’s worth it. D4.1121: Yeah, oh yeah. We’ ve done that. We’ve had crews go illegal at Providence for instance, and gotten a crew out of Boston down there to pickup the airplane and take it out. To take the people ouL I mean, that’s been done. T4.1121: Okay. Well that’s good. D4.[122: 1 mean it’s just a matter of whether we have the crews. There are certain times of the month, and it’s becoming more frequent to be honest, where we don’t have crews because of either, you know whatever reason, some of them are in training and whatever.

The discussion surrounding this alternative solution provided the opportunity for unique domain knowledge to be exchanged between the dyad partners. The traffic manager learned about what are the constraints for determining into what airports an air carrier can fly (e.g., passenger good will, ground support crews, working with contractors) and the dispatcher gained knowledge about possible alternatives that his airline could use for destination and origination airports rather than continuing to fly only into Boston and continually incurring delays. This interaction was sufficiendy interesting to the dispatcher, that at one point he stated, “When E get off the phone [with you] and see what they’ve [Manchester airport] got up there, maybe I’ll make a suggestion” 0 ^4.t9 3 ).

53,7.2 Dynamic redesign of the airspace

In the following exchange the dispatcher (Pj-t) working the Dallas-Ft. Worth to Minneapolis scenario (refer to Section S.2.3 for a description) suggests that rather than having fixed sectors and arrival fixes, a process that would allow for more

168 •i'i 4 flexibility fora dynamic redesign o f the airspace might serve to eliminate some of the delays and re-routings thaLhel:eQ§uin the scenario.

D3.18 O: The other thing that we really need in the real world situation is just a much more flexible system of {pause} you know» you’vegot (pause} how many arrival comer posts do you have for Minneapolis? T3.1.8 O: Ah, one, two, three, four primary. Dj.18 1: Yeah. And that’s basically what DFW has, and I think Chicago has the same thing. But if you put a thimderstorm over one of those comer posts, you wind up shutting off, at least in DEW where Tm most familiar with it. If there’s a thunderstorm over the comer post, they shut off that whole comer post and move all the traffic to the other comer posts, and it would seem like you could just designate a new spot 15 miles east or west of that comer post where it’s weather free, instead of moving a guy 60 miles to the next comer post. But that would require a lot of new procedures and certainly a —something like GPS navigation to do it. Tj.i8 L: Either that, or I suppose they could chart more. It might be something for the controllers, more for the big controllers to learn and get used to, but it’s probably do-able.

The traffic manager (T3.1) agrees with the dispatcher that dynamically designating a new comerpost when weather is impacting the original fix might be a solution. However, the dispatcher then suggests dynamically moving sectors, and the traffic manager is hesitant to endorse this idea.

D].i82: Yeah, and that would also probably put them right in the face of a bunch of departures, but, I mean there should be a way of dynamically moving around some of those sectors too, so that you can say “This weather is here so we’re going to take this traffic and bring it in on this...through this.’’ or actually redesign the sectors on a dynamic basis, instead of having the same guy work the same piece of air all the time. I mean this is major project I’m talking here. But (pause}— T3.182 : Yeah. T m thinking the abili^ to make dynamic sector boundaries right now, is not there. 03.(83 : No, I’m Slue its noL But I think that’s something that would be beneficial. Don’t you? Ordo you? T3.183 : Yeah, somewhat. 03.(84 : I mean ifyou could/pause/ if one of yourcomerposts is closed, rather than moving a guy all the way to another comer post, if you could Just move him a few miles instead of moving him all the way over to Mason City from Redwood Falls or something. And when there’s thunderstorms east of DFW, they wind up, you know they’ve got four departure routes to the east, and when they are all shut off it Just gets everything all bottled up. Get some enormous takeoff delays. Maybe 169 they could send them to the northeast Instead o f[pause). But they can't send them to the northeast because that’s aa arrival route.

[utterances omitted]

Tj.i89: And you know, I think the further away ftom the airport, they do more of that. I think the sectors are much more dynamic. They can run airplanes on the north part of the sector, on the south side of the sector. But you’re right, once you get Into the terminal you've got the four comer posts and you don’t run traffic right next to the comer posts. Maybe that Is something that they could do to devise a better plan. D3.19 O: Yeah. It’s just real rigid.

These two unique proposals are Interesting because they provide the dyad partners an opportunity to thlnk “out of the box.” Exploring such alternates Increases the possibility that new^approaches will be considered.

5.3.8 Tools Used by ATM System Actors

Discussions about various tools that are used In the course of doing their work arose during the dyads’ problem solving activities. The tools that were discussed Include Flight Progress Strips, Traffic Situation Display (TSD) or Aircraft Situation Display (ASD), Center TRACON Automation System (CTAS), Monitor Alert, and Flight Status Monitor (FSM). The Importance of exchanging knowledge about tools that enable them to do their work more effectively becomes clear In the following conversations.

5.3.8.1 Flight Progress Strips

The Flight Progress Strip (or strip) provides, on a paper strip, a representation of the behavior of a single aircraft. Printed text on the paper strip includes the aircraft's callsign, flight level, speed, estimated time of arrival at the next waypoint, and the filed flight plan. In addition, strips possess a number of other properties: they capture, through handwritten annotations, some of the history of

170 ' 'v vS*:-?^Oÿf w :-riv .-..V/ii.;

communications with the aircraft'and can even indicate (through pen color) which controller was responsible forwhich annotation. In the following conve^tidn the traffic manager (Ti.j is prompted (by the dispatcher (Di.i) suggesting that he could file a flight plan closer to the time of departure) to share information about how Flight Progress Strips are used.

T|.:15: Our strips in the towers, at least down here in Atlanta, print 35 minutes prior to proposed time. So once the tower gets that strip, it gets very cumbersome to get an amending clearance to the PDC [Pre-Departure Clearance], to the aircrew, or have a tower cap read a full route clearance. So, if yon' re looking at an hour before the proposed time, you know that’s a good time fiame for us. We’re re­ routing airplanes, we try our best to do it before the strip is printed in the tower. D(.2l6 : And you say you get the strip 35 minutes priorat the tower? Tt.ilô Right. The tower, at least down here in Atlanta Center, we generate the strips 35 minutes prior to the proposed time, and that's just whatever you all file. Sol can amend...flight plans whenever I need to, and it’s very convenient if the new strip... the only strip that the tower sees is the one with the new route on it. And either it goes out through. PDC or we can issue a full (?) clearance. DuL?: Right. Well, when do you typically get them? About an hour before departure time in the Center? Tt.zLT: No. Well, the Center won’t get the strip either. But in Traffic Management, I can go into the host computer, and as soon as you file it—you push the button there because you all are on line with us—you may file two hours prior. It’s sitting in the host and it’s dormanL And I can amend it as soon as it comes in. It may be two hours before, but if we are running reroutes for Chicago all day for Atlanta departures, we will amend them an hour and a half ahead of time. If we know we’re doing this for most of the day, taking everybody over National, (?), St. Louis, (?). As soon as that’s filed, we amend it. D(.%18: So, how do you notify the carriers ifyou amend them? Is it when the flight calls for its release, orfortake-officlearance, or for clearance, that he gets the amendment? T1.2I8 : Well, what they do in Atlanta is (?) flight planning (?) out of PDC, which is Pre- Departure Clearance. They’re automated through (?) and they have to read him a full route clearance, ’cause once P m In the flight plan it will not go through the PDC system. We do have, and I think they all are on board with some of our slot programs now, where we can actually plug in a second route that crews are already dispatched and a possibility you’ll get ’em. Say out of Atlanta westbound over (?) and Memphis, going up to Chicago, St. Louis, that way. And that’s a phone call to you all for you all to, for AATC people and [your airline]-to let them know that Atlanta’s using a SWAP program. And that’s something that we initiate.

171 With this interaction, th&dispatcher learned how Flight Progress Strips are used by controllers and traffic management. Many questions are answered for the dispatcher, which include the following:

• The time ahead of the proposed time that is best for the flight to be filed (Ti-ilS: “...an hour before the proposed time [is] a good time for us”)

• When the Strip is generated in the tower ( T “...we generate the strips 35 minutes prior to the proposed time”)

• When the Center gets the Strips (Ti.?!?: “...the Center won’t get the Strip...! can go to the host computer [and get it] as soon as you file it”)

• When it can be amended (Ti.ilT: “I can amend it as soon as it comes in....”)

• What events determine when notification of a re-route is initiated by Traffic Management CTuilS: “...that’s a phone call to you...to let [you] know that Atlanta’s using a SWAP program. And that’s something we initiate.”)

Flight amendments and proactive flight planning. The following exchange between one of the dyads working the Dallas-Ft. Worth to Minneapolis-St. Paul scenario (refer to Section 5.2.3 for a description) highlights an important gap in dispatcher knowledge as to how dispatchers’ actions, when filing flight plans, impact the actions of the controllers via the strips.

03.(29: ....our dispatchers are usually pret^ proactive in fifing flight plans around the weather, and sometimes it drives ATC nuts because there’s ... almost [all] city pairs have preferential routes, and they ask us to stay on their pref routes, and according to FARs when there is known areas of thunderstorms, we’re required to flight plan around them. So we’ll go ahead and file the flight plan around the weather, and then the guys m there handling the strips and departure strips in the tower go nuts, because we keep re-filing routes all of the tune. And they get one strip after another, and they get confused as to which, way we really want this guy to go. You know, they’ll get two or three or four strips for the same flight. And I guess those 172 things don’t have time stamps on them either, so you don’t know which one is the current one. T3.[29a: ....But I know that they do have an amendment number. D3.1: Okay. T3.i29b: ....anytime there’s an amendment to a flight plan {pause} you know, if you file a whole new flight plan... you know, we might not Imow. If there’s an amended flight plan, it tells you the amendment number and you always go with the most recent amendment number....

The traffic manager (T 3.1) shares his knowledge about amendment numbers on the flight strip and that re-filing a new flight plan may not be viewed as an amendment and thus, the flight strip generated by the new flight plan would not show up as an amendment but as a newly filed flight.

DuSO: What’s the difference between filing a new flight plan and an amended flight plan? It’s an amendment. Is that something that ATC does, or is that something that the airline does? T3.13O: Typically, I just amend thenu Dj.i31: Okay. Well, we put out a new flight plan, and I don’t know if it comes out with any kind of an amendment number on it, or if it’s Just another strip that looks just like the strip before it with a different route. T].|31: So you find that the tower controllers don’t know which route a guy’s supposed to goon? Dj.i32: That’s what they tell us.

This interaction has revealed some important knowledge for the dispatcher (D3.1) as he now realizes that there is a difference between amending a flight and re­ filing a new flight plan. He now understands why the controllers at the Center have had difficulty understanding what the dispatcher intends when they receive multiple strips for flights with the same flight plans.

Diversions. The following exchange between the dyad working the Chicago to Boston scenario (refer to Section 5.2.4 for a description) gives the dispatcher an opportunity to understand that information he believed was on the flight strip, and therefore, information the traffic manager would have access to, does not appear on the strip. That information is whether a flight is a returning diversion.

173 -r's': ■-

: li ►.

T4.j38: ....So if you go in and yoii divert, this guy refuels, he’s ready to go, the point is we need to know conununicâtion wise that this guy is a divert, otherwise we wouldn’t know. D4.i39 a: We have an entry that’smade on the, that should come up on the strip if I’m not mistaken, to who goes out. And there is also a message that our ATC person here, when he sends out the thing to Central Flow— T<.i39a: Okay. D4.i39 b: It lists the diversions. T4.i39 b: It does? D4.i39 c: Yes. Now I don’t know if you get that, but Central Flow gets it.

[utterances omitted]

Tw4I: You know what I’m going to look for the next time that we are holding. I’m going to look into seeing if it is on the strips. Because I haven’t seen them. The only way that we’ve been made aware of it is when we get the phone call saying “Look this guy’s a diversion, send him in.’’ Or if we do poll the towers, we do put out messages now and then, saying “Look, if you have a divert, let us know.” D4.i42: There is an entry that the dispatcher makes when he sends the flight plan, on that like Bradley to Boston say, that he has an entry he can make that’s supposed to trigger a message on the strip that he is a diverted flight. Now, that’s what they are supposed to do. On occasion that is probably sent without it. In which case you wouldn’t have any idea. Other than the fact that I would know because we normally don’ t serve Hartford to Boston. That could happen, and I have not really done any checking on that other than the fact that we do send a message from here, one of the ATC coordinators who works in that position, can send a message to central flow even requesting the order in return. In other words, like I through whatever. Priority as hiras with our aspect in mind. If it could be worked out with you guys. Ti.[42: Yeah. Absolutely. I guess that’s the key. Something is not coming across. To just ensure that this is going the whole way.

This section has illustrated the lack of knowledge that dispatchers have with respect to how their actions in filing a flight plan impact those who use the Strips in managing air traffic. The dispatchers also lack knowledge as to what data that they provide in their flight plan is represented on the Strip. Acting without the relevant knowledge can create gaps between what the dispatcher intends in a flight plan and what the traffîc manager, using data on the Strip as evidence, thinks is intended.

174 5J.8.2TSD/ASD

The Aircraft Situatioa Display (ASD) is a strategic tool used to plan and monitor specific traffic management actions. It allows air traffic facilities to observe aircraft system-wide on a single display, thereby increasing lead time for planning and implementing traffic management actions. In the following interaction between one of the dyads working the Dallas-FL Worth to Atlanta scenario (refer to Section 52.2 for a description), the traffic manager (T 2.2) asks the dispatcher whether airline dispatchers use Traffic Situation

Displays (TSDs). The dispatcher (D 3.2) explains what is used at the various positions within the Dispatch controLroomJ

T2.336: At a dispatcher level, do you guys use the TSDs? D2.i37: Yeah. Well, we call them ASD. Here at American, each dispatcher position has an ASD, but it’s Just for their flight at their desk. Now the TSD does live in the ATC Coordinator position, which of course we can get up and go over to and look at. So yeah, the information is available. T2.:37: Yeah. Well actually the only difference between TSD and ASD is if you can get the same information so that you can do it, it’s easier to access. D2.i38: Yeah. And the TSD I think, it shows you everybody, so you can see what’s really going on. T2.238 : Right. And with the TSD, you can actually select several screens and toggle back and forth, like if you’re working Atlanta to Ft. Worth, Atlanta to Oklahoma, Atlanta to Kansas City, Atlanta to Houston, you can have a screen for each one of those and toggle, so you can have one up at a time. D2.239 : Yeah. That must be nice when you know you just got to (?) change the departure route, and can pull up a list I guess of just those flights. T2.239 : Right That makes it easier. I think that, like you said, communication is something ....that’s getting a lot better. The use of TSD’s, ASD’s in both places, helps everybody see what’s going on, and uh, sure helps you folks out there.

S.3.8.3 CTAS

The Center TRACON Automation System (CTAS) provides automation tools for planning and controlling arrival air traffic, and it generates air traffic advisories designed to increase fiiel efficiency, reduce delays, and provide automation assistance to air traffic controllers. Di the following conversation, the dyad working the Dallas-

175 Ft Worth tcMnrieàpolîs-St Paul scenario (^féç to Section 5.2.3 for a description) discusses the use of CTAStforlSx: balancihg.

D 3.i3 2 : . . . JD o you use CTAStfbc^ba|ancmg? T3.233: We're ^st,uh,w e'ceshad6^g it right now. The prototype two. E think some of our guys have been, down to Dallas/Ft. Worth Center to—they have the NASA version, the original [pause} and the one we're getting is like level two or the next generation of it. And the hardware and software is all there, and now it's a process of shadowing it to just insure compatibility and seeing any quirks and stuff like that. But I think our IDU—initial daily use—is like June 27* they are scheduled for, and then I think we'll use both systems, the old metering system until like October or November, and then we are just going to go straight (?). D].:33: Again, since they put that in here, in ouroffice a couple of years ago, I very rarely call the TM—your guys at Ft. Worth Center—anymore to rind our where our flints are, and you know in the sequence or delays, or things like that. So I'm sure it's really decreased the amount of calls. It's, uh, well, we have a repeater in our dispatch office from the Ft. Worth Center. We don't have any active. It's just passive, but Just without a (?). It answers a lot of questions about, you know, what fixes flights are coming over and how many minutes of delay they’re going to get. Tj.234: That will be nice. Because you know when I fix balance, typically it's using Northwest and the amount coming here, the volume—and I'll usually call them just to let them know, “Hey, I'm going to take these two guys.” And we do it like to Portland, Seattle, Spokane, Vancouver, and a lot of times we are filing to Redwood, and we'll take them up to Fargo to fix balance, and we'll do that. But yeah, with what you're talking about—I haven't gotten that familiar yet with CTAS, in the way of training. People down there, are they pretty happy with it? D j .2 3 4 : I think s o . I haven't really heard them complain about it Part of our recurrent training last year was to go over to the Ft Worth Center and, you know, it seems to be a tool that they use quite often. It’s not like they were sitting here with a piece of chalk—and they should take it to the scrap heap—but it just, uh, it seems like they recognize that it will keep constant pressure on the fixes and on the finals, and it seems to be serving its purpose. I really haven't heard any negative comments about CTAS at all. I'm not sure if they use it to its full capability, but we really don't take that many delays here....

53.8.4 Monitor Alert

The Monitor Alert function assists the Traffic Management Coordinator (TMC) in the effective utilization of the airspace. Using Enhanced Traffic Management System (ETMS) data. Monitor Alert compares traffic demands with Monitor Alert Parameters (MAP) and. alerts the TMC that sector/airport efficiency may be degraded. The Monitor Alert alerts yellow for proposals and red for active

175 aircraft exceeding the MAP values. Alerts then prompt the TMC to adjust traffic on a proactive basis. The following interaction between partners in the Dallas-Ft. Worth to Atlanta scenario (refer to 5iecnon 5.2.2 for a description) is about yellow and red alerts occurring in a sector. The dispatcher initiates the topic, and the traffic manager fills in the dispatcher’s gap in knowledge.

D2.226: How far out does your computer project if the Center is going yellow or red? I mean a sector, excuse me. TmSô: You mean time wise? Dt227a: Yeah, I mean it’s looking like the [pause} let me see if I can phrase this right. It doesn’t actually (pause) if it’s yellow, isn’t that in so many minutes from now that sector is going to be yellow, or is it once it’s yellow it has already been (?) too many airplanes in there. T^lTa: We’ll get a yellow alert as far in as we set the parameters, but that’s based on proposed aircraft. We usually set it here an hour and a half ahead of time, but if it’s, uh {pause} yellow an hour and a half from now, (?) and we don’t pay a whole lot of attention until 30-45 minutes because so many things change here. Dî.227b: Sure. Tt227b: They change altitude. They change routes; uh [pause} there’s too many variables in there. What we do is sector off-load some aircraft, and (pause) most of them in a situation move an airplane, like for example, from Rome to Meridian. We’re looking at aircraft coming from out west, say the West Coast centers, we’ll pull an aircraft in the city of Albuquerque and stuff, and move them down because that’s saving the carrier more fuel instead of having them go over Portsmith and all the way down two states south and cross. D2-228 : Yeah. When you do something like that, do you have to coordinate that through Central Flow and get all the other centers around on? T2.228 : Yeah. We’re going to have...every Center that that aircraft wOI now transition through is different than the original was, and there’s certain times of day we’ll oh [pause) 4 o’clock Eastern Time, which I guess is five your time—we do a lot of it, especially coming out of the west. D2.229 : Okay. So is that [pause) is that pretty much a daily occurrence? Tt229: On that time frame, yes it is.

53.8.5 FSM

The Flight Status Monitor (FS!VO allows the users and providers in the National Airspace System (NAS) to build a common situation awareness of the constraints that exist in the airspace at any given time. This real-time tool allows for

177 collaborative decisions to be made regarding the best way to keep traffic moving in the event of a ground delay program. Refer to Section 5.3.3.2 for the conversation on how the dispatcher of the first dyad working the Chicago to Atlanta scenario suggests using FSM in helping to make better decisions about using ground delays (turn Di.tl7 to turn D n l8 and turn Dt.i32 to turn Di.i34). The dispatcher discusses how FSM could be used to enable a preview of the airspace for a given period of time. That is, if it looks like there will be more arrivals than can be handled within, for example a 15-minute time period, some flights could be delayed on the ground at their originating airport. This then would put those delayed flights into another 15-minute period when traffic might not be as heavy. The dispatcher emphasizes that this tool allows for the dispatcher and traffic manager to collaborate on ground delay decisions because both are able to be looking at the same thing at the same time as they use FSM.

5.3.9 Summary

Solutions Proposed. The results of this investigation of the interactions between dyad partners document a wide range of potential solutions to deal with air traffic congestion and weather constraints. These solutions include the following:

• Changing arrival fixes in order to balance the traffic flows between fixes

Delaying aircraft on the ground at the originating airport as a way of minimizing en route delays

• Lnpro ving commuriicatioh. and collaboration between the different organizations im th e r^ Traffic Management (ATM) System (e.g., AOC dispatchers, ARTOEUraffic managers, and ATCSCC personnel) to arrive at more effective d isio n s

• Routing aircraft on alternate routes to avoid weather events or traffic congestion, 178 • Separating orLAADRing arrivals and departures to reduce controller workload in affected sectors and in effect reducing delays

• Adjusting arrival Schedules to avoid peak arrival and departure pushes at the destination airport

• Utilizing airports close to the currently scheduled destination airport to reduce traffic congestion and resulting delays

• Increasing the flexibility of the airspace by dynamically redesigning it (e.g., moving arrival fixes when weather is impacting the airspace; sector redesign to reduce delays due to controller workload).

Knowledge Shared. These Endings also provide insights into when each solution is applicable from both FAA Traffic Management and AOC perspectives. For example, the solution to impose a ground delay at the originating airport may be seen by traffic managers as a way to space traffic more effectively, reduce controller workload, and reduce the likelihood of airborne holding at the arrival fixes. However, ACCs may feel that having ground delays imposed on their flights would impose a greater negative impact on performance than if they encounter airborne holding. Table 5.2 categorizes by dyad the solutions that were proposed as the dyads worked on their task. In the course of generating these solutions, the dyad partners shared rich domain knowledge as they worked to build a common ground. This shared knowledge includes the following categories.

• Strategies traffic managers use for handling airspace congestion. These strategies include:

■ Balancing arrival fixes

■ Placing miles-in-trail restrictions on aircraft

179 • Re-routing aircraft to avoid congested airspace, to reduce congestion, or to avoid a weather event

• Vectoring aircraft as a means of delaying them from entering congested airspace

■ Separating aircraft by altitude to reduce sector controller workload

• Constraints with which traffic managers must cope with include:

■ Configuration of the arrival airport, which determines aircraft arrival routes

• Airport arrival rate

• En route traffic crossing over arrival and departure traffic

• Priorities and consents the airline dispatchers must consider include the following: %

• Strategies pflots use in order to avoid getting into a minimum fuel situation (e.g., diverting to an alternate airport);

■ Federal Aviation Regulations (FARs);

■ Determining which strategies are most efficient for reducing delay due to congested airspace (e.g., ground delay versus airborne holding);

■ Satisfying intra-orgam'zational differences as they pertain to on-time performance and fuel usage goals.

Table 5.3 illustrates by dyad the classes of knowledge the dyad partners shared. These classes of knowledge contain various categories within them, and it is at the level of these categories that the knowledge is shared.

Current Problem. A problem that exists currently within the Air Traffic Management system is the impact that changing the locus of control has on the decision-making process when the requisite knowledge does not reside with the 180 decision maker. The concern becomes one of identi^ng what knowledge is needed, who has that knowledge, ^ d hbw'does the decision maker gain access to it. A context that easily iUusü^tes,&f ^eirim a is pre-flight planning. Traditionally, FAA traffic managers hadcontr\)tover^detenhining what routes were filed by the airlines. Currently, due to changes in thSiï ^ increased control of route planning has been given to the AOC dispatched ^[^ever, access to the data and knowledge necessary to evaluate alternative routes did not co-occur with that transfer of control. A concrete example of this situation is provided in the conversations by one of the dyads working the Chicago to Atlanta scenario (See Section 5.3 AA for the conversation and discussion). The dispatcher in this dyad thought that one solution to the problem of airborne holding would be to file some of the flights firom Chicago to Atlanta to another arrival fix. It was only when the trafKc manager shared his knowledge about other Atlanta arrival and departure traffic and the en route traffic crossing the Atlanta airspace for the timeframe in question that the dispatcher realized that this solution was not a viable one. Not only would filing some of those flights over another fix result in no net gain (and possibly more delay) to the dispatcher’s flights, but the probability of negatively affecting other arrival traffic into Atlanta, as well as departure and crossing traffic would be almost assured (according to the traffic manager).

Different Preferences. Another finding of the present study is that there are large individual differences in preferences expressed by individual dispatchers. These varying preferences make it difficult for the traffic managers to decide how to best incorporate an airline’s priorities and constraints when making decisions. The conversations between the dyad partners are presented in .Sigcfrbn 5.4.3. These are rich examples of the different preferences that specific dispatchers have on whether to delay on the ground at the originatfng airport or encounter airborne holding at the arrival airport. It was only by comparing the conversations of the different dyads during the analysis of this research that an underlying consistency between the dispatchers’ 181 preferences was discovered. It appears that the commoa denominator was weather. One dispatcher (Di.i) situated, his preferences of ground delay over airborne holding within the assumption of clear weather conditions. Another dispatcher (D3.1), when discussing his preference for airborne holding, assumed thunderstorm activity. He suggested that because of the uncertainty of such weather events (i.e., it is unknown how quickly they are moving and where they will be located at any given time), he prefers to take a chance of an aircraft encountering airborne holding over the certainty of its delay if held on the ground at the originating airport. What is suggested by these examples is that the knowledge necessary to make a decision does not likely reside with individual agents (e.g., individual airline dispatchers) within this complex, interdependent system. Rather, the complexity of locating relevant knowledge with the locus of control may require a process that provides the agents within the Air Traffic Management System an understanding of the roles, responsibilities, goals, constraints and procedures of the other parties with whom they interact. Finally, these findings indicate that the conversations between the dyad parmers resulted in a rich exchange of knowledge. However, the partners in every dyad failed to reach the final phase of the problem-solving task, i.e., selecting the best alternative solution. The implications and causes for this failure are discussed in the Conclusions chapter of this paper.

182 Arrival Ground improve Alternate Altitude Arrival Proposed Fix Delays Real-Time Routing Separation Schedules Solutions Changes Communi­ /LAADR Adjustment Ofieredby cation Only One Dyad

Dyad l-l XXX Scenario L Chicago to Atlanta Dyad 1-2 X X XX Plan Closer to Time of Departure Scenario 2 Dyad 2-1 X Dallas- Ft Worth Dyad 2-2 X to Atlanta

Scenario 3 Dynamic Dallas- Dyad 3-1 X XXX Redesign of Airspace Ft Worth to Minneapolis- Dyad 3-2 X Better St. Paul Training for Controllers Scenario 4 Additional Runways; Chicago to Dyad 4-1 XX Boston Utilize Close-in Airports Scenario 5 Change Fuel Dallas- Dyad 5-1 X Metric Computation Ft Worth Process to Newark Table 5.2. Alternative solutions proposed by dyad within each scenario.

183 Classes of Knowledge Categories of Knowledge Scenario 1 Scenario 2 Scenario 3 Scenario Scenario 4 5 Dyad 1 Dyad 2 Dyad 1 Dyad 2 Dyad 1 Dyad 2 Dyad 1 Dyad 1 5,3,2 Airline/Cemcr Collaboration V V V V V V 5,3,3 Air Traffic Management Restricted airspace Considerations Fix-balancing V V Miles-in-trail restrictions V V V 5,3,4 Arrival Flow Management strategics for handling Alternate routing V < V congestion Delay vectoring V Altitude separation V V 5,3,5 Arrival Flow Managemeiil Runway configuration ^ V V Cottstraints Arrival rate/ crossing traffic Arrival schedules V V ' . Pilot strategics V V V Fuel consumption V ' , '* 5,3,6 Airline Considerations T- Federal Aviation Regulations V Ground delays vs, airborne holding V Flight Scheduling VV Airline intra-organizaiional V differences in priorities 5,3.7 Unifiue Proposals Utilize other close-in airports V Dynamic redesign of the airspace V 5,3,8 Tools Flight Progress Strips ^ l V V Traffic Situation Display (TSD) V Center TRACON Automation System (CTAS) Monitor Alert V Flight Schedule Monitor (FSM) Table 5,3, Knowledge shared between dyad partners during their discussions, 184 5.4 Communication and Collaboration

5Ad Introduction/"'^

The previous section emphasized the importance of the dissemination of knowledge among the team of practitioners who manage the National Airspace System (NAS). The study participants used this knowledge sharing as they pursued the task goal of identifying alternative solutions to the problem(s) they identified in their respective scenarios. This section looks at other important aspects of communication that lead to successful collaboration. If one views verbal and nonverbal communication as a system of representations, it becomes necessary to place them in relation to other representations, both internal (e.g., schema, mental model) and external (e.g., shared graphical display), within the ongoing conversational activity occurring between the dyad partners. It is only in reference to this larger context of representations that the verbal and nonverbal behavior can make sense. This section examines the role that cognitive artifacts play in enabling the dyad to build a common ground as they share perspectives and establish mutual understanding. How the participants use stories and analogies to aid them in their understanding of the current situation and to allow them to provide explanations to their partner is investigated. Also provided here are descriptive accounts of the consequences of incomplete situation assessments and how difierent dyads manage their problem solving in light of missing data that might be critical to problem definition and alternative-solutions generation.

185 - 1"/. 7 4 ï-L.r'./r

5.4.2 The Role o f Cognitive Artifacts: Building Shared Perspectives through Reference

Shared space literally adds a new dimension to conversationr a dimension embracing symbolic representation, manipulation, and memory....It takes shared space to create shared understanding. Schrage, 1990, p. 98

5.4.2.1 Introduction

People naturally communicate using the multiple modalities available to them. For example, when two people are physically co-located they are able to use spoken language, gestures, facial expressions, as well as non-linguistic sounds (e.g., laughs, coughs} to communicate with one another. They have available to them the - maximum bandwidth forcorrnnnriication, which allows them to maximize the efficiency of their intefactionjby taking advantage of the complementarity that exists between modalities fbrdiSerent aspects of the information to be exchanged (Bunt, 1998). These multi-modal characteristics of face-to-face human communication are what lead Clark and Marshall (1992) to state that the strongest evidence that people are prepared to accept for the existence of mutual knowledge is physical copresence. The role that visibility and copresence play in the establishment of common ground and mutual understanding has been investigated recently. Grosz (1981) found that when an expert and his apprentice engaged in a disassembly task without having a shared visual field, they encountered confusion about common referents. Grosz suggests that even when partners believe that they have established common ground, misunderstandings may arise because, in fact, that common ground does not exisL McCarthy, Miles, & Monk (1991) investigated participants engaged in a problem­ solving task. These participants communicated via text and did not have a shared visual space available to them. They experienced, difficulties in the grounding process, which led McCarthy et al. to put forth several hypotheses to explain them Endings. The authors suggest that the absence of spoken dialog among the 186

■. .ML K r participants resulted in having no shared memory to aid them in their task. They also postulate that the text-only communication did not afford the participants the advantages that deictic references (i.e., pointing) and the visibility of a partner's task­ relevant behavior can provide to conversation (see, for examples, Clark & Schaefer, 1989; Hughes, Randall, & Shapiro, 1992; Hutchins, 1990; Lyons, 1977). The present study represents an interesting variation to the notion of physical copresence that was discussc^mÜi&Cômmunicationwithin Teams section of Chapter , ; -..a*' 2. Since the conversational partners are not co-located, they do not have available to them all of the modalities that they would have if they were interacting face to face. For example, without the ability to see his partner, one cannot know at any particular instance in time where his partner is focusing attention. However, with the modalities of speech (via telephone) and gesturing (via telepointer within the shared display) available to them, the partners can inform one another regarding to what they are attending and referring. This section examines the role that the slideshow and the telepointer feature of NetMeeting as cognitive artifacts have on building shared perspectives. With these artifacts, the partners are able to share their unique knowledge, direct each other’s attention by referring, and move toward a mutuality of understanding. As a result they are able to establish a virtual copresence that strengthens the linguistic copresence enabled by the telephone artifact.

S.4.2.2 Physical copresence

Given that physical copresence provides the greatest opportunity for the establishment of mutual understanding and mutual knowledge (Clark & Marshall, 1992), providing a situation where collaborators are able to be physically co-present with each other and the referent appears to be a desirable component for establishing common ground. However, it often is not feasible or practical for the speaker and listener to be physically located together, and what is more ftequently occurring in organizations is distributed teams located in different sites as they work together. 187 Therefore, providing an environment where the referent is physically co-present with each of the partners at their distributed locations,^ and where each can interact with the referent and with one another through the referent may be as effective as physical copresence if it allows for a virtual and linguistic copresence between partners.

5.42.3 Linguistic copresence V»- n.- It is often the case in conversation that things that are referred to have been mentioned only in the current conversation between physically co-located conversational parmers, without the referent being physically present with them. Clark and Marshall (1981) refer to this as linguistic copresence, which includes all of the conversation up to and including the utterance currently being interpreted by the conversational partners. It is possible for linguistic copresence to exist even when the parmers are not physically co-located. A ubiquitous example of this is the telephone conversation. In this situation the only way to establish the reference of an expression is in relation to previous expressions, or to things in the world that are directly named or described.

S.4.2.4 Virtual copresence

By providing both the trafKc manager and dispatcher with a hands-free audio system (i.e., telephone with speaker) and a shared computerized artifact, a shared external representation, that allows them to be looking at the same thing while referring using deixis and proper nouns (i.e., the slideshow via NetMeeting), an environment is created that enables many of the benefrts of physical copresence, without requiring that the partners be physically co-located. This can be referred to as virtual copresence. Therefore, the shared cognitive display provides a common frame of reference and. allows the parmers to be informed where the other is looking or where to direct

IBS attention. This ability for joint reference aids them in effectively coordinating their conversations, in establishing mutual understanding, and enables a “shared mindset across the cooperating agents about the background field against which the agents can all recognize interesting conditions or behaviors” (Woods, 1991). The shared display also provides contextual cues to help reduce understanding costs (Clark and Brennan, 1991) that could be incurred if only linguistic copresence existed. The persistence of the information on the shared display modifies the communication constraints by reducing the cognitive load required for maintaining the context of interaction. (“Context” is something that is co-constructed by the partners of the interaction and includes the immediate preceding activity as well as larger environment in which it takes place (Drew & Heritage, 1992).) The slideshow allows for the interpretation of verbal utterances and acts as an external memory that retains the situational and communication context. This context is established at the cognitive level, and the mutual understanding of an utterance may rely on mutual visibility of data on the slide. The shared display, and the virtual copresence it enables, relaxes some constraints on communication, helping practitioners to build a shared representation of the problem and repair communication breakdowns. The following excerpts firom the collaborations between dyads, each consisting of a traffic manager and an airline dispatcher, provide examples of how the artifacts (i.e., the telephone that allows for linguistic copresence, and the shared display and telepointer that allow for virtual copresence) become part of the distributed cognitive system. These conversational episodes also demonstrate that even overt communication is often understandable only in the context of the information artifacts and the knowledge shared between the conversational partners. These tools enable the partners to build a common ground that would be much more difficult without the visual representation of the situation with which they are dealing (e.g., Whittaker; et al., 1993).

189 Need fo r Conventions o f Use, One characteristic of using a shared display when your partners are not co-located is that data transmission from one site to another may be at different rates. It is important to understand how different conversational protocols may be necessary m such situations. Because the traffic manager is aware (as a result of the training session) that his partner’s display may not appear simultaneously with his when navigating from one slide to the next, he T,' _ - verifies before beginning the conversation, that the dispatcher is seeing what he is seeing. The following examples illustrate how the dyads compensate for the data transfer delay. v

The first example is about how the conversational partners inform one another that both are attending to the same referent by way of the shared display. The traffic manager checks that the dispatcher is viewing the map, and the dispatcher acknowledges that he is and goes on to confirm that what he is seeing is what the traffic manager is seeing.

Example I: Dallas-Ft. Worth to Minneapolis-St. Paul—Dyad 2

Tj.21 : Do you have your map up?

D3.ZI: I got it. It seems like Minneapolis down to Just the upper part of Texas.

T3.22: Yeah. That’s what Pm showing.

Thus, the traffic manager and the dispatcher establish through conversation that both are viewing the same referent, which suggests that they are virtually and linguistically co-present, allowing for the same assumptions to be made as those with physical copresence (i.e., attention, simultaneity, locatablility, recallability, and rationality).

190 In the second example, the traffic manager in this dyad also checks with the dispatcher about his display before beginning an interaction about it.

Example 2: Chicagoto Atlanta—Dyad 2

Ti.fll: Do you have the picture yet?

Dt.242: Yeah. Okay, I’ve got it.

Once the traffic manager receives acknowledgment that the dispatcher’s display is visible, T n shares with D,.z where he is looking. However, the dispatcher does not acknowledge this utterance, and instead informs the traffic manager where he is focusing his attention by asking a question. The traffic manager appears to drop his attention to the holding time and switches his focus to the dispatcher’s concern about the “jogs.”

Ti.242: Sixteen minutes of holding it looks like.

Di.243: Uh, (?>foFtraffic or something. Those little jogs there?

The third example illustrates the cost of not modifying the communication protocol to account for the constraints of the technology. The traffic manager begins the interaction before the dispatcher’s display has Enished loading, and the dispatcher has to stop the conversation and inform his partner that he cannot see what the trafRc manager is seeing. Once the display is visible to the dispatcher, he continues the interaction that the traffic manager started.

Example 3: Dallas-Ft. Worth, to Minneapolis-St. Paul—Dyad 1

Tj.t26: Let’s take a look at the next map. Looks to me like a weather reroute.

191 D3.t27: Your screen is updating faster than mine. Okay, there it is. Yeah, it looks like a weather reroute. Probably there was some thunderstorm or something over southwest Kansas there, which caused them to deviate to the east and go over Springfield.

These examples give a glimpse of how conventions of use become established overtime. The participants, in recognizing the limitation of the application-sharing tool to provide simultaneous screen, updates, built implicit protocols and cooperation patterns to work around that limitation. As technological capabilities advance, the bandwidth may not present difBculties-and simultaneous updating will be possible, however, other challenges not'fbreseen or prescribed by the designers will surface and require users to establish new conventions of use.

S.4.2.5 Establishing linguistic and virtual copresence through reference

Using proper noun and deictic expressions. In addition to using reference to establish copresence, reference also allows conversational partners to minimize the necessary effort for grounding interactions (Krauss & Weinheimer, 1964). Clark and Wilkes-Gibbs (1986) proposed the principle of least collaborative effort to explain how both partners in a conversation minimize the collaborative effort required for a successful interaction. According to the principle of least collaborative effort, people should try to ground with as little combined effort as possible (Clark & Brennan, 1991). However, different mediums of communication allow for different levels of effort. For example, in a telephone conversation the effort required to express spatial information will be greater than if that verbal interaction was supported by a shared spatial display (Whittaker, et al., 1993). Thus, an important characteristic to consider when designing to enable least collaborative effort is how the media enable visibility, audibility, and simultaneity, thus reducing display costs (or the ease with which they can present an object to support the speaker* s utterance).

192 The use of the slideshow (via NetMeeting allows the participants in the present study to reduce their effort for grounding. It does this by framing the relevant conversation, becoming a lens through which the conversational partners can focus their discussions. This common frame o f reference, or referential anchor, is a shared representation of the situatioa that allows the dyad to move the discussion beyond each individual’s perspective toward the interdependencies between these views, producing a new perspective, à shared understanding. Thus, by having available the shared cognitive display, thepartners’ display cost is reduced, copresence is achieved, and a successful interaction can result. The traffic manager and dispatcher are better able to track each other’s focus of attention, retain their conversational context, and achieve joint reference, three aspects that Whittaker et al. (1993) maintain are critical to any work-related conversation.

Referring using propernouns. Kripke (1972,1977) proposes that in using proper nouns to refer, each proper noun “rigidly designates the same [individual or location! regardless of context” (Clark & Marshall, 1992, p. 43). The following example illustrates the use of proper names as a way of referring to things that, due to community co-membership, are mutually known. Community co-membership is evidence that if something is universally known in a community of practice, then two people in that community can assume that they mutually know it. Since the traffic manager and the dispatcher are part of the community of practitioners in the Air Traffic Management System, they are able to make assumptions that each knows the location of various landmarks used in the discussion. In the present study, the map portion of each slide allows for referring using proper nouns (e.g., geographic landmarks) and directional references. It is important to note for the reader that the geographic locations referred to by the dyad in the next example (Scenario I: Chicago to Atlanta) are not labeled on the map that partners are viewing (see Rgure 5.1 for a picture of the slide as viewed by the dyad). (These geographic labels have been added in Figure 5.19 as an aid for the reader.) This indirect copresence requires mutual knowledge based on conununity 193 membership, and the assumption oCassociativity is required for inducing this mutual knowledge. This assumption states that it must be mutually known in the community that the copresence of these geographic locations is a part of the world that the map represents (Clark and Marshall, 1992).

The following interaction (Scenario 1—Chicago to Atlanta) is an example of how the parmers in Dyad luse names of geographic locations (e.g.. Champaign, Illinois) and directional references (e.g., west) as a way of reducing display cost in the act of reference. By using location names that are mutually known, the conversational parmers are able to create a shared representation of the traffic that occurs in the airspace between Chicago and Atlanta (see Rgure 5.1).

Di.i8 : So would it be possible to route some of that traffic over Rome, to re-route it over Macey'i (?) see this big loop up here by Champaign, Illinois^ There’s a great big loop there. Looks like that guy got a big spacing, ah, right there. T i.i9: ....a lot of times.... we put some in-trail on Memphis 15 miles-in-trail. They back that up on indy [i.e., IndianapoITsI....And they spread them out 15 or 20 miles in trail. D|.,9: What if you took, like 3 aircraft....and then have Memphis route them over to Macey, Tt-i 10: The problem is that the air space that they’re cutting across here is real busy that time of day. Departures going northbound and Cincinnati is becoming such a hub, they’re departing sour/i off Cincinnati golngto Florida, and traffic coming northbound to Chicago [pause} there’s a lot of traffic going this way but they have to cut across, {pause} uh, that’s what we were talking about Just before I came in here. The sector right around VolunteerFix, Victor, X-ray Victor. There’s so much crossing traffic right in that area that we’re trying to avoid that area as much as possible. Traffic comes into Charlotte, comes into the west, nort/twesr, comes in over Volunteer. We’ve got traffic climbing off Cincinnati southbound over Volunteer. You’ve got traffic climbing off northbound off of Atlanta, over Volunteer, plus all your traffic out ofFlorida going to Detroit. Dt-tlO: Okay. So the traffic that inbound to Atlanta would have to cross a departure route from Atlanta northbound^l

194 Figure 5.19. Reference using proper names of geographical locations in Scenario L - Chicago to Atlanta.

Thus, it appears that a shared cognitive display that allows spatial reference using location names and geographical directions reduces the display cost for the dyad and enhances their ability to come to a mutual understanding of the traffic occurring in the Atlanta airspace. However, given the complexity of the data available in the table portion of the slide, (Figure 520), appears not to produce the reduction in display costs that was evidenced in the use of the map. That is, the ability to present distinctly an object to support the speaker’s utterance is made more cognitively difficult because of the great amount of data points that exist in the table part of the shared display. The following interaction between the parmers in Dyad 2 working the Dallas-Ft. Worth to Atlanta scenario illustrates the extra effort that is needed when one dyad partner (Dz. 2) (referring ta the table in the slide), begins talking about the fuel bum of the flight instances that did not experience holding. Tz.idoes not know where to focus his attention since there is no way of physically seeing where Dz.z is looking, and Dz-i’s verbalizations do not appear to be adequate without expending more effort and more description. Thus, this exampWhustrates a breakdown in the assumptions of attention, simultaneity, arid locatability. 195 -Ï CSLANI |t(l.lui|

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42 AKFueBumUneoir. Obtl gjoaa n.4ti.3 2.1021 22» A A»r«neUncert.ti«nl 935 120.1 206 297% A 272 A

Figure 5.20. Data available with the Table of Slide 1 of Scenario 2 - Dallas-Ft. Worth to Atlanta.

D2-2I5 : Even on the flights they didn’t hold, I see the actual bum was slightly higher. T2.2I6 : Which one...what are you looking at? D2.2I6 : Where it said the no holding there (?) down. It says planned, you know it was 9054 actual 9788 and airtime showing 99.4, but the actual was 101, so that it’s taking them longer than planned, even on a day without holding...so, uh, I would think—

The following section introduces a feature that, when used by this dyad, reduces the ambiguity and confusion that the previous interaction illustrated.

Referring through deLxis (with the use o f a telepointer). Another basic type of reference is deixis (Lyons, 1977; Clark & Shaefer, 1989). A deictic expression is used to point to features of the surrounding context. Deictic terms (e.g., ‘here’ and ‘there’) act as pointers and are sometimes referred to as ‘indexical expressions’ (Levelt, 1989). A speaker who uses deixis is expressing his or her situatedness in that context (Schober, 1998). Accompanying deictic expressions when conversational partners are co-located is the deictic gesture, the physical act of pointing. One feature of the NetMeeting application that eases the cognitive load in grounding is the telepointer that is controllable by either parmer and is visible to both. This pointer facilitates the ability of each partner to track the other's attention (Whittaker, et al., 196 1993) and aids them in focusing attention on a specific part of the visual context through gestures. When one partner says “look there” while moving the cursor to some point in the shared display, the second partner can associate “there” with the referred-to location because the first parmer produced the utterance and gesture almost simultaneously. The second parmer can then simultaneously hear the utterance and look at the location in the display where the pointer has been placed.

At the end of the last example, Tz., was not certain where Dz.z was referring, so in the following exchange uses the telepointer to point to where he thinks is referring.

TtzI7: Planned is this one up here {pointing} — Dj.zl7: Right. That’s for the whole 314, because those averages are for the whole 314. Tz.zlS: Right. Planned and then the acmal’s they use with holding and non-holding. With the non-holding,iike you said, did bum less and....

As the traffic manager uses the pointer in Tz-zlT, the conversation can be grounded more quickly because the dispatcher (Dz.z) can know where Tz.i is looking by the location of the telepointer. He helps Tz.z to understand that Tz.z is referring to the Total Air FuelBum numbers and Dz-z to the No Holding Air FuelBum numbers, allowing both parmers through conversation and deixis (through verbal expression and gesmre) to reconstruct their mutual understanding by focusing on the relevant parts of the external representations. This allows for repair of the earlier misunderstanding and for the building of common ground to continue. Thus, the telepointer contributes to the development of the murnal cognitive environment and serves as a basis for further interpretation, explanation, and clarification (Bressole, Pavard, & Leroux, 1998).

fil the following example (Scenario 1—Chicago to Atlanta—Dyad 1), the pointer becomes the virmal hand of the traffic manager (Tt-i) as he endeavors to describe to the dispatcher ÇD n)how traffic firom the west would be re-routed if the 197 arrival fix was changed to the Southwest fix rather than the preferred Northwest fix. He sweeps the pointer across the map, as he would gesture with his hand if the partners were physically co-present and looking at a map spread out between them. (Refer to Figure 5.L for an illustration of the slide they are viewing during this interaction.) This allows the dispatcher, through virtual and linguistic copresence, to build a mental model of the airspace as his attention is directed by the traffic manager f ■ to the important pointe m the shared map display.

T n 2 6 : if we’re going to fix balance Chicago, we’d have to drag him up here [pointing} and he would have to come across probably over here [pointing} to come down. D[.[26: ....Where do you have to send them in order to get them down to the southwest fix? T[.,27: Coming out of Dallas? Probably somewhere around the Mississippi River or somewhere right in here [pointing}. Sometimes Memphis Center, I think that boundary’s right in here [pointing}. Sometimes they’ll grab them right in here [pointing} and bring south to Meridian [sweeping the pointer to the south across the map}.... Dt.i27: Yeah, that’s what I was wondering.

Control o f the Telepointer. Another feature of NetMeeting is the ability for any participant in the meeting to take control of the pointing device. In most dyads, the traffic manager had control of the telepointer during the entire interaction. He had initial control because of the design of the experimental situation: the researcher was present at the En Route Center with the traffic manager, and this is where the NetMeeting session was initiated.

In the following example (Scenario 3—Dallas-Ft. Worth to Minneapolis-St.

Paul), the dispatcher (D 3.2) of Dyad 2 decides to take control so that he can better describe to the traffic manager the location and events he finds important. (Refer to Figure 5.8 for an illustration of the slide they are viewing during this interaction.) It is interesting to note, however, that this is the only instance across all of the dyads in the present study where the dispatcher takes the initiative to control the telepointer.

198 Ds-i?: .... unless you had a fix balancing problem, the routings that are Get’s see, maybe I’ll see if I can take control of this thing here). Okay, I think I’m taking control. These routings up around here [pointing} could almost be due to weather....

In another dyad G^yad 2 of the Dallas-Ft. Worth to Atlanta scenario) the traffic manager (T 2.2) suggests that the dispatcher (D 2-2) take control of the pointer. For some reason (not discernable to the researcher), the dispatcher chooses to not take control.

D2.18 : Let’s see/paitse/— Tz.29 : Do you want to take the mouse and look at some of that? D2.29 : Well, I can see what (pause) It’s okay[doesn't take control}. All right, so this particular instance.... this pretty much followed the flight plan until it got to Meridian [pause} and then.... T2.2IO: It got moved down to Montgomery there [pointing}....

One way that the dispatcher (Dw) of Dyad I in the following excerpt (about Scenario I—Chicago to Atlanta) dealt with not having control of the telepointer, instead of taking control, was by referring to where the trafric manager (Di.i) was pointing.

D|-i21: Okay. And let’s (?) say you have other traffic coming in over that fix, for instance, maybe something like — If yon saw that you’re getting all that much traffic over that sector that you’re pointing at there^you can do like maybe internal first tier ground stop to keep some of that traffic on the ground for say 15 minutes. T[.;22: We do that....

Another way of dealing with not having control of the telepointer was to ask the traffic manager to point to where the dispatcher wanted to refer. The following is an excerpt fix)m Dyad I as they discuss the Chicago to Atlanta scenario. This interaction demonstrates how use of the pointing device allows for the conversational partners to share knowledge with a minimum of effort. The traffic manager (Tt-i) is 199 talking about a location in the Atlanta airspace that is used as a navigational aid for arrivals. (Refer to Figure 5.19.) The dispatcher (Du) does not have knowledge of where this location is and asks to point, using the telepointer, at the location in the representation so that he might understand exactly where is referring.

Tt.t 12: There’s like a Volunteer transition for the Macey arrival right now. We’re in the process of trying to get that taken out of the STAR. D,.i 12: Well, where exactly is Volunteer? Can you point to thatl T ulS: It’s right here {pointing}. Volunteer is right here {pointing}. Dm 13: Okay.... Ti.il4: ....they’re going to do away with that transition and you’d have to come all the way over here {pointing} to probably - uh, probably going to have to come more like into this area {pointing}. Di.iI4: Oh, that would be way out of the way. Tt-ilS: Somewhere across here {pointing}.

Thus, the request by the dispatcher for the traffic manager to point to where he was referring not only allows the dispatcher to gain more knowledge about one landmark in Atlanta Center’s airspace, but also updates the traffic manager’s mental model of the dispatcher’s knowledge. This interaction created the opportunity for even richer knowledge dissemination to occur. By using the pointer to traverse the shared display, Ti.t has provided Di.i with the ability to update his mental model of what might happen to his flight if he was to reroute it over the Macey arrival fix,

Cremers (1998) proposes the principle of minimal cooperative total effort that extends Clark & Wilkes-Gibbs (1986) principle of least collaborative effort to include not only what participants say, but also what they do (Cremers & Beun, 1995), By using the telepointer as a way of gesturing, the partners are able to reduce what they say and do to reach mutual agreement that a target object has been identified.

200 5A 2.6 Monitoring and revising utterance plans

When making a reference to something, someplace, or someone, the speaker intends the identity of the referent to become a part of the speaker and listeners mutual knowledge. For this to happen, the speaker must convince himself that the identity of the referent is truly going to become part of their common ground. The speaker might use longer noun phrases to adjust his utterance than the theories of cooperative and collaborative conversation might predict (Clark & Wilkes-Gibbs, 1986; Grice, 1975). The speaker may believe that the extra effort of revising his utterance-in-process might result in less effort later if, by not revising it, the listener misunderstands and repair has to be taken. If the speaker determines, while making the reference, that it may not succeed, he can change or expand what he has said so far. Thus, in order to make his utterance more likely to succeed, a speaker, taking into account his partner’s perspectives and their current common ground, monitors and revises his utterance plans in the course of executing the utterance (Schober, 1998; Horton & Keysar, 1996)/ % appears that a speaker will make an adjustment to his plan upon the internal assessmentthat his previously presented evidence is inadequate for the listener to identify.the referent. The speaker’s adjustment is an attempt to strengthen that evidence, and the way he strengthens it is to provide more precise evidence that will allow the listener to use less cognitive effort in order to understand. The shared cognitive display used in this study aids this monitoring and adjustment process by allowing the partners to reference tabular and spatial events through deixis and geographic locations rather thaa relying only on linguistic cues. In the adjustment process, the speaker uses objects in the shared display to provide the listener better grounding to what is being referred to. Following are examples that support this finding. Each of the examples illustrates how the speaker adjusts his original utterance to strengthen his evidence

201 ■ - ---'v t=>:f

for where, he waafs the listener to focus his attention^ Example 1 shows how the speaker tells the listener to look at where the telepointer is located so that his original utterance “out here” will be understood. Another way that the speaker adjusts his original utterance plan is by expanding on the original definition that he determines in his internal monitoring will not provide sufficient evidence for the listener to know to what the speaker is referring (see examples 2,3,4^ 5, and 6 ). These examples support the findings of Cremers and Beun (1995) that speakers prefer to use absolute features (those that can be understood by considering only the target object; e.g., “the green route” by considering other objects present) when using referential expressions to focus attention.

Example 1: (Scenario 2—Dallas-Ft. Worth to Atlanta—Dyad 1)

Tm 17: Yeah. Well, if you get out here — see where I got the cursor pointed right there[pointingjl....

Example 2: (Scenario 2—D^a^-Ft. Worth to Atlanta—Dyad 1)

V ...

■itw* ■ ■ Tz.[ 10: That’s right.... JBut it looks-like the majority of ourflights^ 272 of them, are no holding.

... • ■ ■ . Example 3: (Scenario 1—Dallas-Ft. Worth to Atlanta—Dyad 1)

Dz.t6 : You’d have to break it down into peak periods, the number of flights during the peak periods__ Tz.t7: That’s correct. And it looks like, looking at the screen here....several ol those flights, as you can see, went up over Rome on the northern route.

Example 4: (Scenario 2—^Dallas-Ft. Worth to Atlanta—Dyad 1)

Tz.t32: Right. And if you’ll look on this solid route, on the green route here__

202 Example 5: (Scenario 1—Chicago to Atlanta—Dyad 2)

Ti.i7b: You are real close to a boundary outthere, in that one route to the west, and then thunderstorms or whatever.

Example 6 : (Scenario 3—Dallas-Ft. Worth to Miraieapolis-Ft. Worth—Dyad 2)

D3.2I: Do yod'^,any problenas.Tj-i, with/fteroK/e/Aar’syî/ed? The green route^htf' Tj-zl: No. . t These examples giye further evidence for the copresence heuristics (i.e., the assumptions of simultaneity, attention, locatability, and rationality). The reason those making the adjustments have fordoing so is to make their references more likely to succeed. Without the shared display, the precise identirication of the referent would have been possible only with greater cognitive effort through increased verbal interaction. Thus, it is the establishment of a virtual copresence between the partners that allows adjustments to be made that strengthen the evidence for mutual knowledge of the identity of the referent Without this shared display, the speaker and listener would have to rely only on their linguistic copresence, which requires greater cognitive effort to make the same adjustments. Thus, the findings of this analysis suggest that even without the physical copresence of speaker, listener, and referent, linguistic and virtual copresence can facilitate successfully the building of mutual knowledge.

S.4.2.8 Summary and discussion

The findings in this section suggest that an environment that combines an artifact in the form of a shared visual display with telepointing capability and a two- way audio communication tool with which and through which parmers interact is a

203 distributed cognitive system that enables the participants to succeed in building shared perspectives as they engage each other in a complex, ill-structured problem­ solving task. The shared display supports the communication process by reducing the cognitive effort needed by the participants in each dyad to build a common ground an establish mutual understanding. These findings appear to conflict with earlier work that investigated the benefits of adding visual media to audio for such tasks as information exchange and collaborative problem solving (see, for example, Chapanis, 1975; Fish et al., 1990; Reid, 1977; Williams, 1977). That research suggests that adding a medium that allows the presentation of visual information has no effect on either the quality of the interaction or the outcome of the task (e.g., Anderson et al., 1997; Hiltz et al., 1986). However, most of the studies reporting these results focus on the use of video to communicate visual aspects of interaction, such as eye gaze, physical gestures, and facial expressions (Chapanis et al., 1972; O’Conaille et al., 1993; Sellen, 1992; Tang and Isaacs, 1993). The present study makes use of the visual medium to share cognitive artifacts that are part of the distributed problem-solving system as described in the introduction of this section (i.e., Grosz, 1981; Hutchins, 1990; McCarthy etal., 1991; Nardi etal., 1996; Whittaker et al., 1993).

' ■' Supportfo r Communication, Di the present study, it is the shared display that provides the foundation for building a common ground for the participants in their verbal conversation, and it is the conversation, in turn, that helps the partners make sense of what is on each slide. This cognitive artifact (composed of the slideshow, and the NetMeeting application with the telepointer feature that enables sharing) serves to disambiguate utterances between the conversational partners. It reduces the “referential distance" inherent in language interaction by allowing pointing to objects referred, to in verbal utterances (Forhlich, 1993), and it provides the opportunity for deictic gestures indicated by the spatial references (e.g., “there,” “here,” “to the west”) in the verbal conversation. It also allows parmers the ability to simultaneously

204 Y'-* - '

speak and point. The listener can view the slide and listen to the speaker simultaneously, and the telepointer is available for each partner to see, giving them the opportunity to have a mutual focus of attention. Also, the persistence of the information on the display modifies the communication constraints by reducing the cognitive load required for maintaining context. Li other words, this shared cognitive artifact allows the partners to establish a virtual copresence. Virtual copresence enables participants in a conversation to be physically in different locations while still realizing the benefits once thought to be available only through physical copresence (i.e., simultaneity, attention, locatability, and rationality). In this study, it is the complexity of the NAS, as represented in the slideshow, that requires the richness of the display in order to allow the partners to establish virtual copresence. This, in turn, allows them to arrive at a common situation assessment and develop a shared perspective, a shared mental model. It is the non­ verbal resources of the shared display and the telepointer that contribute to the augmentation of the mutual cognitive environment through which the conversational partners are able to reduce their collaborative effort. Thus, it is through the multi­ modal interaction (involving the critical interplay between the graphical representation, the telepointer as“metagraphical arrow” (Lee & Stenning, 1998), and the linearized flow of the verbal conversation) that the participants are able to establish virtual copresence leading to the sharing of critical knowledge as they proceed in their problem solving task.

Barriers to Communication. Even though this cognitive support system enhanced the interactions of the dyad partners, by aiding them in effectively coordinating their conversations and establishing building shared perspectives, some aspects of this system presented barriers to communication. The control feature of the telepointer within the NetMeeting application led to the failure for both partners to share control of the pointer. Only one of the ten dispatchers in the study chose to

205 take control of the pointer. Because this feature lacks the affordance that would allow the partners ease of taking control^ it is possible that the content of the interaction was affected, ft is difficult in the broad brushstrokes painted by this study to know exactly what effect not taking controi had on the content and process of the interaction between dyad partners. It could be suggested that the person who had control of the telepointer also may have had a greater influence on the data that was attended to and to the knowledge that was shared (Cronshaw & Lord, 1987; Lord, Foti, & DeVader, 1984).. By examining only one part of the interaction—that of the number of solutions proposed by which dyad parmer—it appears that not having control of the telepointer did not prevent the dispatchers ftom proposing 60% of the alternative solutions that were proposed. Table 6.1 illustrates the number of solutions proposed by each member across the eight dyads.

Dyad Number of solutions Number of solutions Total solutions proposed by the proposed by the proposed traffic manager dispatcher

Dyadi.i 0 3 3

Dyadi.i "2 2 4

Dyadi.i 1 0 1

Dyadi.i 0 II

Dyad].!. 1 : 4 5

Dyad].2 1 I 2

Dyad^.! 2 2 4

Dyad].! 2 0 2

Totals 9 13 22 Table 5.3. Number of solutions proposed by dyad members.

206 Future research needs to examine what factors impact, constrain, and aid the sharing of knowledge across and within, organizations in order to match knowledge with control. One question of interest is what impact, if any, does controlling the telepointer have on the interaction in terms of directing the parmer's attention, focusing the problem solving activity, and generating alternative solutions. Another barrier to the interaction was the result of the low bandwidth of the telephone line over which the data for the shared display traveled. The result was the need for the partners to check with one another when changing slides beginning a discussion of the new slide. If this communication protocol is not established, either explicitly or implicitly, the result is one partner beginning a discussion before the other can see to what is being referred. This can lead to one partner re-stating his utterance once the other can see the referent, or possibly, in a topic not being picked up again if once the partner can see the referent focuses on a different aspect of the display.

5A.3(Re)presenting Experiences to Build Common Ground

5.4J . l Introduction ^

" The previous section dischssecf the role that cognitive artifacts play in a distributed cognitive system âÿcohvërsdÜonal partners collaborate on a complex problem-solving task. This sectibn describes hdv/these partners make use of analogies and storytelling to aicfin the building of common ground and shared perspectives. These (re)presented experiences engender a variety of alternate perspectives to be brought forth by the partners which then become a resource for establishing a shared view of events, objects, and actors ^ d d le to n , 1996). In the Phaedo^ Plato puts forth his belief that all knowledge is actually remembering (Chappell, 1996). Reeves (1996) suggests that when a person attempts to imderstand or make sense of something new, he or she engages in metaphorical

207 thinking, or the finding of analogies, by activating knowledge structures in memory that closely match the current situation. These structures are often referred to as schemata (Bartlett, 1932), frames (Minsky, 1975), scripts (Schank and Abelson, 1977), or cases (Kolodner, 1993), and it is theorized that they organize knowledge and support the development of expectations. These expectations can be used to guide the processes of comprehension and perception, which, in turn, aid understanding, a process of reminding or remembering (Reeves, 1996). Paul (1990) emphasizes the importance of dialogue in developing an understanding. Dialogue allows the participants to combine and reorganize each other’s existing schernata through the sharing of data and knowledge. ‘Tt would seem that listening and interacting with others is an essential form of access to new information and the transforming of existing schema structure that must occur in the understanding process” (Reeves, 1996, p. 117): This section providesssome examples of how one dyad partner uses stories to (re)present his experiences as a way of providing an explanation to his partner, how another uses analogy as a tool for diagnosis (Weick, 1995), and how a story told by one of the partners prompts the sharing of new knowledge between the parmers.

5.4.3.2 Using storytelling as explanation

The following interaction between the traffic manager and dispatcher discussing the Chicago to Atlanta scenario is an example of how one parmer tells a story in order to help the other understand why a certain strategy is not used by traffic management to control traffic flow, ^eferto Section 5.2 fora description and illustrations.)

Dn3: Why do they Just not give them mfles-in -trail out of Chicago?.... Tt.i4r It’s more efficient: It’s like we’re running in/paiwe/Like going the opposite dnrection and we run in-trail to Indianapolis Center and everyday 20 miles-in-trail. But we might miss a [bucketj somewhere in here fpoînttngf, I have flown to Chicago a coupleof times, and here we are slow back in this area {pointing}, and

208 we get close te Chicago and ail of a sudden they tell us fast forward and short cuts, whereas back in Denver we were back there 20 miles-in-trail and slowing us down. Dn4: So in other words, Chicago didn’t really anticipate the amount of trafBc they were going to have at the time that you were going to be getting there? Tn5: Right. Well, Chicago had a niiles-in-trail restriction on Indy and Didy backed that up over Atlanta. And we basically do that eveiyday in Atlanta. They have an arrival rate and we call that miles-in-trail based on the volume over a certain fix....

When Dt-t asks why the miles-in-trail strategy is not used at the originating airport, the traffic manager begins to explain by the simple statement “It’s more efficient [to not do that].” However, he realizes that this is not a sufficient explanation to ensure that the dispatcher will understand the reasoning and knowledge for not using such a strategy. So, the traffic manager calls to mind an instance that would help explain the inefficiency of putting miles-in—trail on a flight at the originating airport. Even though the story involves different origination and destination airports, the example is sufficient for the dispatcher to understand the explanation and update his existing general schema for miles-in-trail traffic management strategies.

5.4.3.3 Using stories as a tool for diagnosis

». In an utterance just previous to the following interaction, the traffic manager suggests to the dispatcher that the cause of what they are seeing in the first slide of the Dallas-Ft. Worth to Minneapolis-St. Paul scenario may be due to fix balancing. (Refer to Section 5.2 for a description arid illustrations.) The dispatcher then relates his experience and knowledge of fix balancing in the Dallas-Ft. Worth airspace. He presents his perspective as a fiame of reference for interpreting the actions and events of the current slide, using the training scenario to infer what must have happened “between the lines” and why these events happened in the current scenario. This story allows the dispatcher to make sure that he has understood what the traffic manager has told him about Minneapolis-St. Paul airspace and fix balancing, veri^fing that they have established an understanding of the situation. Following this,

209 the oppottuniQris now avmlable to the; traffic manager to accept or correct the dispatcher’s representation of his'understanding.

T3.i4: ....Some of those sectors are going to get buried, and I’ll have to offer a little relief and have to move some airplanes for that reason. Dj.i5: Okay. And that scenario [the training scenario] that we looked at before, the Phoenix to DFW, I know there’s certain times of the day when the way we schedule all of our airplanes coming in horn the west at the same time, that they overload the northwest comerpost for DFW, which is why they tend to reroute a lot of those arrivals down to that southwest comerpost, and that could be the same kind of thing going on here at Minneapolis. Maybe it’s a busy time of day for arrivals from the south, or from the east or something. So tnaybe they take them out west for fix balancing like you’re talking about. That’s what happens at DFW with that northwest comerpost. Tj.i5: ....having worked the arrivals into Minneapolis from the east, typically when we have to take somebody to level off another fix, we try and (?). Well, basically you take somebody out of the stream, it eliminates pressure on the rest of the stream, but then you can keep them higher and cleaner longer. Dj.i6: Yeah. And if your south fix is overloaded it would probably—if this guy is coming a little bit from the southwest—it’s probably less of a deviation for him to go to the west than it would be for a guy whose coming up from St. Louis or Chicago or something [pause]

Thus, the dispatcher uses the analogy of a familiar situation (i.e., fix- balancing that occurs in the Dallas-Ft. Worth airspace) to reorganize information and connect patterns in memory to develop an understanding of the unfamiliar situation at Minneapolis-St. Paul (Reeves, 1996). By calling to mind a model he knows of (i.e., Phoenix to Dallas-Ft. Worth), the dispatcher is able to recognize the common pattern of events between the recalled schema and the current situation. He shares this with the traffic manager in the form of a hypothesis about events that might have caused the problems identified in the scenario. The traffic manager confirms this assessment, allowing them to then explore alternative solutions for avoiding the incurred cost of fix balancing.

210 5.43.4 Story triggers memory event leading to the sharing of new knowledge

In the following interaction the dispatcher relates a story about the situation portrayed in slide 3 of the Dallas-Ft. Worth to Minneapolis-St. Paul. (See Figure 5.10 in Section 5.2.3 for an illustration of the slide.) He shares with the traffic manager the proactive strategies used by dispatchers when re-filing flight plans around weather for flights departing Dallas-Ft. Worth airport and how those actions seem to produce difficulty for Ft. Worth Center traffic management. This (re)presenting of his experience triggers a memory for the dispatcher and leads to a conversation about flight strips and how they are amended. The dispatcher is able to update his mental model of what it means to file a new flight plan and how it differs from amending a flight plan. He is also able to apply the new knowledge about how each are handled by traffic managers. It appears that the shared knowledge resulting from this storytelling episode then leads to some important schema restructuring for the dispatcher, which, in the future, may result in more effective interactions with Ft. Worth Center.

D3.i29: ....our dispatchers are usually pretty proactive in filing flight plans around the weather, and sometimes it drives ATC nuts because there’s ... almost [all] city pairs have preferential routes, and they ask us to stay on their pref routes, and according to FARs when there is known areas of thunderstorms, we’re required to flight plan around them. So we’IF go ahead and file the flight plan around the weather, and then the guys in there hittidlingthe strips and departure strips in the tower go nuts, because we keep re-filing routes all of the time. And they get one strip after another, and they get confused as to which way we really want this guy to go. You know, they’ll get 2 or 3 or4 strips for the same flight. And I guess those things don’t have time stamps on them either, so you don’t know which one is the current one. Tj.i29a: ...3ut I know that they do have an amendment number. Da-t: Okay. Tj.i29b: ....anytime there’s an amendment to a flight plan {pause} you know, if you fUe a whole new flight plan... you know, we might not know. If there’s an amended flight plan, it tells you the amendment number and you always go with the most recent amendment number.... D3.3 O: What’s the difference between filing a new flight plan and an amended flight plan? It’s an amendment, k that sometiiing that ATC does, or is that something that the airline does? 211 Tj-tSO: Typically, IJust amend them. Dj-iSl: Okay. Weil, we put out a new flight plan.... Tj-i31: So you find that the tower controllers don’t know which route a guy’s suppose to goon. D;.[32: That’s what they tell us....

Following the story by the dispatcher about the interactions he has had with Dallas-Ft. Worth tower controllers on the issue of re-filing flight plans, he is reminded of another issue he has with Ft. Worth Center traffic management. The dispatcher relates to the traffic manager the called-to-mind story about how the Center’s traffic management reroutes traffic due to weather out of Dallas-Ft. Worth airport This story reminds the dispatcherof how another Center (i.e., Chicago) differs from Ft. Worth Center in handling weather reroutes. This prompts the traffic manager to share with the dispatcher how Minneapolis-St. Paul traffic management handles the issue of rerouting departures due to weather.

Dj.i32: ....Another thing. Ft. Worth has a strange system of working reroutes out of DFW anyway. If they have weather, say on the east departure routes, and suppose we got, uh, say the north departure routes, since we’re talking about Minneapolis. Suppose that there’s thunderstorms along with the Red River just north of DFW there, and so the dispatcher being the good guy that he is, he decides he’s going to file the guy out to the east over Texarkana and then up to Minneapolis that way. Well, the guys....say, “Well now the east departures are overloaded, so we’re going to take the east depaimres and move them south’’. So what happens is the dispatcher....his flighTwhichwas filed on the [north] route, he gets filed out east over Texarkana and he goes'onhis merry way. The dispatcher who was doing his job and filed the guy d^ec'Wtarkana in order to avoid the weather, now his flight gets rerouted overHbustoiuorsomething. Because they reroute the east traffic [to the] south. And hcwintis u^goingDEW to Houston and then up to Minneapolis. So itjkind ofhurts ypmthe way DFWddesthis. If you’re doing an effective job of pre-planning, sometimes,itcotnes backto bite you. But Chicago does it differently. At Chicago, they look at the destination of the trip and they’ll say all trips to DFW are going this way, and trips to Houston are going that way. So it’s just kind of inconsistency fix)m one center to another how they handle reroutes. T3-i32: ....[Tin Minneapolis, typically we just don’t swap a whole departure and say, like you said, move all the north departures to the east, and the east departures to the southeast. Dj.t33: You don’t usually move around a whole block of them like that?

212 T3.t33c: ....[Wlhat we would do is we say '‘Anybody who has filed the north departure route, the Dallas for example, call individually and (?) get an approval request, (?) the release.” So they call the traffic management at the center, and we come up with a reroute for them. So I guess that way we would avoid the scenario where the guy was re-filed out to the east and then you take him to the southeast.... D].[: Yeah.

The traffic manager interprets the dispatcher's uncertainties about how Dallas-Ft. Worth traffic management handles departure rerouting due to weather as a concern about whether there are analogous issues in Minneapolis-St. Paul. The dispatcher’s story prompted the traffic manager to recall and relate how Minneapolis- St. Paul Air Traffic Control handles weather-related re-routing for its departures. So, the hypothesized explanation about what happened to the flight instance described in slide 3 of the scenario (see Figure 5.10 in Section 5.2.3) led to the dispatcher to call to mind concerns about how traffic management handles weather reroutes of flights departing Dallas-Ft. Worth. This, in turn, prompted the traffic manager to share with the dispatcher that Minneapolis-St. Paul center differs in how they handle rerouting of departing traffic due to weather. So, what these interactions about re-filing versus amending and departure re-routing allowed was a resolution of the uncertainties the dispatcher had about how Air Traffic Control works and whether there were analogous issues at Minneapolis-St Paul Center.

5.4.3.5 Summary and discussion

These excerpts from interactions between dyad partners illustrate how storytelling using similar or analogous examples can aid in the building of common ground and the establishment of mutual understanding as the problem solvers collaborate in their task. Specifically, the storytelling allowed the partners to:

213 • Ensure that they had a shared understanding of the current scenario

• Use the stories and analogies as tools to help diagnose the underlying problem to be solved

• Use storytelling as a method for extending or refining their knowledge.

5.4.4 Coping with Uncertainty when Data and Knowledge are Unavailable

5.4.4.1 Introduction

The previous section dealt with story-telling and analogy as a way of applying prior knowledge to a new situation in order to provide explanations, as tools for diagnosis, and as a means to prompt knowledge sharing. Stories enable people to talk about absent things and to connect them with present things in order to attach meaning to the current situation. This section provides descriptive accounts of how different dyads coped with the unavailability of certain data (i.e., data that was not provided to them in the slides of the scenario and assumed to not be a part of their combined knowledge base). The slideshows of the scenarios used in the present study did not provide all of the data that might be necessary in order to solve the inefficiencies represented in the scenarios. Even with certain data being unavailable to them, the dyads proceeded with the problem-solving task. The categories of unavailable data mentioned across the different dyads can be found ia Table 5.4. Each dyad mentioned at least one category of data or knowledge that was unavailable but would have been helpful to know to correctly diagnose the problem situation. The ways in which the dyads coped with this unavailable data varied, and the following sections describe and discuss some of those differences.

214 V. - ' " ' ': ' -Î ; e. ':- :- i A :

Unavailable Data Identified by Dyad Partner Calling Attention to Unavailable the Dyads Data

Scenario Scenario Scenario Scenario Scenario I 2 3 4 5 Endividual instance information (i.e.» actual speed, approach speed, T ul Ti.2 D22 D4.1 Tm altitude, length of holding delay, Dm T2-2 D5-1 mileage of actual route) Specific holding information (i.e., Tm T2-2 time or location of hold, causes, Ti.i Ti-2 D^[ Dm daily trends) Fuel data (i.e., actual arrival fuel, actual release fuel) D3-2 Dm Traffic status (i.e., other traffic in Dm center and neighboring centers; in potential reroute space) Tm Arrival air space (i.e., flow patterns into airports, TRACON Tm configuration) Airport restrictions (i.e., runway configuration of destination and of T m Tm nearby airports, airport arrival Dm rates) Meteorological information (i.e., D m Tt.2 Tm Dm weather, winds) T m D3.1 Intentions of those involved during Tm T2-2 Dm actual flight

Table 5.4. Unavailable data categories by dyad

S.4.4.2 “Filling in” for unavailable data

The dispatcher begins the following interaction by suggesting to the traffic manager that understanding the cause of holding involves having access to certain data that appears to be unavailable to them in the slideshow.

215

-SSL,-'': DzclO: Do we know if tbaCs, uh[pausef I guess any holding would be for metering as opposed to justy uh {pause} is weather causing this or just the amount of traffic? Is there a push? We don’t know that, do we? Tz-zlI: Uh, no/paHse/get time of day there. 1937 Zulu was the arrival time, so you figure that when he made that holding turn out here it was probably I8S0/I90O....

[utterances omitted]

Tz-zlS: .. ..basically it arrived at [pause} the aircraft arrived about 2:37 Eastern Time, which is at the tail end of an Atlanta push....

The data that the dispatcher identifies as unavailable is the cause of holding i.e., whether it was for metering due to weather or amount of traffic. He hypothesizes that the likely cause is traffic congestion and checks with the traffic manager that his assessment is correct. The traffic manager supports this hypothesis by sharing with the dispatcher knowledge about traffic typically occurring in the Atlanta airspace at the time of arrival stated in the data of slide 2 (i.e., 1937 Zulu; refer to Rgure 5.21). This knowledge is that the flight instance arrived into Atlanta at the end of an arrival push. The weather data that was identified as unavailable is pursued later in their conversation, as indicated in the following interaction.

Tz-zl9: ... And I could see why they are going over College Station on that north end [pause] looking at the one month period, you got weather /paître / 1 guess on weather days some of the flights were rerouted out of College Station and on other days they were going north over Portsmith [pause} Dz.zI9: Yeah. And that happens quite a bit, as the line gets busy here. Tz.z20: Because looking at die dates now [pause} uh [pause} We’re talkin’ May 1“ to June 1“. Dz.z20: The Ft. Worth Center [pause} I mean if we lose our east arrival, excuse me, east departure gates \because ofweather\r they are going to start sending ’em to the south and to the north.

So, even though data about what weather was occurring was unavailable to the dyad, they make inferences based on their experience and prior knowledge that allow them to “fill in” the missing data and use their guesses to proceed in the problem-solving task. Markman (2001) suggests that when problem solvers feel that they are knowledgeable about something, they may feel more secure about 216 proceeding with the best evidence they have available. This dyad was able to form a hypothesis about the weather situation (not available in the data provided) in their scenario based on data and knowledge that were available to them (i.e., the dates that the scenario covered - May t“ to June a month when thunderstorm activity is common - and prior knowledge of how past flights were re-routed due to weather), and proceeded with their task as if the hypothesis of weather acti vity was known to be correct.

Ai Futfiifn UnemObtl ajaao ia.4sao 21200 255% ToUIFuefiuRAtl saao lasoaa tJOaO 165% AiTim* Uncatlmnl mo mo 260 252% Tailrdnnsl 7.0 50 ■20 266% . - TjMOutinrel 150 too 50 -313% OiATinegl . 1732 1732 00 ...... O«rr»0 .. t747 1742 50 Onrmgl _ ISQO„ JS5J_ 21.0 ...... 1937 __ 1356 „ tao a— iMnntigwriii—ill ■ ii'wiii

Figure 5.21. Dallas-FL Worth to Atlanta-Slide 2

S.4.4.3 Reluctance to simplify interpretations

The following interaction is an example of a dyad whose members were reluctant to proceed beyond the situation assessment phase of the problem-solving task due to the uncertainty and equivocality that is provoked by data that is not 217 available to them ia the slideshow. This interactfoa between the dyad partners working the Dallas-Ft. Worth to Newark scenario differed from the interactions between other dyads as they identified unavailable data during the problem-solving task. The interaction between the parmers of Dyad 2 of the Dallas-Ft. Worth to Atlanta scenario illustrated in the previous section is typical of how other dyads proceeded in the face of uncertainty. Table 5.4 indicates the different number of data categories that Dyads-i identified as unavailable (six out of the eight categories) as compared to other dyads in the study (e.g,^ Dyadu had the next largest number of categories of unavailable data with four of the eight categories). Dyads.i iterated between the activities of discussing data available in the slide or knowledge held by one or both members and naming data that was unavailable to them but was important for them to proceed with the task. Often this iteration included going from identification of unavailable data to hypothesizing about what appears to be happening in the scenario (e.g., “maybe speeds were reduced further than the normal approach speeds for that particular sector”, weather avoidance, or “arrival volume at Newark”).

The following conversation between the dyad partners took place while they viewed slide 1 of the scenario (see Rgure 5.22):

T sil: ... J’msaying those instances barring something that’s happening en route, which I realty can't determine from thiSr you know, air traffic wise.... Ds.t I : ....the problem here the difference is, uh, what the, as far as the case study that I’m looking at, is what the actual arrival fuel is. I mean that 8 % might have been taken into my consideration by, you know, additional fuel or something like that, you know. With these actual fuels. Just by looking at this /can't predetermine if that's good or bad or, you know, stuff like that.... Tst3: ....I don't see, you know, that doesn’t give me the runway depiction, I mean, you know, there was a,big difference in you coming in over Robinsville and straight in and landingon four, then having to circle all the way around and come the opposite direction kind of thing. That's 4 or 5 minutes, you taow, fuel bum right there. So I can't really, you knom tell from the {pause}

218 Ds-i3: Right you doa’t know what kind of configuration they’re using out of LaGuardia or Kennedy, etc. etc. That could be the whole balls of wax why the fuel bums are up so high. You know, we just don’t know what kind of configuration. Cause, it’s not Just one airport that you look at up there, it’s the other two....you know, including Philadelphia also. We got to know what type of configuration they’re doing.

[utterance omitted]

Ds.i4: Then also, you take into consideration once again, what’s DC doing? All this traffic is being flown right from DCA’s airspace. (T^: Correct) They could have another, you know, where, where's the (?), where they get em, that’s the big thing. What’s happening, you know. And this picture doesn’t tell us that, Tj.t5: Yeah. I can’t really, {pause} you know this may determine how American Airlines flights flew, but I don’t really, it’s certainly not the only airplanes that were going in there and E can’t determine, like where holes were trying to make to fit other airplanes in and that sort of thing either, but it would seem just from looking at the information on this scenario that when you go into a hold for Newark, coining up from the south, you are in there for awhile.... Jt’s like 25-30 minutes, or something like that. Ds.i5: But once again, that alternate route up over the top there. Did he get any type of delay? You know, that’s the other— Tj.i6a: Yeah, I don’t - D s.i5: — Just need information,

[utterance omitted]

D 5 . 1 6 : Uh, you know, some of the aircrafts actually took holding, some didn’t, you know, then why were they overbuming? You ioiow, just because maybe they were, you know, once again into the approach phase, they was, you know, the speeds were reduced even further than the normal approach speeds into that particular sector. You know, that could -this information, once again, doesn’t tell us or give us enough information, let’s put it that way.

The reluctance of the members of Dyads-i to replace data and knowledge unavailable to them raises a number of possible explanations. It may be that neither member of this dyad had enough expertise to proceed by using inferences based on prior experience. However, the years of experience each had with their respective organizations were 12 years for the dispatcher and 18 for the traffic manager, so it is unlikely that inexperience is a likely explanation for their reluctance.

219 - _ -

CSIAHT lldtlnil

Bteaisaa M lÉm ■ 5D Ai F i^ u n UncoK {b l a m s 2*JU7S 7SCA. 17K0 la s o m o 5 Ai FueBunUncoR Obtl a s a a a a o a a *sa.2 aT Z A . l a a ZISS 4716 203% sssss^ ^ s M l

y

Figure 5.22. Slide 1 of the Scenario Dallas-Ft. Worth to Newark.

More conceivable is the notion that this scenario differs in some fundamental ways from the other scenarios used ia the study. The complexity of the airspace in the Northeast corridor of the United. States is far beyond that found in other parts of the National Airspace System (NAS). The sheer number of flights arriving and departing these airports each day, the interdependencies between the Centers (i.e.. New York, Washington, and Boston Centers), the interdependencies between the major airports within these Centers (i.e., Newark, Kennedy and LaGuardia airports in New York Center; National and Dulles in Washington DC Center; and the Philadelphia airport in Washington Center) distinguish this airspace hom other parts of the NAS. The arrivals at Newark airport are impacted not only by weather at the airport and other traffic that is arriving, departing and crossing over Newark, but these flights are also directly affected by the trafiic flows, runway configurations, weather and

220

r - . . . traffic management strategies at LaGuardia, Kennedy, Dulles, and Philadelphia airports. The necessary knowledge and data of these traffic flows and strategies are distributed among traffic management organizations at the various Centers and airports, and the dissemination of this information often does not occur because of the demands of an environment that is highly complex, dynamically changing, and cognitively demanding. This distribution of knowledge without a well-defined process to disseminate it to actors in the cognitive system who need it, can lead to an incomplete understanding of the situation making it possible for actors to solve the wrong problem. Because of this complexity, the distributed nature of the data and information necessary to address the problem in the scenario, and the unavailability of much of this information, Dyads-t has difficulty “filling in the missing information” even though the research literature suggests that problem-solving experts frequently form hypotheses to “fill in” for the unavailable data(Sanbonbatsu, Kardes, & Herr, 1992). This dyad was unable to reduce the uncertainty and equivocality that arose because of the interdependencies and the distributed nature of data and knowledge among Centers and airports in those Centers while engaged in this problem-solving task. Weick, Sutcliff, and Obstfeld (1999) suggest that one practice of organizations, such as air traffic control with “potentials for catastrophic consequences,... interactively complex technology” (p. 81), and high degrees of interdependencies among teams (both intra- and inter-organizational) is a reluctance to simphfy interpretations of the current situation. Constructing simplified models can be potentially dangerous for such systems as air traffic management because they “may lim it... the precautions people take and the number of undesired consequences they envision, [as well as increasing the likelihood of eventual surprise” (Weick, et al., 1999, p. 94). This reluctance enables members of these organizations to resist simplified “mindsets” that would allow them to ignore data or to “fill in” features fiam

221 aa underlying schema for data that is not provided in the scenario in which they are situated, thus avoiding the potential to replace the unavailable data with incorrect or inaccurate data.

5.4.4.4 S umraary and discussion

Most of the dyads in the present study were able to proceed with their problem-solving task even though they identified potentially important data that was unavailable to them in the scenarios: (e.g., Dyad 2 working the Dallas-Ft. Worth to Atlanta scenario described in Section 5AA.2). Because these participants maintain a level of expertise in the work they perform, they had confidence in using their knowledge and experience to make inferences about the data unavailable to them. With these inferences, the participants proceeded in the problem-solving task with the best evidence they had available (Markman, 2001). The dyad working the Dallas-Ft. Worth to Newark scenario (described in Section 5AA.3), however, had difficulty making inferences about the unavailable data. This difficulty was not a result of a lack of expertise needed to call upon the necessary knowledge and experience to make inferences, hstead, their reluctance to proceed by inference and hypothesis generation was probably due both to the complexity of the airspace found in the Northeast Corridor of the United States and to an inherent characteristic of reluctance to simplify interpretations common to actors in high-risk organizations (Weick, etal., 1999). This is a rich example of how the necessary knowledge that is distributed within and among organizations must be brought to bear where decisions are being made. This can be accomplished by assuring that the relevant actors who have unique knowledge and experience, are able to share that knowledge and experience with those responsible for the decision making (Schittekatte & van Kiel, 1996; Stasser, Stewart & Wittenbaum, 1995).

222 5A.5 Effects o f Incomplete Situation Assessment

5.4.5.1 Introduction

The previous section provided descriptions of how the dyads coped with the uncertainty and equivocality resulting from data and knowledge that were unavailable to the problem solvers. In this section, the impact of incomplete or inaccurate situation assessment is discussed. Regardless of what problem-solving or decision-making model one uses, the need for a thorough assessment of the situation prior to solving the problem is undisputed. From Dewey to Polya to Hammond, the first step in problem solving is identifying, understanding, or defining the problem (Dewey,1910; Hammond, Keeney, & Raiffa 1999; Polya, 1957). Simon and Newell’s problem-solving-as-search theory specifies that a problem space is produced from an understanding of the problem (Newell & Simon, 1972). Kast and Rosenzseig (1974) state that the purpose of this problem defrnition stage is to assess the current state as well as the desired state of the system in question. This is often referred to as situation assessment (Endsley, 2000; Kolodner, 1993; Noble, 1993) and is considered critical to the problem-solving process. However, Endsley (2000) reports that errors made during situation assessment occur because even though information is directly available to the problem solver, it is not observed or included in the scan pattern. She suggests that this can be due to several factors, including the failure to look at a piece of information, “attentional narrowing, and external distractions that prevent [the problem solvers] from attending to important informatioh:’i (P-17). A. result o f errors occurring during this assessment phase is formation by the problem solver of an inaccurate,mental model of the problem situation. This inaccurate representatioa could be du& to the problem solver’s expectations that are based on prior experiences. These expectations can lead to an incorrect interpretation of the information or to misidentification of the situation (Woods, Joharmesen, Cook, 223 & Sarter; 1994). They can also serve to activate a schema characterizing a prior event. If some critical features of the current situation do not match up with those in the recalled past event, substitution of these features into the present context can lead to errors in situation assessment (Kline, 1993; Kolodner, 1993; Olson, Roese, &Zanna, 1996).

5.43.2 Examples ofDicomplete Situation Assessment

The data presented in each of the slides used for this study can be thought of as a set of cues about what inefficiencies might be found within each scenario. For the purpose of this study, the assumption was made that a cue is attended to by the partners if one or the other mentioned the cue out loud. Though it may be that those cues not mentioned aloud were attended to, there is no direct evidence to know this. In two of the dyads, the parmers failed to mention aloud certain data which, later in their conversation, was reported as not available (Dyad 1 of the Dallas-Fort Worth to Atlanta scenario), or was replaced by the parmers with erroneous data QDyad 1 of the Chicago to Atlanta scenario). Following is a discussion of these two instances and the implications of the impact that incomplete situation assessment had on the interactions and the task goal.

Example 1: Substituting for data not attended to

In Dyad 1 of the Chicago to Atlanta scenario (Scenario 1), the traffic manager (Tt.i) begins the discussion by referring to data found within the first slide of the slideshow in order to assess the simation. The Erst two turns consist of the parmers mentioning aloud the departure and arrival airports, air fuel bum performance metrics, and air time metrics. What is not mentioned by either partner are the departure dates (May to June, 1998) and the scheduled departure time (1115 Z). Table 5 3 illustrates which conversational turns contained what cues that were spoken

224 1. - . • -

aloud by the dyad Ce.g., T1 indicates the traffic manager’s first turn at talk, and he mentions aloud the departure and arrival airports m this turn). The shaded area indicates the categories of data that were not spoken aloud. Figure 5.23 presents a picture of the slide that the dyad is viewing during the following interaction.

5 AxFweBum Uncot Obi| 9,192.4 njSaO 2.475S 2S9XA f AiTin«Uncon.ri:&1______80,4 22 A(FueEURiUncan:||bt) H AiTroUneacfmwl 120 ISOtA

Figure 5.23. Slide that the Dyadu partners are viewing while discussing scenario using an incorrect arrival timefirame.

225

r AII-Flight-lnsionccs Metrics Holding-Instances Metrics No-Holding-lnsiances Metrics Departure Aim ort ; Air Fuel Bum A ir Time Air Fuel Bum A ir Time A ir Fuel Bum A ir Time » » * » » % Dept Arr Tola! Plan Acius Piff Difr Plan Actual Diff Djtr Total Plan Aciu> Dirr Ditr Plan Aciua PUT PUT Total Plan Actui Pitr Pitr Plan Aetna Pitr Pitr 0 T1 T1 0 PI PI oi 0 0 P 2 P2 0 n T5 0 0 U|7 017 017 Table 5,5, Scenario 1 - Dyad 1 ; Departure Dates and Time were parameters that were not mentioned aloud by the dyad

226 The dispatcher D t.i asks a general question of the traffic manager (I.e., “What effect does traffic coming in from other places like DFW have on Chicago traffic - when you have a volume problem from Chicago?”). This prompts the traffic manager to call to mind a particular timefirame whea difficulties arise due to increased traffic from Chicago as well as from the West Coast.

Tpi 6 : There’s one push every afternoon^ Eastern Time it’s 3 p.m. to 4 p.m. All West Coast traffic comes ia and we also get a lot of traffic coming down from Chicago, and there’s like 42 arrivals over Rome during that hour. Traffic is coming from Dallas, a lot of times we will reach out here, say around even west of Dallas and maybe pull 4 to 6 aircraft south to Meridian/La Grange. What we’re doing is not that they can’t handle them over Rome, but there’s such a volume Issue in this one sector, it’s called Rocket Sector, which is 24 to 43. It’s just more volume that they can efficiently blend to get in trail to go to Atlanta terminal areas.

The result of recalling this particular timeframe (i.e., 3 p.m. to 4 p.m.), allows the traffic manager to build a schema of the situation using the timeframe during which traffic volume routinely presents challenges. He now uses, in place of the departure time data presented in the slide, the arrival time within the schema he has called to mind. This timeframe is used for the rest of the discussion of Slide 1. The dispatcher does not correct the traffic manager, or give an indication that he is aware that the scenario timefiame (which is a departure time of approximately 6:00 a.m. CDT - displayed on the slide as 1115 Zulu- arriving into Atlanta in the 8:00 a.m. EDT timefiame) is different than that being used by the traffic manager. Thus, the discussion proceeds with both partners using the 3:00 to 4:00 p.m. EDT Atlanta arrival push as if it is the timefiame In which the scenario is situated.

Di-t?: Is there any way they could route some of that traffic firom Chicago In over that fix, or do you have too much coming in over the northeast? T n 8 : There’s about 41-42 that comes in over Macey. If they come in in fiant of this bunch that comes in over Rome. So - Di.i8 ; So would it be possible to route some of that traffic over Rome, to re-route it over Macey?....

227 Tn9: Memphis, a lot of times, we’ll put that particular push, we put some in- trail on Memphis 15 miles-in-trail. They back that up on Lidy, and I’m sure that’s what they’re doing because they usually come off, there’s six to eight of them kind of in a line. And they spread them out 15-20 miles in trail. Dt-i9: What if you took like 3 aircraft and run all those over Macey, rerouted them over Macey, rather than give them those vectoring delays?.... T,.i 10: The problem is that the air space that they’re cutting across here is real busythat time o f day,.., that’s what we were talking about just before I came in here. The sector right around Volunteer Fix, Victor, X-ray Victor. There’s so much crossing traffic right in that area that we’re trying to avoid that area as much as possible.

The traffic manager’s utterance "That’s what we were talking about just before I came in here” gives additional insight as to why he activated the schema he did. Such cognitive factors as expectancies and priming seem to have played a role in this example. Priming, a well-researched phenomenon, refers to the tendency for frequently or recently used concepts to come to mind easily and influence the way a person interprets new information (Bargh, Chen, & Burrows, 1996; Higgins & Rholes, 1978; Meyer, Schvaneveldt,^ & Ruddy, 1975; Morton, 1970; Rummelhart & Siple, 1974). Expectancies can be a source for selective attention and accessibility to stored knowledge and, as a result, contribute to what schemas are activated (Olson et al., 1996). It may be that the traffic manager was primed to focus on a particular timeframe by the discussion in which he was participating just prior to entering the study environment. This,priming was reinforced when the dispatcher asked him about times when volume problems are encountered at Atlanta. With one of the study goals being defined as detecting problemfs) in the scenario, the expectation of encountering a particular problem timeframe inay have resulted due to priming effects and the problem-solving context The 3:00 to 4:00 pun. EDT was primed, and the context of the problem situation allowed this timeframe to be retrieved from memory and brought to bear on the current problem. This creates expectations for the traffic manager of what he is likely to see, and these expectations then guide the attention

228 process in a deliberate search, which may have then led to selective attention, resulting in substitution of the expected, timeframe for the scenario timeframe. This substitution then resulted in activation of perceptual schemas through the traffic manager’s focus of attention, which directed his ‘looking.’ Neisser (1991) describes perceptual schemas as “the information that fills the format [of a schema] at one moment in the cyclic process and. becomes a part of the format in the next, determining how further information is accepted" (p.l24). Therefore, expectations and priming are what gave direction to the meaningful looking of the traffic manager that is used in the task. The following contribution by the traffic manager seems to suggest that different traffic management strategies may be used during different times of the day due to the differences in encountered difficulties. This raises the research question as to the direction the problem-solving discussion between the dyad members may have gone, had the actual scenario timefimne been used.

T|.i40: You see, in the mornings we do fine. Our 8 o’clock is pushing in the morning and pretty heavy; it dies off afterward and we can recover. However/paujfi/ after we hit the 3 o’clock push and the 5 o’clock push which is a lot of heavy jets [pause] we have to be very careful how we handle that...we don’t want those 2 pushes to run together.

The traffic manager indicates that the 8:00 a.m. arrival push is one that does not present the same difficulties as the 3:00 -4:00 p.m. push. Had the dyad used the actual scenario timeframe in their discussion, the interaction, content of knowledge shared, and proposed solutions may have been different than what occurred using the substituted timeframe.

Another data category not mentioned aloud by this dyad was the departure dates, which is important for understanding the meaning of the performance metrics, as well as the route data found in the map. The discussion begins with the assumption by the traffic manager that all 27 flight instances are arriving on the same day at the

229 same time rather than the actual scenario of one flight per day departing ORD at 1115 Z (5:15 ajn. CDT) for 27 days. Figure 5.24 is a picture of the tabular part of the slide that the dyad is viewing, their dialogue, and. pointers &om the dialog to the referred-to parts of the table.

»irh i s< h Summ.ijy MiijhM 1 hlr-fHi.iuO*» 1 m Di.ll: .„it’s....27 flights, and uh, it looks Like 22 of them operated normally and 5 o f them held.

Tm2: Which is about average

for a normal push. , AirrudButnUnBn.9bi) &192L4 AtTimeUneontlpiinL @14 J0a2 AiFUfiunUneaitlbil 11114 111614 AdTimmllnrm fmN Wit 9 l t

Figure 5.24. Incorrect assumption due to incomplete situation assessment.

In the following exchange, the traffic manager asserts that for the particular push they are discussing (which is actually his schema-driven time rather than the actual scenario time), there are 27 flight instances over the Rome fix—the 27 from the scenario. However, the reality of the scenario is that for any particular day during the scenario timeframe, there is one flight instance over the Rome fix for this particular airline. So it is uncertain whether 27 is chosen as the number by the traffic manager because he believes that is what the scenario is telling him or if, in fact, he is basing it on his experience of traffic at this particular fix for the timeframe he has in mind.

T n 5 : ....we've got 27 over Rome, and they have 40-42 over on the northeast comer [i.e., Macey], and possibly 27-30 on the two south fixes. Ti-i6 : ....There’s like 42 arrivals over Rome during that time. / ' [utterances omitte(fl '

Ti.iS: There’s about 4M 2 that comes in over Macey. If they come in in finnt of , this btmch that come in ovecRome.... 230 D n9: What if you took like 3 aircraft and run all those over Macey. ...rather than give them those vectoring delays?

Ti-i38: ....this is the problem everyday on the same thing....5 airplanes is not so uncommon to hold for a decent push.

Because the mental model the traffic manager is using was built from his mistaken assumption that all 27 ffight instances are occurring on the same day at the same time, his conclusion is that to have only Kve flights encounter airborne holding during an arrival push is a good statistic. This then can distort the dispatcher’s mental model of what are the real factors during this particular time frame affecting his airline’s flights each day.

Example 2: Data not attended to in situation assessment phase assumed not to exist further in discussion.

In Dyad I of the Dallas-Ft. Worth to Atlanta scenario (Scenario 2), the traffic manager and dispatcher engage in an assessment of the situation by referring to data found within the first slide of the slideshow. The first six turns consist of the partners mentioning aloud the departure dates and times, departure and arrival airports, filed route, and air fuel bum performance metrics for the total number of flight instances, as well as for those flight instances that did and did not experience airborne holding. Table 5.6 illustrates which conversational turns contained the spoken aloud cues presented in the visual field of the dyad (e.g., D l indicates the dispatcher’s first turn at talk, and he mentions aloud the departure dates in this turn). The shaded areas indicate the categories of data that were not spoken aloud. For the next three turns the dyad partners discuss strategies to use to reach the task goals. They also spend some time attending to the map, discussing the routes that the flight instances actually flew, and proposing hypotheses for these deviations fixim the filed routes. What is never mentioned aloud in this part of the task were the

231 ■ : : - ■■ -

air time metrics associated with the flight instances. In the following interaction, the dispatcher raises a question about air time;

D2.1I2: But it doesn't really say if {pause} let’s see, they [the flights that did not incur airborne holding] had less of a [air fiiel] bum. Is there anything that says the time that it took? Ti-tlS: No. No. We doa’thave— all we have on this data here.

The traffic manager responds to the dispatcher’s question about air time by stating that the only data they have available to them is what they are viewing. He goes on to re-state aloud the arrival and departure airports, the number of flight instances that did not experience airborne holding, the percent difference between planned and actual air fuel bum for these instances, and the number of flight instances that did experience airbome holding. What is interesting is that, during this interaction, the airtime performance metrics are available within the same focal area as the other metrics mentioned aloud yet are still not included as part of the data set (see Figure 5.25).

T m 13: It indicates that for the most part, to me, the flights out o f DFW to Atlanta, when we were looking at 272 flights that are going without holding, and I don’t know what industry standard is or acceptable, but 8.1%, I wouldn’t think would be that high when you figure in the weather and the cost of rerouting for fix balancing or (?) concerns. So the 42 flights that we have there during that time period would be the ones we would need to adjust.

42 AtFueBumUncacdal 1303.8 11.411.3 21021 22EXA ( AxTineUncoKtnml 315 12U1 2U8 2U7X4 } 272 AcRaBumUtnatM 1054.3 1788S 7348 11% & \ AirmUncoKttnnl 314 101.1 1.2 1.7% & 1

Figure 5.25. Illustration of selective sampling of data already considered.

232 As a result, what may be important data for a more complete identification of the problem is not noticed. It is possible that if the air time metric for the flight instances that did not experience airborne holding (i.e., on average, the difference between the planned and actual airtime was 1.7 minutes) had been compared to the metric for those that did encounter airbome holding (i.e., on average, the difference between the planned and actual air time was 20.7 minutes), the dyad partners might have explored other possible explanations for the increase in air fuel bum for those flights that did not experience holding (On average, these flight instances had 8.1% increase in air fuel bum than was planned). This further exploration might then have led to more knowledge sharing and, in tum, to the generation of more altemative solutions to the problem than the one they proposed (i.e., adjusting arrival schedules). The research literature on selective sampling provides a possible explanation for this omission. This research states that where a group discussion previously considered certain data, that data has a greater probabiliQr of being re-considered than data that was not previously considered (Larson, et al., 1995; Nye & Brower, 1996; Strasser, et al., 1989). Also, Bmnerand Potter’s (1964) work on early hypothesis formation and its inhibitory effect on recognizing what is actually on the slide may apply. This fixation on an earlier situation assessment appears to result in a commitment to the partners’ original hypothesis which then guides their search for additional evidence (Bower, Black, &Tumer, 1979; Dailey, 1952), leading to a failure to revise by taking into account other data that is present but not attended to QDeKeyser & Woods, 1990; Johnson, Moen, & Thompson, 1988)

233 I: . !■: / -

AII-Flight-lnstanccs Metrics ttolding-lnsianccs Metrics No-Holding-lnstonccs Metrics Dcnanure Airport Air Fuel Bum Air Fuel Bum Air Fuel Bum m a B w r n i n : t m RIet) » % % PutM TinKi Dept Atriv itoMle Total Platt Actiti Diir Diff Plat, Actiti pitr Diff Ran Actiti Diff Diff Ü 9 T l ii » II D l S a#i i T2 T2 T2 n T2 T2 T2 1 m 1 11 T3 j > S «mits ^ W T4 M M! i I T5 I Ü # ### ■' : : I t MB 1 f i t M wm tl 1 IIfit11 # IIiK ifit 1 UH 1 T il 1 1 T I3 T I3 T I3 HB1 Hi r i 4 T I4 f i t Ü « tl ü K R si T20 ■s*

D24 F25

D26 P27 arsissiav T27 ( t ir Table 5.6. Scenario 2 - Dyad I : Air Time was not one of t tie parameters that was mentioned aloud.

234 5.4.5.3 Summary and discussion

The first example in this section described a situation where the dyad partners failed to identify all of the relevant features of the current situation. Because of this failure, the case or schema that was retrieved from the traffic manager's memory contained data that was different from the data in the task scenario. This difference was not noticed by either partner in the course of their problem solving. As a result, the dyad uses the case that the traffic manager retrieved from his memory. Larkin (1989), in his discussion on display-based problems, refers to this as a parsing error because it results from the reasoners building an internal representation of the situation without capturing all of the important features in the display that define the current context. There are several hypotheses that can be entertained to explain how it happened that through the conversation neither partner noticed the discrepancy between the verbalized time and the time displayed in the slide.

Cue Salience. The research literature on the salience of cues is an important area to examine. In looking at the data available in the Search box of the slide, it was only the arrival and departure airport data that was mentioned aloud by the partners (refer to Table 5.6). It is possible that this data was gathered by the partners from the map portion or the tabular parts of the display and not from the Search box. Figure 5.26 indicates the three parts of the display where the dyad could have focused when determining the arrival and departure airport data. It follows firbm this observation that the Search box may not provide a sufficiently salient representation of the data contained within it, which in tum may > ' Si' have led to the lack of attention paid to this data by the dyad.

235 Search box

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Atlanta

Figure 5.26. Alternate sources for determining arrival and departure airports.

Priming and expectations. As discussed earlier in this section, the possibility of retrieving the wrong case from memory (i.e., using a different arrival time than the scenario timeframe) is increased when the current situation is not completely assessed (i.e., the departure time data was not mentioned aloud, and thus, assumed not to be attended to). Also, priming by an earlier conversation and expectations of what will be seen, can lead to the activation of the wrong schema (Chen & Burrows, 1996; Olsoa et al. 1996). This schema may then direct attention and memory, causing some data to be noticed and remembered and others to be ignored or forgotten (Pruitt & Camevale, 1993). Information that is easily processible. Another factor that could influence whether available data is noticed and subsequently used is whether it is easily

236 processible (Schfâde &.KIèrnmuntz, 1993; Slovîc^ 1972). The fact that DepartXime is contained within a string^of data and not easily discernable, and that fact that arrival time must be projected and calculated based on that data may have contributed to the dyad focusing on a different time&ame than found in the scenario. Even though other dyads in this study failed to completely assess the situation in their scenarios, their actions did not contribute to possible negative effects in their problem solving. Appendix E includes the data assessment tables for these dyads and suggests reasons why the incomplete situation assessment may not have led to critical errors. What is suggested by the findings in this section are the following:

• The importance of a complete situation assessment by noticing and using the data necessary in the presenting situation

• The way the data is formatted and displayed, i.e., its salience and easy processibility can be critical to the accurate assessment of the current situation

• An understanding of how the fixation effect can lead to a failure to revise, as well as knowledge of the well-researched sampling effect and the efforts needed to overcome there-sampling bias by being open to discover and “see” data that is present but not previously considered

• An examination of where in the system brittleness many inhibit successful decision making (e.g., whea a partner accepts the timeframe that his other partner uses in discussion of the scenario instead of noticing the actual timeframe and repairing the conversation).

237 -

5.5 Barriers (Designed into the Artifact) to Problem Solving

5.5.1 Lack o fsalience

Data that lacks salience can lead to inaccurate situation assessment. An issue arose in the analysis of several of the dyad interactions about whether data considered important (as determined by the researcher) to the problem-solving effort was sufficiently salient for the participants to notice. Following are two examples of where salience may have beeu a factor in the not-noticing of relevant data.

Example : Dallas-Ft. Worth to Minneapolis-St. Paul - Dyad 2/Slide 1; One of the dyad partners incorrectly identified the departure time in the scenario as zero Zulu when, in fact, flights with departure times for each 24 hour period were included in the scenario.

T3.22: Departure time was zero Zulu... D3.:2 : ...it looks like a pretty much straight shot from Dallas to Minneapolis. TmS: ...Some of the constraints I see....is the time of day. i m Se.Mchk :ch Sumnxiiv 1 iIimI Routr j]

5 '

oemtbsiu

Rgure 5.27. DepartTime metric is divided between two lines, leading to an inaccurate assessment of the situation.

Figure 5.27 illustrates how the format in which the data is displayed is an important consideration in the design of cognitive aids. Because the Departure Time

238 metric found in the Search box is divided between two lines, the traffic manager read only the first line with no indication that he noticed the ‘to 2400’ part of the metric.

5.5.2 Data in the Wrong Format

Requiring calculations on the data can add to the cognitive load of the problem solvers. Some data required calculations by the dyad members to be usable, and this often resulted in errors being made.

Example : Dallas-Ft Worth to Atlanta; Dyad 1

While viewing slide 1: □mm

m 42 A

Figure 5.28. Comparing fuel usage across conditions.

T2.[27: but when you look at272 flights went unencumbered. They went to the airport with no holding and landed, and they still burned 8.1% more fuel. And when you factor in the holding you are only up to two additional percent in fuel. That’s a lot, 1 guess, when you take two percent of 314 flights.

What is interesting about the previous utterance is that earlier in the conversation, the parmers remark about the fact that 8 .1% increase in fuel was very little and did not need any further conversation. Something about how the data was

239 looked at and processed, in light of other assessments they had made after the first remark leading up to this one, caused them to decide that, in fact, an 8 .1% fuel increase deserved more discussion.

While viewing slide 2:

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Total FueB urft»! i3sono I4.70n0 ooao S8% Tm36 AitTineUncontnml loao iiao ISOISO*

Tanlnlninsl 7.0 so -206% TanQuKinintl 125% , ' *** D 2 - i4 0 Q u trira m C 2000 so oifriM0 ' a m O nTinem lao InTm eg] .Q220S2 ,1K 0

Figure 5.29. Converting times from Zulu to EDT.

T:.[36: f m looking to see departure time, arrival time is 2208. Uh, is this Daylight Savings? It’s May, so this is Daylight Savings, so that would have been eight minutes past four locally here. That is an extremely busy time for us here. We’re at the peak of our afternoon push that is the busy push that we have, right there.

[utterances omitted}

Di.i40: I would imagiiie that it would probably the traffic at DFW. He’s leaving at 15— T2.i4 l: 2000Z. But actually back then it would have been 1600, but yeah, yeah, at yoiicehd it would have been 1500.

240 While viewing slide 3:

ifjhf Insidnce

Ait FueSun Uncoit(l»| azm o lo isa o 1.874.0 228%

Total FusBun(fcsl szoao losoao 1.4000 152% AirT>neUncan.lniinJ loso loao 4.0 18%

TaiWiiireJ ao 10 10 •500% r«.'Outfnnl Til —. T»n •10 •200% Outr«ne0 * * t 1305 17.0 It»r«ne0 C ia s y 1908 14.0

Figure 5.30. Converting Zulu times to CDT.

Ti.i44: ...and he arrived here at 2:54 locally....

[utterances omitted]

Tm46: His out time also, if you’ll look at that, 1643 [planned] and 1704 [actual]. Uh, that was pretty high also. Dî.i46: Well, let’s see. Out DFW at 1643 would be around one o’clock. Ti.i: Yeah. Dm : No, twelve. Tm: Yeah, twelve o’clock. Yeah, that’s right.

241 While viewing slide 4:

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FueSur(b»l Unooir-l!«D)_ m = Taalntm ial IT TaaOulfiiiitai lao .dulTnwHL 1732 OffTinegl 17<7 1742 •SO O nT hitgl 195T 21.0 lnTime(Zl & 135E ISO

Figure 5.3 L. Converting Zulu time to EDT.

Ti.i49: ...he was trying to arrive here, would be 15. That's another busy time, right at 3:37 in the afternoon. That’s another flight. Like f was saying, between 3:30 and 4:15 is our peak time during the afternoon.

[utterances omitted]

Dz-i: At the time period, that’s really a peak period too, right?

On slide 2 (Figure 5.29), the traffic manager converted 2208Z to 4:08 EDT, which is incorrect. The actual conversion for2208 to EDT is 6:08 p.m. On both slide 3 and slide 4 ^gures 5.30 and 5.31, respectively), the conversions were done correctly. The conversion error on slide 2 is surprising because the both the traffic manager and the dispatcher work with both Zulu and local times in their everyday work. Also of interest is that the dispatcher did not correct the traffic manager’s mistake. This suggests that because the conversion between Zulu and local time is not automatic and takes cognitive resources it is a potential source of error. This type of error could lead to the participants calling tomind the schema for what traffic is like during the time they are to be discussing rather than the actual timefirame of the scenano.

242 5S.3 Limitations o f One-at-a-Time Sequential Views

The disadvantages of not being able to view more than one slide at a time became apparent in a variety of ways. Generally what sequential views made more difficult was the ability to use data found on one slide to aid in inferences being made on another slide. The problem solvers can access data on previously viewed slides in several ways. Two of these include the following:

• Navigating back andforth between slides. The participant must navigate back to the slide that contains the data he is trying to recall, look up the data, he wants, and then proceed back to the slide he was originally on when he desired the data. Doing this requires the participant to remember which slide the data he wants is on and then once he has that slide in hront of him to remember what data he wanted to capture and why. He then must remember this data when he arrives back at the original slide that prompted the data search as well as the context of the conversation in which the search for the data was prompted.

Recalling frorit memory. Another way that may require less time and physical effort but has a greater potential for cognitive error is the recall of data from a previously viewed slide from the participant'^s memory. Following is an example where this remembering failed:

243 CSLANI lEdjtüi)

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Figure 5.32. Slide 2 of Scenario 5 - I toEWR

While on slide 2 (Figure 5.32), T;., refers inaccurately back to data on slide I (Figure 5.33).

Tj.tll: ...And he lost, uh, what, 40 minutes en route there, somewhere, and 40 minutes. It’s about right. Right &om the other slide it looked like they lost an average ofbetw ^n30 and 40 minutes when they didn’t have to hold for Newark.

h H | Ax FudBun Uncoo: (bs| 23.1213 24J47.3 7.SKA AxTir* Uncut [mml 17C0 18S0 STXA At FudBun Unccm (bit 218618 218010 2 1 » A. AtTine Uncut (n*ii 1610 2116 47.B 213% A

Figure 5.33. Slide I of Scenario 5 - DFW to EWR

This finding suggests that, in order to reduce the cognitive load of remembering and running the risk of inaccurate remembering, improvement in the design may be needed that reduces reliance on the user’s memory. 244 5.6 Overall Discussion of Findings

The analysis of the data in this investigation explores the unique knowledge that was shared between dyad partners and the solutions they proposed for jointly identified problems as they engaged one another in the research task. The data also allowed for investigating how the use of cognitive artifacts provided an environment in which the partners could collaboratively build a common ground by sharing perspectives and establishing mutual understanding. The results discussed in this chapter indicate that through the use of the shared display the dyad partners were able to make references to objects in the slides rather than having to rely solely on their spoken words. With the shared display, use of deixis, and through the use of stories and analogies, they were able to arrive at a common assessment of the situation and to provide explanations from their unique perspectives of the events they perceive. The research findings also suggest mis-steps that occurred in the problem­ solving episodes that can be attributed either to weaknesses within the distributed cognitive system or to the processes or strategies employed by agents in that system. These weakness are discussed further in the Conclusions chapter of this paper. The results of this analysis document observations and implications for distributed work among interdependent, inter-organizational teams in a complex problem-solving environment. These are explicated in the next chapter of this paper (Chapter 6 . Conclusions)^ * ‘

245 CHAPTER6

CONCLUSION

6.1 Introduction

The findings of this study are a result of investigating several interacting phenomena that are often studied independently. This has been an investigation not only of how two people come together to solve a problem but also how these two people, who are spatially distributed, are able to collaborate with one another through the use of interaction technologies. The use of this technology allowed the study of human-computer interactions, as well as human-computer-human interactions. The problem-solving activities of the participants were made possible through the collaborative process of communication. Within these communicative interactions, the dyad partners engaged in an exchange of domain-relevant knowledge that allowed the team members to better understand the interdependence between their roles in Air Traffic Management System.

Tools. The analysis illustrates how the difiërent modalities made available by the interaction technologies both enabled, and constrained the cognitive process of the problem solvers. These technologies enabled the problem solving activity by making available the objects of work (Le., the data within the problem scenario) and by supporting the conversation surrounding those objects.

245 These artifacts also constrained the interaction because of limits placed oa their design (e.g., not all needed data was available) or because of technological inefRciencies (e.g., limited bandwidth). Because audio communication is ephemeral, the participants did not have available to them something that could serve as an external memory of their interaction-in-progress. Human memory is faulty, making it difficult to recall, in an error-free way, data and knowledge that has been shared. Without the ability to easily review what has been said, ideas that were mentioned in passing were not revisited, and thus, not explored for their relevance or contribution to the problem-solving activity. Also, in-process decisions, explanations of reasons why certain solutions might not work, and conclusions that were made were often lost as the discussion progressed.

Context. The situated context of the interactions must also be considered in how the collaborations unfolded. The dyad partners were from two different organizations, with complementary as well as competing goals. The relationship between these organizations has not always been one of collaboration. Their roles, responsibilities, goals, constraints, and procedures differ. What accompany these differences are the different perspectives that each take in considering problems and their solutions. Complicating the interactions further are the differences that occur at the individual level within each organization. The study of inter-organizational teams is not new (cf. Levine & White, 1961; Litwak & Hylton, 1962). However, this research differs somewhat from other studies of inter-organizational collaborations because of the characteristics of the high- reliability organizations being studied here and their inherent, ongoing relationships. Thus, the challenge to the partners of the collaborative teams formed for this study reach beyond the problem-solving task assigned to them ia this study. The aviation system is a high reliability organization in which the organizations that compose the systems are interdependent in providing a safe and efficient environment for the customer to use. It is not the threat of competition with

247 other service or industry providers that bring the FAA and air carrier organizations together. The threat that is conunon to these organizations is one of customer safety. The threats to the business goals of the air carriers, as well as the safety of their passengers as air traffic increases, provided the impetus for these organizations to search for ways ia which collaboration among the organizations within the ATM system could be established and produce mutually beneficial results. As a result of these motivations, the organizations have realized that a collectively optimal outcome of particular situations occurring in the NAS requires mutual cooperation and collaboration by the FAA and the air carriers as they attempt to maintain the goals and priorities of each. The remainder of this chapter speaks of issues specific to the aviation community, the findings of this study as they relate to aviation, and provides an evaluation of the artifacts used by the participants during their problem solving. In addition to the domain-specific discussion, the findings as they apply to distributed collaborative work environments are considered. Design suggestions for facilitating distributed work are offered. These suggestions include features for tools to aid and mediate the interaction between human agents, as well as process design features that support more effective collaboration. Finally this chapter offers questions to be answered by future research.

6.2 Issues Specific to the Aviatiou Community

6.2.1 Characterization o f the Aviation Research Context

The design of the Air Traffic Management (ATM) system is highly distributed with command, control, and communication responsibilities spread across a large number of FAA organizations and air carriers (see Chapter 3 Research Context), hr order to reduce the cognitive complexiQr with which each individual

248 participant must cope, tasis are assigned so as to limit the amount of data and knowledge that each individual is-expected to access and process directly. An example of how a task is decomposed to reduce cognitive complexity can be found in the Traffic Flow Management (TFM) component of the ATM system. A major task of TFM is pre-flight and traffic flow planning in an uncertain and dynamically changing environment. This overall task of selecting safe routes of flight for aircraft and of operating these aircraft is decomposed so that each of the participants (i.e., pilots, ATC controllers, AOC dispatchers, and FAA en route traffic managers) has full knowledge of how to perform their particular subtask, but has only partial knowledge of other factors involved in pre-flight and traffic flow planning. Traditionally, TFM has been primarily a function performed by the FAA, with traffic managers at various facilities making decisions about what routes could be flown by flights scheduled by the airlines. As a result, both access to necessary knowledge (about traffic flows and congestion) and the locus of control were located with the traffic manager. However, this decomposition meant that decisions were sometimes made that did result in the most efficient operation as viewed fiom the airline perspective. Today, changes in the architecture of the NAS (known as the National Route Program ^AA, 1995)) have resulted in a paradigm in which route selection is under primary control of the airlines. This control allows the airlines, subject to certain constraints, to simply file with the FAA the routes that they prefer for particular flights. The FAA traffic managers monitor conditions, watching for situations (such as severe weather) where the program has to be cancelled temporarily for particular portions of the country. This architectural change in the NAS has significantly altered the traditional task decomposition, requiring airline dispatchers to now consider factors (such as prediction of air traffic bottlenecks, and traffic in other parts of the airspace) that in the past were handled largely by FAA traffic managers. This paradigm shift has changed the locus of control fiom traffic managers to airline dispatchers. Dispatchers now have more control to determine the routes to be

249 filed but are not provided with direct access to the data and knowledge necessary to evaluate alternative routes in terms of efficiency of traffic flow. Strategic problems exist currently in TFM because of the highly distributed nature of knowledge and because new patterns of communication with traffic managers have not been adequately established. This new architecture of the ATM system blurs some traditional divisions of responsibility and it is notalways known to the agents in control when a knowledge-seeking interaction is necessary and where to seek that knowledge.

5.2.2 Aviation-Specific Findings

6.2.2.1 With the changing architecture of the NAS, decision makers are operating under a “control-by-exception” paradigm where access to requisite knowledge often is not coincident with the locus of control.

The AOC dispatcher, under the control-by-exception paradigm, has control of decisions about what routes his flights will use, but he does not have systems-view knowledge of how these flight plans will impact the airspace through which his aircraft will fly. Without this requisite knowledge, these plans often result in less efficient flights (in terms of fiiel usage and time) for the dispatcher’s airline. These flight plans also may negatively impact other airlines’ efficiency. Even more importantly, the safety of the NAS could be impacted by creating greater workload for the controllers and traffic managers responsible for the flight of all aircraft in their particular airspace.

250 Knowledge Sharing. As the participants engaged each other in their problem­ solving task, the dyad partners shared rich domain knowledge. This knowledge includes the following categories.

1. Strategies traffic managers use for handling airspace congestion. These strategies include:

■ Balancing arrival fixes ■ Placing miles-in-trail restrictions on aircraft ■ Re-routing aircraft to avoid congested airspace, to reduce congestion, or to avoid a weather event • Vectoring aircraft as a means of delaying them from entering congested airspace ■ Separating aircraft by altitude to reduce sector controller workload

2. Constraints with which traffic managers must cope, for example:

■ ConBguratioa of the arrival airport, which determines aircraft arrival routes

■ Airport arrival rate

■ En route traffic crossing over arrival and departure traffic

3. Priorities and constraints the airline dispatchers must consider include the following:

Strategies pilots use in order to avoid getting into a minimum fuel situation (e.g., diverting to an alternate airport)

Federal Aviation Regulations ^ARs)

Determining which strategies are most efficient for reducing delay due to congested airspace (e g., ground delay versus airborne holding)

Satisfying întra-orgamzational differences as they pertain to on-time performance and fuel usage 251 Solutions Offered. This knowledge sharing occurred as the dyad, partners explored a number of potential solutions to deal with the problems identified in the scenarios. These solutions include the following:

1. Changing arrival fixes in order to balance the traffic flows between fixes;

2. Delaying aircraft on the ground at the originating airport as a way of minimizing en route delays;

3. Improving real-time communication and collaboration between the different organizations in the Air Traffic Management (ATM) System (e.g., AOC dispatchers, ARTCC traffic managers, and ATCSCC personnel) to arrive at more effective tactical decisions;

4. Routing aircraft on alternate routes to avoid weather events or traffic congestion;

5. Separating or LADDRing arrivals and departures to reduce controller workload in affected sectors and in effect reducing delays;

6. Adjusting arrival schedules to avoid peak arrival and departure pushes at the destination airport;

7. Utilizing airports close to the currently scheduled destination airport to reduce traffic congestion and resulting delays;

8 . Increasing the flexibility of the airspace by dynamically redesigning it (e.g., moving arrival fixes when weather is impacting the airspace; sector redesign to reduce delays due to controUerworkload).

252 Ô.2.2.2 Processes for identifying what knowledge is needed, its source, and how to gain access to it are currently inadequate for effective decision making in traffic flow management.

There is, in general, for routine pre-flight planning, no process or procedure that aids the decision maker in understanding when more information is necessary, and what that information is, and how to access it. Also, at the present time, the processes for disseminating the requisite knowledge to individual dispatchers and traffic managers who have control of particular decisions are inadequate. Complicating this situation is the fact that the work of air traffic management occurs in a time-constrained, real-time environment where temporal events are dynamically unfolding. So, even when the decision maker has identified the source of the requisite information, the pace of this distributed work environment does not always allow for unpredictable interruptions that real-time access would require. Unlike situations where collaborators are spatially and temporally co- located, the distributed context of many high reliabilify organizations does not lend itself to the initiation of mutual engagement, the collaborative partners do not have access to looks, body postures, gesturing, touching, or other physical means of gaining another’s attention. Currently in traffic flow management, the processes forgetting real-time access to the person who has the necessary knowledge are inadequate. Therefore, how this real-time access can occur effectively is a challenge that needs further exploration in future research.

253 Ô.2.2.3 An incomplete understanding of organizational priorities and constraints and of the different perspectives and preferences that exist within the collaborative dyad often Ted participants to make inaccurate assumptions, which in practice could lead to decisions that result in inefficiencies and/or undesired consequences.

Often AOC dispatchers and FAA traffic managers lack an understanding and knowledge of the roles, responsibilities, goals, constraints, and procedures of their inter-organizational parmers. Knowledge of the different perspectives and preferences held by their collaborative partners is necessary to make effective decisions.

Organizations have Different Perspectives on Impact of Solution. There is a. wide range of potential solutions to deal with traffic congestion and weather constraints, and the affected organizations have different perspectives as to how effective each solution will be and how to implement the solutions decided upon. To further complicate this issue is that the preferred solutions are dynamic and changes in external conditions (e.g., the price of fuel) may influence the position an organization takes for a solution at any given time.

Individual Preferences among Organization Members. Even at the level of individual members of an organization, different perspectives are held on what strategies to use in a given situation. There are large individual differences in preferences expressed by specific dispatchers, making it difficult for traffic managers to decide how to best incorporate an airline's priorities and constraints in making decisions.

254 6.2.2A The tools used by the participants to mediate and facilitate their interaction can serve as cognitive aids for establishing common ground and building shared perspectives.

Through the use of the shared display of the problem scenario, a telepointer, and two-way audio communication, the dyad partners were able to collaborate on their problem-solving task, establish common ground, and build shared perspectives. The contributions that these artifacts offered include the following:

• The shared visual display provided a base on which the participants were able to ground their verbal conversation. This display provided data about the scenario in both tabular and graphical forms. It allowed the participants to make references using deictic gestures, geographical locations, and those based on community co-membership.

The telepointer allowed the participants a means with which to interact with the shared display, provided the ability to use deictic gestures by way of pointing and enabled the participants to establish and maintain a mutual focus of attentipn.

The us&of the cognitive artifact provided a means for establishing a virtual copresence (enabled by the physical copresence of the display with each dyad member and the linguistic copresence established through use of the telephone). This artifact enabled participants to refer to the objects of the conversation through both gesturing and spoken generalizations and to maintain the situational context within and about which they were interacting.

# The telephone provided a means for establishing linguistic copresence, and allowed the partners to share analogies and stories through a medium with which they are comfortable interacting. These stories, in turn, enabled the parmers another means to build a shared uncferstanding of the current 255 situation, to diagnose the problems to be solved, to verify understanding of knowledge shared by the partner, and to increase their knowledge about particular situations occurring in the NAS.

6.2.2.S Factors not considered by designers of the technologies used in the interactions contributed to inaccurate situation assessment and problem identification.

Certain factors in the shared display appeared to contribute to the dyad partners inaccurate situation assessment and problem identification. These factors include the following:

• Cue Salience. Certain data in the display (e.g„ departure time and dates of the flights in the scenario) were placed in such a way that they lacked the salience to be easily noticed by the dyad partners. By appearing in the Search box that was placed apart from the other data on the slide, in addition to being in a text string of data rather than displayed in a way that would allow attention to each individual datum, this data was often not attended to by the dyad partners. When this inattention occurred, inaccurate situation assessment and problem identification sometimes resulted.

• Data Form. Some of the data (e.g., departure time) required the participants to do calculations on it before it was in a useful and useable form, and this often resulted in errors being made. Such manipulations included converting arrival and departure times displayed in Zulu (i.e., Greenwich Mean Time) to military or local time. Erirors in these conversions often caused the partners to situate the scenario in the wrong timeframe, which then led to solving what may have been the wrong problem^ 256 6.22.6 Participants bring with them to the interaction expectations based on prior events.

The expectations that participants brought to the problem-solving task, in at least one case, led to an inaccurate assessment of the problem situation. The traffic manager, having been primed just prior to the study session by a conversation about air traffic problems occurring at a particular time of day, fixated on a timefirame that was different than the one on which the scenario was based. This resulted in an exploration of alternative solutions and an exchange of knowledge that may not have been accurate for the scenario timeframe.

6.2.2.7 A lack of a defined process for the dyads to follow in their problem solving often led to a lack of focus that resulted in a lack of closure.

Without a process to follow, the dyad partners often did not discuss or evaluate alternative solutions after proposing them, and did not proceed to choosing a “best” solution from the alternatives generated. Often one dyad partner would begin a discussion of a particular strategy, and the partner, thinking along different lines, would shift the topic to his thoughts. This resulted in the other partner losing focus of his topic, and usually it was not revisited. Providing a process under which to proceed would likely result in a the dyad returning to briefly mentioned or partially discussed topics, leading to closure on the topic as well as the possibility of reaching a more effective solution.

6.3 Evaluation of Tools^ Used ia Present Study

The analysis of the tools and cognitive artifacts used by the participants in this study (i.e., the shared cüsplay,. telepointer, and telephone) allows exploration of the following questions; 257

.. .. : y . .. L What did this technologyallow the participants to do that they couldn’t have done otherwise?

2. How did these tools support communication intensive functions that are already in place?

3. What limitations did this technology impose on the interaction?

Table 6.1 presents the results of the evaluations of the artifacts used by the participants in this study. These include the telepointer, the slideshow, and the telephone.

6.5.1.I Telepointer

The telepointing feature aided the directing and tracking of the partner’s attention, and enabled referring using deictic gesturing, which supported the focusing of attention on a specific part of the visual context. This tool also contributed to the development of shared perspectives and supported communication between the parmers as they engaged in the activities of interpretation, explanation, clarification, and repair of misunderstandings. However, the telepointer did not provide affordances that would allow ease in the partners sharing its control. It is uncertain what, if any, impact there was on the content of the discussion with only one participant controlling the telepointer throughout the interaction.

6 J. 1.2 Slideshow/Shared display

The participants were able to use the shared display as a memory aid. This common display enabled a shared focus or shared reference, which supplemented the

258 spoken communication by providing more cues for the hearer. It also provided anchoring by linking the communication to external artifacts and by helping to focus attention. The display allowed the dyads to refer using deixis and description and provided a foundation upon which the building and rebuilding of common ground could occur.

Some of the characteristics of the slides that may have had negative impacts on the interaction include the following:

• Complex data can add to the cognitive load with which the participants must cope. The participants must make sense of the data they see, inferring relationships, and extrapolating from these data, inefficiencies occurring in the airspace. Each slide consists of complex data both in tabular and graphic forms.

• Lack o f salience can lead to inaccurate situation assessment. An issue arose in the analysis of several of the dyad interactions about whether data considered important (as determined by the researcher) to the problem-solving effort was sufficiently salient for the participants to notice.

The disadvantages of not being able to view more than one slide at a time became apparent in a variety of ways. Generally what sequential views made more difficult was the ability to use data found on one slide to aid in inferences being made on another slide. This finding suggests that, in order to reduce the cognitive load of remembering and running the risk of inaccurate remembering, there is a need to improve the design in such a way that data the partners want to bring forward to another slide is available for them to do so.

Access to necessary data and knowledge was not available. A limitation of the content found within the slides was evident by the many references the

259 dyad partners made about data that was unavailable to them but considered necessary for a complete assessment of the situation and identification of the problem. Data that was identified as unavailable include the following:

• Meteorological data • Actual release fuel • Other traffic in airspace • Intentions of those involved during the actual flight • Airport restrictions

fit most scenarios the dyad partners made assumptions and “filled-in” data for what was missing and then proceeded with their problem-solving task. In one scenario the dyad parmers found the situation too complex to be able to generate reliable assumptions (see Section 5AA Coping with Uncertainty when Data and Knowledge are Unavailable), This finding points to the necessity that when developing scenarios that portray inefficiencies in a part of the National airspace, as much data relevant to the scenario as possible be made available to the problem solvers. It also suggests that the use of more than one source may be necessary to acquire the relevant data. Finally, in the Dallas-Ft. Worth to Newark scenario, it is apparent that not all of the people who needed to be involved in a discussion of the situation represented in the scenario were part of the problem-solving team. Consideration needs to be given toward what decision makers need to be involved in the problem­ solving effort for any particular scenario.

6.5.I.3 Telephone

The telephone allowed the participants to use of a tool that is a ubiquitous part of the work environment for both traffic managers and dispatchers. Because the

260 telephone Is an Integral part of their everyday work, the dyad partners had experience In Its role for problem solving. The use of the telephone provided a two-way spoken conversation that supported communication by allowing the use paraverbal mechanisms (e.g., delivery style. Intensity, phraseology, rhythm), as well as providing the problem solvers the ability to establish linguistic copresence, a critical ingredient to the establishment of virtual copresence.

Even though the telephone enables collaborative communication to occur. It does not provide a permanent record, of the conversatlon-In-process. This transitory aspect of the spoken word appeared to contribute to the participants losing track of threads of discussion.

261 Question Posed Telepointer Slideshow/Shared Display Telephone

Whot Did TiUs Technology • aided the directing and • acted as a memory aid • allowed the use of a Allow the Participants to tracking of attention commonly used tool that is • enabled a shared focus or a ubiquitous part of the Do? shared reference ■ enabled referring using work environment for both deictic gesturing, which • provided anchoring by traffic managers and supported the focusing of linking the communication dispatchers attention on a specific part to external artifacts of the visual context How did these tools • contributed to the • provided the ability to refer • allowed the use paraverbal support comtmmlcatlon development of shared using deixis and mechanisms (e.g., delivery ihtetmvefimctiotis that are perspectives description which required style, intensity, already In place? • supported communication less effort than audio-only phraseology, rhythm) between the partners as they interaction would have • provided problem solvers engaged in the activities of permitted. the ability to establish interpretation, explanation, • provided a foundation upon linguistic copresence, a clarification, and repair of which the building and critical ingredient to the misunderstandings rebuilding of common establishment of virtual ground could occur. copresence What limitations did this • did not provide • complex data • does not provide a technology Impose on the affordances that would • lack of salience permanent record of the Interaction? allow ease in taking • ability to view only one conversation-in-process control of it slide at a time • contributed to participants • access to necessary data and losing track of threads of knowledge was not discussion available Table 6.1, Evaluation of artinets used by participants 262 6.4 Issues for the Design of Distributed Collaborative Work Environments

The previous section has described the findings of this descriptive study in domain-specific terms. In the following, section the discussion centers around how the findings can be more broadly described as they apply to distributed collaborative work environments in general.

6A J General Characteristics o fDistributed Environments

'-r- Traditionally the way that organizations deal with complexity in work is to divide the task of managing the overall system into subtasks, and then to assign these subtasks to different individuals. The assumption behind this division of labor is that there is a sufficient degree of independence among the subtasks, so that when each subtask alone is performed well, the combined effects will produce acceptable (rather than optimal) levels of performance for the system as a whole. Because few systems are actually decomposable into fully independent subtasks, it is often necessary that individuals responsible for particular subtasks interact with one another as needed when the solutions to these subtasks also interact in significant ways. However, the reality is that these individuals may not know how signiricantly their subtasks interact, and therefore will not know when collaboration is needed. Collaborative work can be characterized as a highly interactive endeavor, directed toward some shared goal that requires the presence of team members. When work is temporally or geographically distributed what is meant by ‘presence’ requires some thought and planning as to how it wiH be effectively accomplished. Understanding the mediating effects of the technologies used in the interaction is necessary. Distributed collaborative problem solving and decision making involve the collective effort of multiple problem solvers, combining their knowledge,

263 information, and expertise in order to develop solutions to problems that each could not have solved as well (if at all) alone. The challenge for these distributed problem solvers is to utilize the available technology and processes in such a way that their joint problem-solving activities (e.g., problem identification, hypothesis generation, and alternative solution generation) result in effective solutions. The knowledge sharing that occurs among team members is a critical component to the success of collaborative work since different parts of the solution space reside with the different members.

6A.2 Applying the Findings to Distributed Collaborative Work Environments

The research reported in this paper has resulted in a number of observations and empirical findings that can be applied more broadly to other distributed collaborative work environments. These findings are reported below.

6.4.2.1 For effective decision making, access to relevant data and knowledge needs to be available to those who have decision-making control.

Li a distributed work context, there are a number of situations where the locus of control does not coincide with access to the relevant knowledge for many important decisions. Unlike traditional organizational structure, it is not only the division of labor that occurs when attempting to reduce the complexity of a task. Also occurring in today’s more flexible organizational structures is the division of knowledge into specializations, and complex, dynamically changing environments compel an organization to differentiate its specialties to an even higher degree (Lawrence & Lorsch, 1967). This specialization leads to different patterns of information access and learning (Zuboff, 1988; Galbraith, 1993). As some organizational structures appear to be changing fiom that of management by directive

264

...... - -' A to more flexible and adaptable forms, the flow o f data and knowledge must also change and be readily accessible to those who have decision-making control for specific tasks.

6A.2.2 Identifying the source of relevant knowledge and having a process that enables real-time collaborative interaction and dissemination of this knowledge is necessary for effective decision making.

Identifying the source of knowledge and processes to access that knowledge. hi order for the necessary knowledge to be available when and to whom it is needed, processes that provide to the decision makers not only what knowledge is relevant but also where to find that knowledge and how to access it must be in place.

Real-time access.^to team members. In order to assure that the decision maker has the knowledge he' needs at the time needed, processes must be in place that allow access in a timely way. In many traditional organizations, decision making occurs over time and real-time access is not a critical consideration. However, in high- reliability organizations where dynamically changing events are the norm, time- critical decisions are necessary. Therefore, how this real-time access can occur effectively is a challenge that needs exploration in future research.

6 A .2 3 Incomplete understanding of organizational characteristics and the different perspectives and preferences that exist within the collaborative team can lead to incorrect assumptions and inefficient and/or undesired decisions.

There is often a lack of understanding and knowledge of the roles, responsibilities, goals, constraints, and procedures of each agent or organization that exist within the collaborative team, and unless these are made explicit assumptions are made that may not reflect accurately the current situation, which can then lead to poorer decisions being made. The dissemination of knowledge among team members 265 is critical to reduce the level of equivocality that occurs when gathering members from different organizations to form a collaborative team.

6.42.4 Tools to mediate and enable interactioa can. serve as aids to the collaborators in establishing common ground and building shared perspectives.

An environment that provides a shared visual display with a capability for telepointing and two-way audio communication may ease the effort that a team, engaged in a spatially distributed, collaborative problem-solving task, must use to build shared perspectives. Through the use of a shared display and audio communication the team members have the opportunity to establish a virtual copresence (enabled by the physical copresence of the display with each dyad member and the linguistic copresence established through use of the telephone), which can facilitate the collaborative interaction. These artifacts enable the giving and taking of perspectives, and a free flow of task- and team-relevant knowledge among the members, and a culture of collaborative teamwork.

6.4.2.5 To ensure accurate situation assessment and problem identirication several factors need to be taken into consideration by designers of interaction technologies and practitioners who engage in problem-solving tasks.

To ensure accurate situation assessment and problem identification several factors need to be taken into consideration by designers when building cognitive artifacts. These factors include the following:

• Cue salience. For data that may be critical to notice for an accurate assessment of the situation, the designer must ensure that the data will be 266 salient to the problem solvers. Those engaged in the problem-solving task, in turn, must be vigilant to the determination, noticing, and use of the relevant data available to them.

• Data form. The designer must consider what form the data needs to be represented in order to be useful and useable to the users. If the user must manipulate the data to make it usable, the task will require additional cognitive effort that is a scarce resource in complex, problem-solving environments.

6.4,2.6 The expectations participants bring to the problem-solving task can prime them to fixate on particular assessments of a situation that may be incomplete or inaccurate.

Cognitive factors such as expectancies and priming can influence the search for data during situation assessment. Priming can occur because frequently or recently used concepts easily come to mind and can influence the way a person interprets new data. Expectancies can be a source for selective attention and accessibility to stored knowledge and, as a result, contribute to rixation on particular aspects of a situation to the exclusion of other data that may be critical to an accurate assessment. Fixation errors can result due to a failure to revise in light of additional data or a failure to sample that additional data due to re-sampling bias.

The designers of interaction technologies and distributed collaborative work processes can take steps to reduce these effects by introducing features that help ensure that team members accurately assess the situation by accounting for all requisite data. For example, technology designers can assure that data can be easily accessible, in a form that does not need to be manipulated to be meaningful, and that is salient to the team. Process designers can implement checks that make it more likely that the team members will notice all data relevant to the situation. 267 -r ■

To guard against in accurate situation assessment, team members need co be aware of the expectations that are brought into the interaction in order to guard against being influenced by those expectations to the exclusion of noticing event cues in the present situation.

Ô.4.2.7 To ensure effective and timely problem-solving a process needs to be defined.

In order to improve problem solving in a distributed and complex, data rich environment, providing a process for the team members to follow is likely to result in a more effective solution. Designing such a process may include the provision of a facilitator to help structure the discussion and guide the interaction, or the establishment of communication and interaction protocols that help team members monitor their interactions.

6.5 Future Tool Development

Computer support can be very effective in improving the way in which information is shared among the participants. Technology is needed that can support distributed cognition by enabling individuals to make rich representations of their understandings, reflect on those representations, engage in dialog about them with others, and use them to inform action Roland, Tenkasi, Te’eni, 1996, p. 247). ‘The most important implication of the theory of distributed cognition is that we can design the artifacts and social processes to embody cognition...How do we design the artifacts that support our needs in distributed cognition? How do we understand what is missing when we use certain kinds of technology that affect distributed cognition?” (Olson & Olson, 1999, p. 418) Three classes of tools needed to support teams include communication tools, coordination and managementtools, task-oriented tools designed to facilitate

268

-J- :';v ; • ^ completion and integration of specific work products. With these tools the potential exists to bring out problems explicitly, to encourage communication, and thereby to act as tools for learning (e.g., Casey, 1993; Hague, 1993; Morgan, 1998). These interaction technologies can aid in the identification of cues and the reduction of cognitive load, and can be designed to positively influence situation assessment, helping the human actor to focus attention on important stimuli that might otherwise go unnoticed. Olson & Olson (1999) make the following suggestions when considering the design of artifacts that support distributed cognition. They write that one needs to design the system to aid:

“Short-term memory (e.g., ...after an interruption, asking person we had been talking with to remind us what the topic was)

Calculation (e.g., using paper and pencil to do multiplication....)

Long-term memory (e.g., ....cheerleaders using gestures to orchestrate a cheer)

Attention (e.g., ...a checklist to help us remember all the steps to go through)

# Cognitive representation (e.g., plotting data in a graph so we can visually inspect it and gain insight through perceptual processing)” (p. 418).

Findings of the present study suggest additional features that could further aid distributed collaborative work. These following subsections describe features for collaborative support tools.

269

; V

i .Ç- . 6.5.1 Allow for an interactive search fo r data to support the dynamic problem solving process

Di order to reduce the uncertainty and equivocality of the situation under investigation, it maybe necessary to have more information available than static slides that represent the situation in a particular way. By allowing access to a "live" analysis tool (e.g., POET), to weather data, and other flight data such as altitude, speed, or diversions, there is a much higher probability that the data and knowledge requisite for reducing uncertainty and equivocality and necessary for sensemaking will be available to those assigned to the problem-solving task. Having the ability to use an interactive search tool would aid the user in the following tasks:

• Decomposing data to any level determined by the problem solvers as necessary • Creating different representations of the data that might allow for greater ease in situation assessment • Providing data that problem solvers determined necessary to identify and solve the problem at hand • Eliminating statistical outliers in their search so they could have a more accurate picture of the problem • Managing the direction of their problem solving, determining what clues they feel are important; going to whatever depth of analysis they deem necessary.

However, care must be taken when allowing the problem solvers access to additional features as it is possible to introduce new problems. These can result in the following:

2 7 0 • LiefSciencies due to individuals not completing their work before the group dialog takes place

• Increased complexity due to access to increased (potentially unlimited) amounts of data

• Difficulty in bounding the problem-solving process.

6.5.1 Provide a history o f the interaction so that the problem solvers are able to see where^hey have been to better decide where they need to go

This type of collaborative support would provide the users with a trace of such things as the problems identified, hypotheses made, and solutions proposed. This trace would be structured in such a way that provides a useful representation of the interaction, allowing the problem solvers to dynamically assess their process and progress in their task activity.

6.5.3 Provide affordances in the telepointing device that allow each participant ease o f taking control and using the tool

By providing each person in the collaborative work team the use of a telepointer, each would have easy access to the device that allows virtual gesturing and reference. This feature would allow each to take full advantage of control of telepointer in focusing others' attention, as well as, organizing his or her thoughts.

6.5.4 Allow the ability fo r different representations o f the data which may produce different insights

“The central premise of display-based problem solving is that the external display is the main representation of the current problem state. If various internal goals or annotations are lost, they can always be reconstructed fiom the display” (Larkin, 1989, p. 337).

271 This shared representation can serve as an external memory, which can then mediate interaction through which the team members construct and maintain shared interpretations. Decision makers can be guided differently with different visual representations of the problem. For example tables offer pte-defined information guidance and provide determinatioa of exact data values for computational purposes. To evaluate data in order to determine promising directions in the search for an optimal solution, graphical representations are useful. Assisting functions can be added that empower users to manipulate the data (e.g., by allowing ranks for the criteria, providing percentages across different data items, or converting data to different formats).

5.5.5 Summary

It is probably true that no one tool will be able to meet the needs of evey kind of distributed team as they collaborate to achieve some goal. As Kraut, Galegher, & Egido (1988) conclude there is no single technology that adequately supports the I. collaborative process. Rather, team members will need to make use of a “rich palette” of computer-based tools as they interact with one another across time and distance.

6.6 Process Design for Distributed Collaborative Problem Solving

Designing to enhance mutual understanding and to provide feedback means considering not only the technolo^ that enriches and mediates the interaction, but also the social processes that ernbody cognition both at the organizational and interpersonal levels. The focus cannot be on highly specific electronic tools but on the broader interactive environment of which tools are a part.

272 6.6.1 Combine asynchronous and synchronous capabilities

Because of the high-demand work environments of high reliability organizations such as those that comprise the AirTraffic Management System, the possibility and desirability of having only synchronous interactions between collaborative problem solvers will not be realized. By understanding the environmental constraints that exist in this context, designers of distributed collaborative processes must consider alternative means that will allow the joint collaborative work to occur. Therefore, designers must understand not only what contributes to effective spatially distributed problem solving but also to temporally distributed events. Alleviating the temporal constraints with asynchronous collaboration needs to be explored to understand what are the barriers and opportunities that will allow this mode of interaction to contribute positively to the collaborative efforts of distributed teams. One advantage that asynchronous modes of collaboration provide is that the interactions can be viewed and reviewed as desired, and they can be annotated (e.g., by voice, text, drawing) and sent on to other collaborators. However, difficulties can arise in such systems and include the following:

• They can require large amounts of computer storage and a. wide bandwidth may be needed for effective interaction.

• Problem solving involves a great deal of discussion and joint interaction and the delay imposed by the use of an asynchronous method might well disrupt the task.

• It is less likely that copresence will be established.

• Qnmediate feedback and error correction is delayed or does not occur, which allows for miscommunication to escalate.

273 It is difficult to ensure that common ground and shared perspectives are established.

It is likely that memory-triggering events will not occur with same frequency as occurs in real-time interaction.

Building relationships between collaborators will be much more difficult than with synchronous spoken interactions.

In designing a process that allows for both asynchronous and synchronous interaction, the interface design must provide a seamless transition between the two.

5.5.2 Process facilitation during synchronous interaction

Group facilitation can be defined as any meeting technique, procedure, or practice that makes it easier for groups to interact and/or accomplish their goals (Frey, 1995). In order to help structure the discussion, a human facilitator or some structured process is necessary. The role of the facilitator is to guide the process, without engaging in the content of the task at hand. He or she does guides the group members in applying various tools for problem solving. The facilitator may also record the alternatives that are generated, factors considered in their evaluation, and reasoning behind why certain alternatives were chosen and others were not.

6.6.3 Communication and interaction protocols: Establishing conventions o f use

Conventions of telephone conversations did “not spring up overnight. They were established by people who used telephones over time, as they discovered what telephones were good for, learned how it felt to use them, and committed social gaffes with them” (Nardi & O’Day, 1999, p. 21). This too is true of the introduction of interaction technologies. As these technologies become incorporated into and 274 adapted to the situated context of their use conventions of use will be established. Systematic communication processes will need to be defined so that the collaborators are able to know when interaction is necessary and how to best accomplish it.

6.7 Questions for Future Research

Following are questions that have arisen during this endeavor and are in need of further exploration.

1. How do distributed inter-organizational teams engaged in collaborative problem solving identify and apply the resources that group members bring to the task?

2. What processes are needed to ensure that the unique knowledge of the individuals in this team is shared among those who need it in order to make effective decisions?

3. How does the distribution of information among team members influence who directs attention to what?

4. How are individual perspectives combined to allow for the establishment of a shared perspective on what problems exist and what are the best strategies to alleviate or eliminate those problems while still meeting the goals and priorities of each organization?

5. What role does trust play in effective distributed collaborative work?

6. What in face-to-face interaction affords cooperation and trust that other technologies cannot seem to capture?

7. How can trust be fostered in an inter-organizational distributed collaborative team?

275 If the future is certain regarding the growing number of distributed collaborative teams in both intra- and inter-organizational settings» it is much less so with regard to the kinds of tools and processes that are needed to support the cognitive work of these kinds of interactions.

6.8 Concluding Remarks

Distributed collaborative work is becoming increasingly prevalent across organizations as they become more global and the cost» in time and dollars, of travel increases. As the structures of organizations change and more inter-organizational collaborations are entered into, studies of how to aid these collaborations becomes increasingly critical. The findings of the descriptive study reported here are a first step in understanding ways in which distributed inter-organizational collaboration in the sharing of task-requisite knowledge can be facilitated by interaction technologies. The technologies used by the participants enabled the sharing of critical domain knowledge, the building of common ground, and the establishment of a shared understanding of problems, constraints, priorities, and potential solutions to inefficiencies currently existing in the aviation industry with respect to pre-flight and route planning. Also realized in this study were characteristics of the interaction technologies and the problem-solving process that created barriers to effective collaboration and problem resolution. These results point to improvements that can be made both in the design of interaction technologies and in the processes of knowledge getting and giving, communication protocols, and collaborative problem solving that provide an environment that balances distributed responsibilities and access to requisite knowledge.

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Wittenbaum, GM . & S tasser, G. (1996). Management of information in small groups. In J i . Nye & AM. Brower (Eds.), What's social about social cognition? Research on socially shared cognition in small groups, (p. 3-28).

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Zander, A. (1982). Making groups effective. London: Jossey-Bass

330 GLOSSARY

Aviation Terms and Acronyms

A-

AAR - see Airport Acceptance Rate

ACARS - see ARINC Communications and Address Reporting System

A F M - see Arrival Flow Management

A O C - Airline Operations Control Center

ARTCC - see Air Route Traffic Control Center

ASD — see Aircraft Situation Display

ASP - see Arrival Sequencing Program

ATC - see Air Traffic Control

ATCSCC - see Air Traffic Control System Command Center

ATL - abbreviation for Atlanta

ATM —see Air TrafSc Management

Aircraft Situation Display (ASD) — a computer system that receives radar track data from all 22 ARTCC% organizes this data into a mosaic display, and presents it on a computer screen; display allow traMc management multiple methods of selection and the highlighting of individual aircraft or groups of aircraft. By using ASD, a coordinator can monitor any number of traffic situations or the entire system-wide traffic flows

331 Airport Acceptance Rate (AAR) - refers to the number of aircraft that can land in a specified period of time; factors that can affect the acceptance rate include the number of runways available for use based on wind direction, whether the airport can use multiple mnways at the same time, noise abatement procedures in effect, and the visibility and runway surface conditions.

Air Route Traffic Control Center (ARTCC) -T h e FAA currently has 22 Air Route Traffic Control Centers (ARTCCs) in the conterminous United States, each responsible for the separation of aircraft traveling between airports.

Air Traffic Control (ATC) — a service operated by appropriate authority to promote the safe, orderly and expeditious flow of air traffic by: a. Preventing collisions between aircraft and on the maneuvering area between aircraft and obstructions; and b. Expediting and maintaining an orderly flow of air traffic.

Air Traffic Control System Command Center (ATCSCC) - Responsible for the coordination and approval of all major inter-center flow control restrictions on a system basis in order to obtain maximum utilization of the airspace.

Alternate Airport - an airport at which an aircraft may land if a landing at the intended airport becomes inadvisable

Amendment - see Right Amendment

AOC Dispatcher - Employee of his/her respective airline and work at the operations control center for that airline. Responsible for the preflight planning, delay and dispatch release of a flight,

ARINC Communications and Address Reporting System (ACARS) -digital communication system used primarily for aircraft-to-airline messages.

Arrival C enter-The ARTCC having jurisdiction for the impacted airport.

Arrival Flow Management (AFM) - to allow aircraft to absorb arrival delays, based on current AAR, during the en route phase of flight under more fuel efficient conditions Mid proceed to the airport in a pre-planned sequence; can be accomplished by fix balancing, speed control, vectors, miles-in-trail, ASP, ground stops, and airborne holding.

Arrival Sector - an operational control sector containing one or more meter fixes

332 Arrival Sequencing Program (ASP) - to allow aircraft to absorb arrival delays during the en route phase of flight under more fuel-efficient conditions, feed, into the airport in a pre-planned sequence, based on current AAR; must be routed into terminal area via designated metering routes consisting of an outer fix, a meter fix, and a predetermined route to the active runway.

-B-

-C-

CTAS - see CenterTRACON Automation System

Center TRACON Automation System (CTAS) - provides automation tools for planning and controlling arrival air traffic; generates air traffic advisories designed to increase fuel efficiency, reduce delays, and provide automation assistance to air traffic controllers.

-D-

Departure C enter-The ARTCC having jurisdiction for the airspace that gnerates a flight to the impacted airport.

Dispatcher-see AOC Dispatcher

-E-

E FC —see Expected Further Clearance

EFM - see En route Flow Management

ESP - see En route Spacing Program

ETMS - see Enhanced Traffic Management System

Enhanced Traffic Management System ^TM S) - a system that performs flight data collection, monitoring, management, maintenance, analysis, forecasting, distribution, display and reporting

En Route Center—see Air Route Traffic Control Center

333 En Route Flow Management (EFM) - designed to regulate en route flow by monitoring designated sectors; assists exit sectors in ensuring required in-trail spacing; utilizes en route spacing program (ESP), altitude restrictions, reroutes, miles-in-trail, and airborne holding.

En Route Spacing Program (ESP) — program designed to regulate en route traffic whereby Traffic Management Units (TMUs) monitor designated en route sectors, assist sectors in ensuring spacing, assist in maintaining sector efficiency; purpose is to enhance safety by reducing bunching, reduce cognitive load on controllers, increase system capacity, and reduce departure delays.

Expected Further Clearance (EFC) — The time a pilot can expect to receive clearance beyond a clearance limit.

-F-

FFA - see Federal Aviation Administration

FAR—see Federal Aviation Regulations

FMS - Flight Status Monitor

Federal Aviation Administration (FAA) - Ensures safe and reliable air transportation for the nation. Responsibilities include air navigation, air traffic control, aviation certification and regulation, aviation security, environmental impact minimization, and aviation research and development.

Federal Aviation Regulations (FARs) - Federal rules under which flight operations are conducted.

First Tier Center - The ARTCC immediately adjacent to the impacted center

Fix—Position in space usually on an aircraft flight plan.

Fix Balancing - A process whereby aircraft are evenly distributed over several available arrival fixes reducing delays and controller workload.

Flight Plan - speciff es^the aircraft flight route, estimated departure and en route times, and intended'cruise speed and flight altitude

334 -G-

GDP—see Ground Delay Program

Ground Delay—the amount of delay attributed to ATC encountered prior to departure; usually associated with a GDP.

Ground Delay Program (GDP) - a traffic management process administered by the ATCSCC whereby aircraft are held on the ground at their origination airports in order to maintain the sector efficiency, limit airborne holding, and/or reduce arrival rate for the destination airports.

LFR - see Instrument Flight Rules

Instrument Flight Rules-rules that govern the procedures for conducting flight under instrument meteorological conditions, which are defined by visibility, distance from clouds, and ceiling less than the minimum specified for visual meteorological conditions; is normally less than three mile visibility or less than 1000 foot cloud ceiling.

-K-

-L-

LAADRing—see Low-Altitude Arrival and Departure Routinj

Low AItitude Arrival and Departure Routing (LAADRing) - Traffic management strategy that offers a way to dynamically decide what flights should be held at lower altitudes and thus allow for increased airspace capacity by reducing controller workload in affect sectors.

335 -M- ? ■ ' 't '

M SP-abbreviation forMInneapoIis- St. Paul

Meter Fix - a fix along an established route Grom over which aircraft will be metered

MIles-In-Trail—refers to the distance at which one aircraft is following another over a common route. In-trail spacing requirements can be used by the controller to deliver aircraft across a boundary or to a point (e.g., fix or runway threshold) at a specified rate or to help the following aircraft avoid the lead aircraft’s wake turbulence.

-N-

NAS - see National Airspace System

NAVAID — Navigational Aid

NRP—National Route Program

NWA - abbreviation for Northwest Airlines

National Airspace System (NAS) -comprises the set of airports, air carriers, and FAA facilities that collectively make safe and efficient air transportation possible within the United States.

- 0-

OALT—see Operational Acceptable Level of Traffic

Operational Acceptable Level of Traffic (GALT) - An air traffic activity level associated with the designated capacity for a sector or airport, normally considered to be the total number of aircraft that any air traffic functional position can accommodate for a defined period of time under a given set of circumstances. The GALT considers dynamic changes in staffing, personnel experience levels, equipment outages, operation configurations, weather, traffic complexity, aircraft <> performance mixtures, transitioning flights, adjacent airspace, and other factors that may affect an air traffic operational position or system element.

Outer Fix - an adapted fix along the converted route of flight prior to the meter fix, for which crossing times are calculated and displayed in the metering position list.

336 PDC - Pre-Departure Clearance

Preferred Routes -established between busier airports to increase system efficiency and capacity. They normally extend through one or more ARTCC areas and are designed to achieve balanced traffic flows among high density terminals.

Push - see Arrival Push or Departure Push

-Q-

-R-

Re-routes - used to avoid areas of constraint; unplanned (unlike pre-coordinated SWAP routes; usually for weather, facility outages, or volume; coordinated with ATCSCC and other facilities as necessary

-S-

SWAP - see Severe Weather Avoidance Program

Severe Weather Avoidance Program (SWAP) - program implemented by the ATCSCC where there is an operational need; preplanned alternate routes designed to accommodate arrival, en route, and departure traffic; designed to return traffic to nonnally used city pairs or preferred routes; use of coded routes to simplify coordination

Strips - see Flight Progress,Strip

-T-

T FM —see Traffic Flow Management -

TRACON—Terminal Radar-Approach Control -

TSD —Traffic Situation Display

TMC — Traffic Management Coordinator

337

r. ,■ TM Ü—see Traffic Management Unit

Terminal Radar-Approach Control CTRACON) - Once an aircraft takes off and before it lands the aircraft is under the control of the TRACON, TRACON airspace generally extends about 40 nautical miles from the airporL

Traffic Flow Management (TEM) - Seeks to optimize the movement of air traffic while maintaining a safe operating environment

Traffic Management Unit (TMU)-—The entity in all ARTCCs and designated terminals responsible For direct involvement in the active management of facility traffic; mission is to provide direction and assistance in the use of traffic management programs; a.critical element for ensuring the efficient and safe operation of the Air Traffic System

Transition Point - a point at an adapted number of miles from the vertex at which an arrival aircraft would normally begin descent from its en route altitude; is the first fix adapted on the arrival speed segments

-Ü-

VFR - see Visual Flight Rules

Visual Flight Rules (VFR) - rules that govern the procedures for conducting flight under visual meteorological conditions. Requirements for visual conditions are normally three-mile visibility and a 1000 foot cloud ceiling,

-W-

Waypoint - Position in space usually on aircraft’s flight plan.

-Y-

338 -Z-

Z -Zulu (Greenwich Mean Time)

2JNY - New York Air Route Traffic Control Center

339 APPENDIX A

TRAINING Slide/Data Training

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Rgute A-L Description of the kinds of data found on the rirst slide of the scenarios.

340 UKWOFW

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34L APPENDIX B

INSTRUCTIONS TO PARTICIPANTS

I will give you. a scenario that contains information about a certain flight between two cities. Youwillbe working with your partner who you have just met. The goal for both of you working as a team is to accurately and fully identify and describe the problem or problems that you find between the cify-pair in the scenario with which you will be working. Working together, you are to generate the fullest range of solutions that you think will resolve the problem(s) that you've identified. All alternative solutions are to be considered and evaluated as to their viability for implementation. Once you have evaluated the alternatives, you are to work together to arrive at the best solution for the problem or problems you have identified.

342 APPENDIX c

SUBJECT FORMS and DEMOGRAPHICS

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AgaiL wewoulipealyeppmeiaeyoiaeaaaoeebiMeattdy. lfyatthe«eaqrqaniioiB.pieiteIetme kMw (Phone: 614-29Z4I20: S n ik Philf^oaudn).

Rgure C-L Letter of Information

343 /- ■ v :

FAA Demographic Questionnaire

Name: Phone: Email:

1. Years employed by FAA:

2. Current Job Title:

3. Current Job Responsibilities:

4. Other positions held within the FAA and number of years in each:

5. Do you use a computer? At work At home 6 . Please indicate your previous personal computer experience. Check all that apply: Hardware: # IBM (DOS) Windows (98,95, NT, or 3.1) Macintosh Other, please specify ______Software: Spread Sheet Programs Database Programs Word Processing Statistics Graphics Desktop Publishing Dispatcher Software Email Email with attached documents Other, please specify ______

344

• , ■■■■ ' - -i:. - J- Vi :: Participant Age (in years) Years Employed Current Job Responsibilities Other positions held Use of Computer by FAA - years at each Home W ork Regulating flow > A T C S -1 0 T m 42 17 years STMC Supervisor Traffic Mnnugemcni through ATL at > Operations Yes Yes manageable, efficient Supervisor -4 pace > TMC/STMC-3 ARTCC Management > Airspace and T|-2 38 15 years TMC duties; departure/ Procedures Yes Yes arrival/ESP en route Specialist - 1 spacing 51 2 7 years STMC Traffic management > Controller-15 Tz.i —— into and out of ATL > Supervisor - 5 —' and satellite airports T 2.2 43 19 years Traffic Managcmem Traffic management > Controller-11 Yes Yes Coordinator > Airspace & Procedures Office-1 > ATCS Supervisor-3 > Traffic Manager- 4 T3.1 33 8 years TMC Traffic management > A T C - 7 T3.2 35 9 years TMC Traffic management > ATCS Yes Yes T4.1 37 10 years TMC Optimizing use of > Supervisor - 1 Yes Yes airspace by balancing > A T C - 5 demand and capacity Ts-i 44 18 Supervisory Traffic Supervising Air > Controller - 10 Management Traffic Managers at > T M C - 2 Yes Yes Specialist ZNY > Area Supervisor- 1.5 Table C-1, Traffic Manager Participants Demographics

345 Airline Demographic Questionnaire

Name: Phone: Email:

L ' City Pair(s) work (currently and in. the past): 2. Years employed by AAL:

3. Current Job Title:

4. Current Job Responsibilities:

5. Years employed in the airline industry:

6. Other positions held within the airline industry and number of years in each:

7. Ar= you a pilot’ p,. 8 . Do you use a computer? , . , ^ At work At home 9. Please indicate your previous personal computer experience. Check all that apply: Kirdware: IBM (DOS) Windows (98,. 95, NT, or 3.1) Macintosh Other, please specify ______Software: Spread Sheet Programs Database Programs Word Processing Statistics Graphics Desktop Publishing Dispatcher Software Email Bnail with, attached documents Other; please specify ______

Î46 City Pairs worked Years Years Other positions held Use o f Participant Age (currently & in Employed Current Job Responsibilities in in airline industry- Com outer past) by FAA industry years at each Home Work

D m 54 All domestic 26 Operations Maintain operational > Agent - 2 AAL city pairs Coordinator viability of airline on 26 > D isp a tc h e r -19 Yes Yes a day-to-day basis

D j,2 43 All domestic 9 Sector Supervise AAL 9 > Dispatcher - 4 . No Yies AAL city pairs Manager dispatchers 1 Di-i 53 EWR/LGA to 3 0 Operations Coordinate aircraft > Ticket counter-2 ORD and return Coordinator assignments with 30 > Gate agent - 2 No Yps maint. & hub stations y Operations - 3 Dg.g 57 Mainly domestic 18 Flight Manage section of y Baggage Handler Dispatcher the operation 25 y Cleaning - 0,5 N o Yes y Catering - 0,5 y Charter Coord.-l (lefi Monk) Center > Dispatcher - 8 D3 . 1 4 8 15 Daily operation Manager 29 y Inflight service - 6 No Yes y M a n a g er-15 23 N o D 3 . 2 4 2 ORD to ATL 12 Flight ATC Coordinator y Fleet Services Yes Dispatcher Equipment Coord. y Mail services-3 D 4.1 57 All domestic 39 Manager - AAL city pairs Systems (Icfi Monk) 39 y AAL metro- 1 No Yes Operations > Dispatch aseiu -1 Control y Dispatcher - 22 y Ops Coord. - 6 D;., 4 6 MIA to South 11 Dispatcher 25 y Dispatcher y Ops agent Yes Yes America (left Monk) y P ilo t- 6 y Ramp agent, etc. Table C-2, Dispatc ler Participants Demographics

347