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Old Dominion University ODU Digital Commons Engineering Management & Systems Engineering Management & Systems Engineering Theses & Dissertations Engineering Winter 1995 A Nonlinear Dynamic Method for Supporting Large-Scale Decision-Making in Uncertain Environments Wayne Woodhams Old Dominion University Follow this and additional works at: https://digitalcommons.odu.edu/emse_etds Part of the Industrial Engineering Commons, Structures and Materials Commons, and the Systems Engineering Commons Recommended Citation Woodhams, Wayne. "A Nonlinear Dynamic Method for Supporting Large-Scale Decision-Making in Uncertain Environments" (1995). Doctor of Philosophy (PhD), Dissertation, Engineering Management & Systems Engineering, Old Dominion University, DOI: 10.25777/4nxp-7q12 https://digitalcommons.odu.edu/emse_etds/135 This Dissertation is brought to you for free and open access by the Engineering Management & Systems Engineering at ODU Digital Commons. It has been accepted for inclusion in Engineering Management & Systems Engineering Theses & Dissertations by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. A NONLINEAR DYNAMIC METHOD FOR SUPPORTING LARGE-SCALE DECISION MAKING IN UNCERTAIN ENVIRONMENTS Wayne Woodhams B.S.E.E. May, 1968, Clarkson College of Technology M.B.A. May, 1972, Adelphi University A Dissertation Submitted to the Faculty of Old Dominion University in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY ENGINEERING MANAGEMENT OLD DOMINION UNIVERSITY December, 1995 Approved by: Dr. Laurence D. Richards (Director) Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT A NONLINEAR DYNAMIC METHOD FOR SUPPORTING LARGE-SCALE DECISION MAKING IN UNCERTAIN ENVIRONMENTS Wayne Woodhams Old Dominion University Director: Dr. Laurence D. Richards This research developed a methodology for supporting decision making by reducing uncertainty in decision environments which are too large, dynamic and complex to be treated by traditional quantitative and simulation techniques. These environments are complex because of the free choice associated with human involvement, and the existence of a large number of interrelated factors which influence the outcomes of the decision process. They are dynamic because the ground rules affecting those interrelationships are constantly changing. Uncertainty cannot be treated probabilistically, since identification of a full set of outcomes and factors of influence is not possible. The venue for the investigation was the infrastructure which supports commercial space launch activities in the United States. The issue treated was whether it would be advisable to make large capital investment in that infrastructure. The problem was approached using the principles of Chaos Theory and Nonlinear Dynamics, in a manner similar to that used by Priesmeyer (1992). The intent was to engender a more systemic view of the environment and Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. approach analysis by examining marginal changes, over a period of ten years, in factors which tend to influence the outcome. The objective was to develop hypotheses which, when validated, will provide a new perspective for decision makers from which to enhance the robustness of these kinds of decisions. The methodology, which evolved over several years of preliminary research, involved identification of sectors of the commercial space infrastructure, isolation of the more important decision factors, identification and solicitation of knowledgeable respondents from the various infrastructure sectors, development of a computerized qualitative data gathering instrument, and graphical analysis of data represented by phase plane diagrams. Although there was little evidence of “classical” chaotic behavior in the data, the analysis was able to isolate those nonlinear dynamic relationships between decision factors which appeared most likely to provide information regarding system behavior. One hypothesis was developed directly from that observation. A second resulted from the development of an aggregate measure of the level of uncertainty (and, consequently, investment risk) inherent in the decision environment. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. DEDICATION To my wife, Sam, and son, Chris, without whose understanding, support, encouragement and prodding, this endeavor may not have been concluded. Also, to my mother, Lucille, without whose steadfast support I never would have made it through undergraduate school. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ACKNOWLEDGMENTS In the absence of a degree program in the discipline of Engineering Management, I would certainly not have pursued a terminal degree. My thanks are extended to all of those people in the College of Engineering and Technology and the Department of Engineering Management who have contributed their energies to make the program what it is. I also wish to express individual thanks to my dissertation committee: Dr. Larry Richards and Dr. Billie Reed, for providing guidance and feedback throughout the process, and to Dr. Barry Clemson and Dr. Jim Schwing for their valuable insights in creating the final product. Others in the Department to whom I owe a debt of gratitude include Dr. Derya Jacobs, Dr. Fred Steier, Dr. Chuck Keating and Ms. Gerri Dutton, who provided valuable advice, assistance and encouragement. Collegial interaction with fellow doctoral students, especially Shelley Gallup, also provided valuable insight and information. Finally, although they remain anonymous, my thanks are extended to those who participated in the data gathering and analysis which supported this research. iii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS Page ACKNOWLEDGMENTS....................................................................................................iii LIST OF FIGURES AND TABLES...................................................................................vii Chapter 1. INTRODUCTION....................................................................................................... 1 Problem Statement ...............................................................................................1 Venue of Investigation ........................................................................................3 Purpose of the Research .................................................................................. 4 2. UNDERLYING THEORY OF RESEARCH (LITERATURE REVIEW).....................................................................................6 Strategic Decision Theory and Policy Formulation ........................................ 7 Robust (Investment) Decision T h eo ry ............................................................ 14 Forecasting ......................................................................................................... 16 Chaos Theory and Nonlinear Dynamics .........................................................21 Departure From Existing Theory .......................................................................26 3. METHODOLOGY.....................................................................................................28 Background ........................................................................................................28 Theoretical/Conceptual Framework of the Research ................................... 30 Identification of Sectors of the Environment .................................................. 32 iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Page Identification of Factors Affecting Decision M aking ..................................... 37 Formal Data G athering ......................................................................................43 Human Subjects ..................................................................................... 43 The Survey Instrument ............................................................................ 44 Selection and Recruitment of Survey Respondents ........................... 48 Data Analysis ...................................................................................................... 52 Data Processing ........................................................................................ 52 Development of Marginal Change D a ta ................................................ 53 Development and Analysis of Phase Plane Diagram s ....................... 55 Periodicity ...................................................................................... 57 Limit C ycles ...................................................................................61 Development of System Uncertainty In d e x ...........................................62 Summary of Methodological Process ............................................................. 66 4. FINDINGS AND R E S U LTS ................................................................................... 68 Filtered Marginal Change D a ta ........................................................................68 Phase Planes for Pair-wise Comparison of Marginal Changes in Decision Factors .......................................................................................

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