MULTI-LEVEL ISSUES IN ORGANIZATIONAL BEHAVIOR AND LEADERSHIP
RESEARCH IN MULTI-LEVEL ISSUES Series Editors: Francis J. Yammarino and Fred Dansereau
Previous Volumes:
Volume 1: The Many Faces of Multi-Level Issues – Editors, Francis J. Yammarino and Fred Dansereau Volume 2: Multi-Level Issues in Organizational Behavior and Strategy – Editors, Fred Dansereau and Francis J. Yammarino Volume 3: Multi-Level Issues in Organizational Behavior and Processes – Editors, Francis J. Yammarino and Fred Dansereau Volume 4: Multi-Level Issues in Strategy and Methods – Editors, Fred Dansereau and Francis J. Yammarino Volume 5: Multi-Level Issues in Social Systems – Editors, Francis J. Yammarino and Fred Dansereau Volume 6: Multi-Level Issues in Organizations and Time – Editors, Fred Dansereau and Francis J. Yammarino Volume 7: Multi-Level Issues in Creativity and Innovation – Editors, Michael D. Mumford, Samuel T. Hunter, and Katrina E. Bedell-Avers RESEARCH IN MULTI-LEVEL ISSUES VOLUME 8
MULTI-LEVEL ISSUES IN ORGANIZATIONAL BEHAVIOR AND LEADERSHIP
EDITED BY FRANCIS J. YAMMARINO State University of New York at Binghamton, NY
FRED DANSEREAU State University of New York at Buffalo, NY
United Kingdom – North America – Japan India – Malaysia – China JAI Press is an imprint of Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK
First edition 2009
Copyright r 2009 Emerald Group Publishing Limited
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ISBN: 978-1-84855-502-0 ISSN: 1475-9144 (Series)
Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print CONTENTS
ABOUT THE EDITORS ix
LIST OF CONTRIBUTORS xi
ACKNOWLEDGMENTS xiii
OVERVIEW: MULTI-LEVEL ISSUES IN ORGANIZATIONAL BEHAVIOR AND LEADERSHIP Fred Dansereau and Francis J. Yammarino 1
PART I: ORGANIZATIONAL BEHAVIOR
A NEW KIND OF ORGANIZATIONAL BEHAVIOR Francis J. Yammarino and Fred Dansereau 13
THICK OR THIN? A FUNDAMENTAL QUESTION IN ORGANIZATIONAL BEHAVIOR Neal M. Ashkanasy 61
A NEWER ORGANIZATIONAL BEHAVIOR Francis J. Yammarino and Fred Dansereau 69
PART II: OUTSTANDING LEADERSHIP
CHARISMATIC, IDEOLOGICAL, AND PRAGMATIC LEADERSHIP: AN EXAMINATION OF MULTI-LEVEL INFLUENCES ON EMERGENCE AND PERFORMANCE Michael D. Mumford, Samuel T. Hunter, Tamara L. 79 Friedrich and Jay J. Caughron
v vi CONTENTS
LEVELS OF PERFORMANCE: MULTI-LEVEL PERSPECTIVES ON OUTSTANDING LEADERSHIP James G. (Jerry) Huntw and John N. Davis 117
PRESIDENTIAL LEADERSHIP STYLES: HOW DO THEY MAP ONTO CHARISMATIC, IDEOLOGICAL, AND PRAGMATIC LEADERSHIP? Dean Keith Simonton 123
CHARISMATIC, IDEOLOGICAL, AND PRAGMATIC LEADERSHIP: WHERE WE ARE, AND WHERE DO WE NEED TO GO? Michael D. Mumford, Jay J. Caughron and 135 Tamara L. Friedrich
PART III: LEADERSHIP AND SOCIAL RELATIONS
A COMPONENTIAL ANALYSIS OF LEADERSHIP USING THE SOCIAL RELATIONS MODEL David A. Kenny and Stefano Livi 147
CONSIDERATIONS IN APPLYING THE SOCIAL RELATIONS MODEL TO THE STUDY OF LEADERSHIP EMERGENCE IN GROUPS: A LEADERSHIP CATEGORIZATION PERSPECTIVE Rosalie J. Hall, Robert G. Lord and Katey E. Foster 193
THOUGHTS ON STUDYING LEADERSHIP IN NATURAL CONTEXTS Stefano Livi and David A. Kenny 215
PART IV: LEADERSHIP SIMULATION
A LEVELS-BASED LEADERSHIP SIMULATION: INSIGHTS REGARDING GROUP DECISION OPTIMIZATION Shelley D. Dionne and Peter J. Dionne 227 Contents vii
COMPARING SIMULATION RESULTS OF LEADERSHIP STYLE IMPACTS ON EMERGENT VERSUS SPECIFIC TASK OUTCOMES AND REQUIRED SIMULATION MODEL COMPONENTS Janice A. Black, Richard L. Oliver and Lori D. Paris 271
MAKING IT PRACTICAL: SIMULATION, NATURALISTIC DECISION MAKING, AND COMPLEXITY IN TEAM PERFORMANCE Jessica L. Wildman and Eduardo Salas 301
SINS OF OMISSION AND ENVY: REDEMPTION AND SALVATION THROUGH LEVELS OF ANALYSIS Shelley D. Dionne and Peter J. Dionne 321
PART V: ENVIROSCAPES
ENVIROSCAPES: A MULTI-LEVEL CONTEXTUAL APPROACH TO ORGANIZATIONAL LEADERSHIP Richard Reeves-Ellington 337
TARGETING THE CULTURAL PROCESSES OF PARTNERING FOR ANALYSIS Elizabeth K. Briody 421
ENVIROSCAPES: THE CHALLENGES OF CULTURAL PARTNERING CONCEPTS Richard Reeves-Ellington 431
PART VI: ABOUT THE AUTHORS
ABOUT THE AUTHORS 447 This page intentionally left blank
ABOUT THE EDITORS
Francis J. Yammarino, Ph.D., is SUNY Distinguished Professor of Manage- ment and Director and Fellow of the Center for Leadership Studies at the State University of New York at Binghamton. He received his Ph.D. in Organizational Behavior (Management) from the State University of New York at Buffalo. Dr. Yammarino has extensive research experience in the areas of superior–subordinate relationships, leadership, self–other agree- ment processes, and multiple levels of analysis issues. He has served on the editorial review boards of eight scholarly journals, including the Academy of Management Journal, Journal of Applied Psychology, Journal of Organizational Behavior, Leadership Quarterly, Organizational Research Methods,and Personnel Psychology. Dr. Yammarino is a Fellow of the American Psycho- logical Society and the Society for Industrial and Organizational Psychology. He is the author of 13 books and has published more than 100 articles. Dr. Yammarino has served as a consultant to numerous organizations, including IBM, Textron, TRW, Lockheed Martin, Medtronic, United Way, Skills Net, and the US Army, Navy, Air Force, and Department of Education. Fred Dansereau, Ph.D., is Professor of Organization and Human Resources and Associate Dean for Research in the School of Management at the State University of New York at Buffalo. He received his Ph.D. from the Labor and Industrial Relations Institute at the University of Illinois with a specialization in Organizational Behavior. Dr. Dansereau has extensive research experience in the areas of leadership and managing at the individual, dyad, group, and collective levels of analysis. Along with others, he has developed a theoretical and empirical approach to theorizing and testing at multiple levels of analysis. He has served on the editorial review boards of the Academy of Management Review, Group and Organization Management, and Leadership Quarterly. Dr. Dansereau is a Fellow of the American Psycholo- gical Association and the American Psychological Society. He has authored 12 books and more than 80 articles and is a consultant to numerous organizations, including the Bank of Chicago, Occidental, St. Joe Company, Sears, TRW, the United States Army and Navy, Worthington Industries, and various educational institutions.
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LIST OF CONTRIBUTORS
Neal M. Ashkanasy UQ Business School, The University of Queensland, Brisbane, Queensland, Australia Janice A. Black Department of Management and Marketing, School of Business and Public Administration, California State University, Bakersfield, CA Elizabeth K. Briody General Motors R&D, Warren, MI Jay J. Caughron Department of Psychology, The University of Oklahoma, Norman, OK Fred Dansereau School of Management, State University of New York at Buffalo, Buffalo, NY John N. Davis Hardin-Simmons University, Kelley College of Business, Abilene, TX Shelley D. Dionne Binghamton University, School of Management and Center for Leadership Studies, Binghamton, NY Peter J. Dionne Sensis Corporation, East Syracuse, NY Katey E. Foster Department of Psychology, University of Akron, Akron, OH Tamara L. Friedrich Department of Psychology, The University of Oklahoma, Norman, OK Rosalie J. Hall Department of Psychology, University of Akron, Akron, OH James G. (Jerry) Huntw Texas Tech University, Lubbock, TX Samuel T. Hunter Department of Psychology, Penn State University, University Park, PA xi xii LIST OF CONTRIBUTORS
David A. Kenny Department of Psychology, University of Connecticut, Storrs, CT Stefano Livi Department of Social and Developmental Psychology, University of Rome ‘‘La Sapienza,’’ Rome, Italy Robert G. Lord Department of Psychology, University of Akron, Akron, OH Michael D. Mumford Department of Psychology, The University of Oklahoma, Norman, OK Richard L. Oliver Department of Accounting and Information Systems, College of Business, New Mexico State University, Las Cruces, NM Lori D. Paris Department of Management and Marketing, School of Business and Public Administration, California State University, Bakersfield, CA Richard Reeves- School of Management, Binghamton Ellington University, State University of New York, Binghamton, NY Eduardo Salas Department of Psychology, and Institute for Simulation and Training, University of Central Florida, Orlando, FL Dean Keith Simonton Department of Psychology, University of California at Davis, Davis, CA Jessica L. Wildman Department of Psychology, and Institute for Simulation and Training, University of Central Florida, Orlando, FL Francis J. Yammarino School of Management and Center for Leadership Studies, State University of New York at Binghamton, Binghamton, NY ACKNOWLEDGMENTS
The publication of the Research in Multi-Level Issues annual series and this volume have been greatly facilitated by Rachel Brown and Emma Smith at Emerald Publishing Group in the United Kingdom, and the staff at Macmillan Publishing Solutions, India. Closer to home, we thank our Schools of Management, the Center for Leadership Studies at Binghamton, and the Jacobs Management Center at Buffalo as well as our assistants, Marie Iobst and Cheryl Tubisz, and our copyeditor, Jill Hobbs, for their help in preparing this book for publication. Finally and perhaps most importantly, we offer our sincere thanks to our contributors. The authors of the essays, commentaries, and rebuttals in this volume have provided new ideas and insights for unraveling the challenges of dealing with multiple levels of analysis and multi-level issues in a wide variety of areas. Thank you all.
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OVERVIEW: MULTI-LEVEL ISSUES IN ORGANIZATIONAL BEHAVIOR AND LEADERSHIP
Fred Dansereau and Francis J. Yammarino
INTRODUCTION
Multi-Level Issues in Organizational Behavior and Leadership is Volume 8 of Research in Multi-Level Issues, an annual series that provides an outlet for the discussion of multi-level problems and solutions across a variety of fields of study. Using a scientific debate format of a key scholarly essay followed by commentaries and a rebuttal, we present, in this series, theoretical work, significant empirical studies, methodological developments, analytical techniques, and philosophical treatments to advance the field of multi-level studies, regardless of disciplinary perspective. Similar to Volumes 1 through 7 (Yammarino & Dansereau, 2002, 2004, 2006; Dansereau & Yammarino, 2003, 2005, 2007; Mumford, Hunter, & Bedell-Avers, 2008), Volume 8 contains five major essays with commentaries and rebuttals that cover a range of topics, but in the realms of organi- zational behavior and leadership. In particular, the five ‘‘critical essays’’ offer extensive literature reviews, new model developments, methodological advancements, and some data for the study of organizational behavior, outstanding leadership, leadership and social relations, leadership simula- tion, and enviroscapes. While each of the major essays, and its associated
Multi-Level Issues in Organizational Behavior and Leadership Research in Multi-Level Issues, Volume 8, 1–9 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1475-9144/doi:10.1108/S1475-9144(2009)0000008018 1 2 FRED DANSEREAU AND FRANCIS J. YAMMARINO commentaries and rebuttals, is unique in orientation, all of the essays share a common bond in raising and addressing multi-level issues or discussing problems and solutions that involve multiple levels of analysis in organizational behavior and leadership.
ORGANIZATIONAL BEHAVIOR
In the first essay, following from the cutting-edge work of Stephen Wolfram in A New Kind of Science (2002), we (as authors) propose ‘‘a new kind of OB’’ (organizational behavior) based on the varient approach to theory building and testing. In particular, we offer four simple, yet comprehensive theories to account for individual behavior, interpersonal relationships, group dynamics, and collectivized processes in organizations. We believe that our approach differs from contemporary approaches to OB in two ways. First, we provide four sets of two constructs, each of which is proposed in different multi-level configurations. Second, we propose very simple theories that we suggest may underlie very complex processes. Thus, although the theory is multivariate (eight variables), the constructs, their association, and the levels of analysis are considered two at a time. While the four sets of variables and levels and potential interactions proposed here seem simple notions, we believe that taken both alone and in combination, they may explain a variety of complex phenomena and behavior in organizations. In his commentary, Ashkanasy notes some possible problems in our essay and suggests some alternative strategies. He identifies three core areas of concern. The first is that the essay sets out a ‘‘thin’’ theory, which is at odds with the idea that OB in real organizations is inherently complex and addressable only though ‘‘thick’’ descriptions. Second, while the theory covers four levels of analysis, Ashkanasy feels that we may have neglected the time dimension. Third, he suggests that the theory seems an example of ‘‘grand’’ theorizing, suggesting it might also share the disappointing fate of such theories in the past. In our reply to Ashkanasy’s commentary, we argue that we are not taking a logical positivist approach that ignores the complexity of the situation. We suggest that some basic processes may underlie what may appear to be complex processes. We also agree that the time dimension is an important part of our theory and point out where in the essay we considered this issue. Finally, we argue that even if the result of empirical work does not support a grand theory, we believe following this line of research has the potential to Multi-Level Issues in Organizational Behavior and Leadership 3 make a significant contribution to the field of OB, particularly, in terms of including multiple levels of analysis in the field.
OUTSTANDING LEADERSHIP
In the second essay, Mumford, Hunter, Friedrich, and Caughron begin by pointing out that theories of outstanding, historically notable, leadership have traditionally emphasized charisma. Recent research, however, suggests that charisma may represent only one pathway to outstanding leadership. Outstanding leadership, according to these authors, may also emerge from ideological and pragmatic leadership. In their essay, they examine the multi- level conditions influencing the emergence and performance of charismatic, ideological, and pragmatic leaders. They argue that different conditions operating at the environmental, organizational, group, and individual levels influence the emergence and performance of each of these three types of leaders. Implications for understanding the origins and impact of charis- matic, ideological, and pragmatic leaders are discussed. This essay clearly extends the field by adding multiple levels of analysis to the area of out- standing leadership. In regard to the commentary by Hunt and Davis, we were deeply saddened by the death of Jerry Hunt, who was one of the most open-minded professionals whom we have ever met. It was in his biannual research series on leadership that one of the editors of this volume, Fred Dansereau, had his first article on levels of analysis published. To our knowledge, it was the first article published on levels of analysis in leadership. Jerry will be deeply missed both by the editors of this volume as a person, supporter, and colleague, and by the field for his superior intellectual capability as a scholar. In line with Jerry’s open-minded approach to the field, in their com- mentary, Hunt and Davis attempt to push the work of Mumford, Hunter, Friedrich, and Caughron forward by asking how scholars might use their work to make predictions about outstanding leadership and the conditions that might be ideal for the emergence of each of the three types of out- standing leadership. Three of the questions that they ask provide a direction for future research based on Mumford et al.’s work. First, Hunt and Davis state that all other things being equal, according to Mumford et al., the strongest case for the emergence and performance of outstanding charismatic leadership would seem to be when trust is present at the group level (at the time of emergence) and under conditions of 4 FRED DANSEREAU AND FRANCIS J. YAMMARINO socio-technical change and lack of elite consensus at the environmental level. They then suggest that this idea allows future researchers to follow Mumford et al.’s lead and address the question of when these conditions that favor charismatic leadership might prevail. Second, they state that all other things being equal, according to Mumford et al., the strongest case for the emergence and performance of ideological leadership would seem to be when leadership can be shared at the group level, when culture is strong at the organizational level, and in collectivist cultures facing social disruption at the environmental level. They suggest that this notion allows future researchers to build on Mumford et al.’s work and address the question of when these conditions that favor ideological leadership might prevail. Finally, Hunt and Davis state that all other things being equal, according to Mumford et al., the strongest case for the emergence and performance of pragmatic leadership would seem to be when support is based on elite reactions, when the leader possesses strong cognitive skills at the individual level, and when the leader takes action to maintain perceptions of fairness at the group level, the amount of follower professionalism at the organization level, and consensus among elites at the environmental level. As was typical of Jerry Hunt’s work, the question then becomes how one makes advances based on previous work. In this case, Hunt and Davis again suggest that this assumption allows future researchers to follow Mumford et al.’s lead and address the question of when these conditions that favor pragmatic leadership might prevail. In his commentary, Simonton raises the question of whether the general framework in the Mumford et al. essay applies to more focused domains of leadership. More specifically, Simonton discusses his own research on leader- ship styles in the U.S. presidency – interpersonal, charismatic, deliberative, creative, and neurotic – and then examines how these five styles have some correspondence to the three broad types of extraordinary leadership discussed by Mumford et al. His essay also includes a table that provides scores for all U.S. presidents on two key dimensions: charismatic – creative and interpersonal – deliberative. We believe that this integrative thinking and these applications make an excellent contribution and addition to the area of outstanding leadership. Mumford, Caughron, and Friedrich, in their reply, suggest that the comments by Hunt and Davis and by Simonton raise a variety of questions about how the charismatic, ideological, and pragmatic leadership styles should be measured and how hypotheses should be developed with regard to multi-level influence on leader emergence and performance. They effectively Multi-Level Issues in Organizational Behavior and Leadership 5 respond to such issues but also point out that, although evidence is often available for charismatics, it is rare for studies to have contrasted charismatics with ideological and pragmatic leaders. Thus the authors hope their work and the work of Hunt and Davis and of Simonton will provide the impetus for future studies that address the issues raised by the commentators.
LEADERSHIP AND SOCIAL RELATIONS
In the third essay, Kenny and Livi present their social relations model (SRM), which explicitly proposes that leadership simultaneously operates at three levels of analysis: group, dyad, and individual (perceiver and target). According to the authors, by using their model, researchers can empirically determine the amount of variance at each level as well as those factors that explain variance at these different levels. This essay attempts to show how the SRM can be used to address many theoretically important questions in the study of leadership and can be used to advance both the theory of and research in leadership. For example, based on their analysis of leadership ratings from seven studies, Kenny and Livi suggest that there may be substantial agreement (i.e., target variance) about who in a group is the leader. In a second analysis, the authors examine the effects of gender and gender composition on the perception of leadership. They also explore how self-ratings of leadership may differ from group members’ perceptions of leadership. Finally, they discuss how their model can be used with conve- ntional software. This essay offers an extension of the SRA approach to leadership from a multi-level perspective. In their commentary, Hall, Lord, and Foster critically consider limits to the generalization of the variance components analysis results described in Kenny and Livi’s first example, and briefly summarize results of an additional study that supports the original findings. They also suggest interpretational issues and problems of interest to researchers who may wish to continue to apply the SRM to multi-level issues in the study of leadership. In their response, Livi and Kenny focus on whether the SRM variance partitioning would be the same when groups are long term in duration and have formal leaders. In particular, they speculate about how the variance partitioning might change if these dimensions change. They also consider the design and analysis issues, as well as the estimation of group effects, in natural workgroups using their SRM approach. 6 FRED DANSEREAU AND FRANCIS J. YAMMARINO
LEADERSHIP SIMULATION
In the fourth essay, Dionne and Dionne begin by pointing out that previous literature has compared the effectiveness of different styles of leadership, yet most of this research has not compared different levels of analyses regarding leader styles or behaviors. In their essay, these authors develop and present a computational model and describe a levels-based comparison of four types of leadership that represent three different levels: individual, dyad, and group. When examined across a dynamic group decision-making optimiza- tion scenario, group-based leadership is found to produce decisions that are closer to optimal than do dyadic- and individual-based leadership. An alternative computational model, in which individual cognitive and experience-based components vary among group members, also indicates that group-based leadership produces more optimal decisions. The essay offers an introduction that discusses simulation as a theoretical development tool and supplies additional evidence related to the use of simulation methods in leadership research. In their commentary, Black, Oliver, and Paris begin by pointing out that clear specification of leadership efforts spanning levels of analysis has lagged behind leadership research in general. Black et al. use agent-based modeling, along with Dionne and Dionne’s choices of leadership styles, to examine the impact of those styles on the generation of an emergent group resource, context-for-learning (CFL), instead of the specific task outcome (group decision making) studied by Dionne and Dionne. In their work, they find consistent effectiveness across leadership styles for workgroups with both high and slightly lower initial individual levels of a CFL. Using a second agent-based model that includes the ability of agents to forget previous learned skills, these authors then report a reduced effectiveness of all leadership styles. However, the effectiveness of the leadership styles differs between the two outcomes (specific group task model and emergent group resource model). Black et al. note reasons for these differences and describe the implications of the comparisons of the two multi-levels models. In their commentary, Wildman and Salas also begin by highlighting the lack of focus on multi-level issues within leadership research. They suggest that while the work of Dionne and Dionne makes a strong contribution to the sciences of leadership, group decision making, and team complexity, many aspects of these authors’ research demonstrate potential for great expansion and improvement. In their commentary, Wildman and Salas discuss and provide suggestions related to the topics of computer simulation in team research, group decision-making theory, and the modeling of team Multi-Level Issues in Organizational Behavior and Leadership 7 complexity. The authors’ intention is to stimulate continued critical thinking and inspire more innovative, practical, and carefully designed multi-level research efforts. In their reply, Dionne and Dionne focus on the importance of multi-level issues in their simulation. They point out that Wildman and Salas suggest more descriptive decision-making models and more sophisticated simulation techniques would improve the practicality of their work. They also note that Black, Oliver, and Paris employ an agent-based model within an emergent task context to examine a leader’s influence on group context-for-learning and, in doing so, found differences from their own work. Dionne and Dionne demonstrate the practicality of their model and contrast their approach with the suggested additional simulations. Their reply, along with their earlier work and that of the commentators, offer an exciting glimpse into the future of group decision-making research from a multi-level perspective.
ENVIROSCAPES
In the fifth essay, Reeves-Ellington offers a paradigm for understanding organizational leadership realities through a multi-level understanding of the organizational environments of climate, knowledge, ethos, and time. To do so, he presents and discusses five enviroscapes: climate, knowledge, ethos, time, and leadership. The author suggests that each of these enviroscapes has two phenotypes: business and commerce. Each of these enviroscapes, with its concomitant phenotypes, is viewed as being used differently at multiple levels of management and leadership by senior managers, middle managers, and entry-level managers. After reviewing these conceptual and theoretical ideas, Reeves-Ellington applies the theory and model to an extended-time case study of land purchase in Indonesia by a U.S. pharmaceutical firm. This essay is likely to surprise readers who are more accustomed to traditional organizational behavior essays, in that it takes an anthropological approach to understanding leadership. In her commentary, Briody focuses on the case study presented at the end of the essay by Reeves-Ellington. Specifically, she attempts to examine the successful integration of an expanding U.S. pharmaceutical firm into Indonesia’s multicultural environment, by viewing the situation as a context marked by the interweaving of market exchange and reciprocity exchange. Her analysis directs her attention to the interactions occurring both among key leaders within the firm, and between those leaders in the firm and their 8 FRED DANSEREAU AND FRANCIS J. YAMMARINO counterparts in the peasant and governmental communities. By focusing on the cultural processes of partnering, Briody attempts to show the contri- bution of cooperative, healthy relationships in achieving the firm’s business goals. In his response, Reeves-Ellington responds to Briody’s three major areas of concern related to the original case: methodology, theoretical concepts, and leadership processes. He argues that Briody takes an anthropological approach, whereas the original case took the perspective of a business practitioner/researcher. The response essentially casts Briody’s observations as encouraging an ongoing dialogue among academic, practitioner, and anthropological researchers.
CONCLUSION
The essays, commentaries, and replies in this book illustrate the kind of issues that arise in dealing with multiple levels of analysis in organizational behavior and leadership. The definitions of concepts (i.e., organizational behavior, outstanding leadership, leadership and social relations, leadership simulation, and enviroscapes) change depending on which combination of levels of analysis is involved and added to them. The nuances of analytical methods (i.e., multi-level quantitative or qualitative in nature) change when one moves from one level of analysis to multiple levels of analysis. Moreover, although different paradigms may guide different scholars’ theories and research methods and techniques, levels of analysis issues must be resolved to have a viable paradigm (i.e., traditional or novel). We believe that the explorations of these issues in organizational behavior and leadership found in this volume show that these insights, applications, and advances will apply to numerous areas of scholarly investigation. The authors in this volume have challenged theorists, researchers, and methodologists to raise and address multi-level issues in all their disciplinary and interdisciplinary work. If you would like to be a part of contributing ideas to this scholarly endeavor, please contact us directly or visit our website at www.levelsofanalysis.com.
REFERENCES
Dansereau, F., & Yammarino, F. J. (Eds). (2003). Multi-level issues in organizational behavior and strategy. Vol. 2 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Multi-Level Issues in Organizational Behavior and Leadership 9
Dansereau, F., & Yammarino, F. J. (Eds). (2005). Multi-level issues in strategy and methods. Vol. 4 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Dansereau, F., & Yammarino, F. J. (Eds). (2007). Multi-level issues in organizations and time. Vol. 6 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Mumford, M. D., Hunter, S. T., & Bedell-Avers, K. E. (Eds). (2008). Multi-level issues in creativity and innovation. Vol. 7 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Yammarino, F. J., & Dansereau, F. (Eds). (2002). The many faces of multi-level issues. Vol. 1 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Yammarino, F. J., & Dansereau, F. (Eds). (2004). Multi-level issues in organizational behavior and processes. Vol. 3 of Research in Multi-Level Issues. Oxford, UK: Elsevier. Yammarino, F. J., & Dansereau, F. (Eds). (2006). Multi-level issues in social systems. Vol. 5 of Research in Multi-Level Issues. Oxford, UK: Elsevier.
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PART I ORGANIZATIONAL BEHAVIOR
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A NEW KIND OF ORGANIZATIONAL BEHAVIOR
Francis J. Yammarino and Fred Dansereau
ABSTRACT
Following from the cutting-edge work of Stephen Wolfram in A New Kind of Science (2002), in this chapter we propose ‘‘a new kind of OB’’ (organizational behavior) based on the varient approach to theory building and testing. In particular, we offer four simple, yet comprehen- sive theories to account for individual behavior, interpersonal relation- ships, group dynamics, and collectivized processes in organizations. In each case, two constructs, their association, and the levels of analysis of their operation are proposed. While the four theories proposed here are simple notions, they can explain a variety of complex phenomena and behavior in organizations.
INTRODUCTION
Extraordinary claims require extraordinary evidence. – Carl Sagan, Billions and Billions (1997)
The evidence is crummy. There’s a much simpler explanation. – Carl Sagan, The Demon-Haunted World: Science as a Candle in the Dark (1996)
Multi-Level Issues in Organizational Behavior and Leadership Research in Multi-Level Issues, Volume 8, 13–60 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1475-9144/doi:10.1108/S1475-9144(2009)0000008001 13 14 FRANCIS J. YAMMARINO AND FRED DANSEREAU
In 2002, Stephen Wolfram – PhD in theoretical physics (at age 20), MacArthur award recipient, and creator of the Mathematica software system – published his tome A New Kind of Science. Wolfram’s key point, which aimed to revolutionize how we view and conduct ‘‘science’’ (broadly defined), was that simple notions can explain complex phenomena. He asser- ted and then demonstrated in a variety of disciplines and areas (i.e., mathe- matics, physics, biology, social sciences, computer science, philosophy, art, technology, artificial intelligence, artificial life, catastrophe theory, chaos theory, complexity theory, computational complexity theory, cybernetics, dynamical systems theory, evolution theory, experimental mathematics, fractal geometry, general systems theory, nanotechnology, nonlinear dynamics, scientific computing, self-organization, and statistical mechanics) that simple rules (ideas, notions, theories) can lead to simple or complex phenomena. Moreover, Wolfram demonstrated that more complex or com- plicated ‘‘rules’’ do not ultimately lead to more complex behavior; using more complicated rules may be ‘‘convenient’’ but they do not add fundamentally new features (p. 62). In line with Wolfram’s postulations, with which we wholeheartedly agree, in this chapter we propose ‘‘a new kind of OB’’ (organizational behavior) based on the varient approach to theory building and testing (see Dansereau, Alutto, & Yammarino, 1984; Dansereau, Cho, & Yammarino, 2006; Dansereau & Yammarino, 2000, 2006; Yammarino, 1994, 1998; Yammarino & Markham, 1992). Specifically, following from the key assertion made by Wolfram, we propose four simple, yet comprehensive theories to account for both simple and complex organizational behavior. These theories, again analogous to the crisp nomenclature of Wolfram, are called Theory 1, Theory 2, Theory 3, and Theory 4. They attempt to understand and explain (1) individual behavior and decision making, (2) interpersonal relations and leadership, (3) group dynamics/team proces- ses and norms, and (4) collectivized processes and roles, respectively. In each case, a theory consists of two constructs, their association, and the levels of analysis of their operation. The four proposed theories that form a new kind of OB are summarized in Table 1. Before elaborating the details of each ‘‘simple’’ theory, we offer a brief summary of those portions of Wolfram’s work that are relevant for our approach and propositions here. We also review briefly ‘‘an old kind of OB’’ – the current approach to building and testing theories in organizational behavior. We then present an overview of a contrasting approach – the varient approach – to generating and testing theories for a new kind of OB. Next, we develop each of the four theories for understanding behavior in A New Kind of OB 15
Table 1. Four Theories for a New Kind of OB.
Theory Entities/Levels of Variables/Relationship Analysis
þ Theory 1: individual behavior Whole persons Option cutting ! commitment and decision making þ Theory 2: interpersonal Whole dyads Investments ! returns relations and leadership þ Theory 3: group dynamics/ Whole groups Interdependence ! cohesion team processes and norms þ Theory 4: collectivized Whole collectives Titles ! expectations processes and roles Theory 1: level-specific at the person level Theory 2: level-specific and emergent at the dyad level Theory 3: level-specific and emergent at the group level Theory 4: cross-level to the collective level organizations in terms of persons, dyads, groups, and collectives. In each case, we assert and justify a general formulation of a theory and then offer a more specific formulation for empirical testing in organizations. Finally, we discuss the implications of our approach and theories for future work in organi- zational behavior including multi-level empirical testing and the potential integration of our ideas for developing a new kind of OB.
A NEW KIND OF SCIENCE
Wolfram (2002) presents a comprehensive new paradigm for science in general as well as for its many disciplines, fields, and subfields in particular. Our purpose here is not to review his work in its entirety, but simply to provide an overview of key points to justify and demonstrate Wolfram’s position and our own position that simple ideas are valuable, are preferred, and explain a great deal of both simple and complex behavior for all of science, including OB.
Simple Rules
Wolfram (2002) uses the notion of rules – ideas or theories – to describe and explain behavior and states that ‘‘in reality even systems with extremely simple rules can give rise to behavior of great complexity’’ (p. 110). Moreover, he notes that ‘‘the simpler a structure is, the more likely it is that it will show 16 FRANCIS J. YAMMARINO AND FRED DANSEREAU up in a wide diversity of different places. And, this means that by studying systems with the simplest possible structure, one will tend to get results that have the broadest and most fundamental significance . . . looking at systems with simpler underlying structures gives us a better chance of being able to tell what is really responsible for any phenomena one sees – for there are fewer features that have been put into the system and that would lead one astray’’ (p. 109). This is a goal we hope to accomplish with the four simple theories for OB proposed here. This approach, according to Wolfram, leads to an interesting possibility: ‘‘to consider completely random initial conditions . . . one might think that starting from such randomness no order would ever emerge. But in fact . . . many systems spontaneously tend to organize themselves, so that even with completely random initial conditions, they end up producing behavior that has many features that are not random at all’’ (p. 223). When starting with a fixed or given state, there are three basic types of behavior/patterns identified by Wolfram: simple or repeating; nested or fractal; and complex or random. In terms of randomness, ‘‘something should be considered random if none of our standard methods of perception and analysis succeed in detecting any regularities in it’’ (p. 556). Regularities are repetitions or nesting patterns. More formally, ‘‘something should be considered random whenever there is essentially no simple program [rule, theory, model] that can succeed in detecting regularities in it’’ (p. 556). In terms of complexity, ‘‘when we say that something seems complex what we typically mean is that we have not managed to find any simple description of it – or at least those features of it in which we happen to be interested’’ (p. 557). The simplest descriptions are repetition and nesting: If we don’t ‘‘see’’ these, then we consider things to be complex. Relevant for our work here in OB, our four proposed theories are simple ones that can detect, predict, and help understand regularities in behavior. Other, more complex and complicated theories in OB appear to do no better in detecting regularities, as evidenced by the oftentimes nonreplicability of studies and/or findings in the field, and so may be merely tapping randomness. In Wolfram’s words, ‘‘From the intuition of traditional science we might think that if the behavior of a system is complex, then any model for the system must also somehow be correspondingly complex. But . . . this is not in fact the case, and . . . even models that are based on extremely simple underlying rules can yield behavior of great complexity’’ (2002, p. 364). Our contention is that our four simple theories proposed here meet these conditions – that is, beyond being ‘‘simple,’’ they can account for or explain complex behavior and actions of various entities. A New Kind of OB 17
Wolfram goes on to state, ‘‘Typically it is not a good sign if the model ends up being almost as complicated as the phenomena it purports to describe. And it is an even worse sign if when new observations are made the model constantly needs to be patched in order to account for them’’ (2002, p. 365). Unfortunately, this pattern is often observed in OB, where new variables are constantly added to models, increasing their complexity, to account for unexplained behavior. In contrast, ‘‘[it] is usually a good sign . . . if a model is simple, yet still manages to reproduce, even quite roughly, a large number of features of a particular system. And it is an even better sign if a fair fraction of these features are ones that were not known, or at least not explicitly considered, when the model was first constructed’’ (Wolfram, 2002, p. 365). This goal, in fact, underlies our proposing of four simple theories to account for OB at the person (individual), dyad (interpersonal), group (team), and organizational (collective) levels of analysis.
Computations and Rules
Wolfram (2002) creates simple models for explaining complex ‘‘everyday systems’’ such as the growth of crystals, the breaking of materials, the flow of fluids (e.g., air and water), fundamental issues in biology (e.g., molecular structure and natural selection), the growth of plants and animals, biological pigmentation patterns, and financial systems. He also demonstrates how simple models can explain complex phenomena in fundamental physics (e.g., conservation of energy, equivalence of direction in space, models of the universe, space–time and relativity, elementary particles, gravity, and quantum phenomena) and in processes of perception and analysis (e.g., randomness, complexity, data compression, visual and auditory perception, statistical analysis, cryptography and cryptanalysis, mathematical formulas, and human thinking). Wolfram accomplishes this by focusing on the notion of computation. For him, systems can be viewed as simple computer programs or in terms of the computations they can perform. The initial conditions are the input; the state of the system after some number of steps corresponds to the output. Also, different systems may have very different internal workings but the com- putations the systems perform may be very similar, such that ‘‘any system whatsoever can be viewed as performing a computation that determines what its future behavior will be’’ (p. 641). A further notion Wolfram discusses is universality: ‘‘if a system is uni- versal, then it must effectively be capable of emulating any other system, and 18 FRANCIS J. YAMMARINO AND FRED DANSEREAU as a result it must be able to reproduce behavior that is as complex as the behavior of any other system’’ (p. 643). He notes that cellular automata, Turing machines, substitution systems, and register machines are examples of systems that, despite the great differences in underlying structures, can be made to emulate each other – that is, ‘‘universals.’’ Also, ‘‘any system whose behavior is not somehow fundamentally repetitive or nesting will in the end turn out to be universal’’ (p. 698) and ‘‘universality is in a sense just associated with general complex behavior’’ (p. 713). This behavior results from simple rules and from altering the initial conditions. More specifically, the general underlying hypothesis for Wolfram’s whole paradigm is the principle of computational equivalence (PCE). It applies to any kind of process, whether natural or artificial. The key underlying idea that leads to PCE is the notion that ‘‘all processes, whether they are produced by human effort or occur spontaneously in nature, can be viewed as computations’’ (p. 715). PCE asserts that ‘‘when viewed in computational terms there is a fundamental equivalence between many different kinds of processes . . . almost all processes that are not obviously simple can be viewed as computations of equivalent sophistication’’ (pp. 716–717) and that ‘‘even extremely simple rules can be universal’’ (p. 718). While we are not dealing with computations per se here, our four proposed theories of OB are simple rules that are universal in Wolfram’s sense. Moreover, PCE ‘‘introduces a new law of nature to the effect that no system can ever carry out explicit computations that are more sophisticated than those carried out by systems like cellular automata and Turing machines’’ (Wolfram, 2002, p. 720). PCE suggests ‘‘that beyond systems with obvious regularities like repetition and nesting most systems are universal, and are equivalent in their computational sophistication’’ (p. 735). Again, this idea also applies to the four theories of OB presented in this chapter. Lastly, ‘‘even though a system may follow definite underlying laws its overall behavior can still have aspects that fundamentally cannot be described by reasonable laws’’ (Wolfram, 2002, p. 750). According to Wolfram, this idea explains the phenomenon of free will. In other words, PCE explains and helps us understand why persons, dyads, groups, and collectives can follow option cutting/commitment, investments/returns, interdependence/cohesion, and titles/expectations, respectively, yet still show variation in behavior that is not accounted for by the theories (rules) per se. In short, systems/entities have ‘‘free will’’; thus, in OB as in science in general, despite our simple theories’ attempts to account for a variety of complex behavior, we can still expect some variability in behavior of persons, dyads, group, and collectives. A New Kind of OB 19
AN OLD KIND OF OB
Complex Rules
In contrast to the approach of Wolfram (2002), the field of OB is replete with complicated and complex ‘‘rules’’ (ideas, notions, theories) that do not appear to add new explanations for the behavior and actions of systems/ entities. While not wishing to single out any particular publication outlet (because we view this issue as a general problem for OB journals), a typical article published in the Academy of Management Review proposes a theory with ‘‘multiple boxes and arrows,’’ all of which are interconnected to form a complex web of relationships. These complex explanations, which often are never tested or at least never fully tested or replicated in subsequent publications, strain to account for behaviors that may be explained by simpler ‘‘rules,’’ such as those offered in this chapter. These ideas are reflected in the quotations at the outset of this chapter from Carl Sagan, who some have suggested may be the second greatest scientist of the twentieth century (after Albert Einstein) based on not only his discoveries but also his role in making science readily accessible to the general public. In brief, the quotes from Sagan’s work indicate that there are too many theories and not enough data, too many untested or weakly tested theories, and weak evidence for complicated theories, especially when simpler explanations are available. These ideas seem to readily apply to OB, where they are further supported by weak or at best marginal results in meta-analyses on most complex (rather than simple) theories.
Levels of Management versus Levels of Analysis
Another problem with current approaches in OB is that they often ignore entities (or systems) per se, instead focusing and building upon on levels of management or assuming levels of analysis (without making them explicit) or both. Even now, despite more than two decades of levels work, there is still confusion and misunderstanding about levels of analysis versus levels of management issues. These issues have been discussed in detail for a variety of areas in OB in general (see Dansereau et al., 1984, 2006; Dansereau, Yammarino, & Kohles, 1999; Dansereau & Yammarino, 2000, 2003, 2005, 2007; Yammarino & Dansereau, 2002a, 2004, 2006; Yammarino, 1994; Yammarino & Markham, 1992) as well as for specific areas within OB such as leadership research (see Dansereau & Yammarino, 1998a, 1998b; Yammarino, Dionne, Chun, & Dansereau, 2005; Yammarino, 1998). 20 FRANCIS J. YAMMARINO AND FRED DANSEREAU
Levels of Management: Organizational Chart (4 Levels)
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Levels of Analysis: 15 Persons, 14 Dyads, 7 Groups, 2 Collectives, 1 Organization
Fig. 1. Levels of Management and Levels of Analysis.
While levels of analysis issues are more fully explicated later in this chapter, Fig. 1 begins this clarification and highlights the differences between levels of management and levels of analysis. The same people within the same organization are shown in the upper (levels of management) and lower (levels of analysis) portions of the figure, but a different configuration or view occurs by rearranging the nodes in the figures (adapted from Wolfram, 2002, on network systems). The nodes are individuals who, in the upper portion of the figure, are placed in an organizational chart of four levels of management (with the CEO, e.g., at the top). In the lower portion of the figure, these same individuals (with the CEO in the middle) account for various levels of analysis – that is, 15 persons, 14 dyads (one-to-one relationships), 7 groups (or teams), 2 collectives (e.g., departments), and 1 organization – and can be A New Kind of OB 21 viewed in terms of any of these ‘‘lenses.’’ Note that specifying and/or testing levels of management is not the same thing as specifying and/or testing levels of analysis.
Summary
Given the previously identified issues, it is time to dispense with ‘‘an old kind of OB’’ and begin to focus on a new kind of OB that values simple ‘‘rules’’ (Wolfram, 2002) or what we might call ‘‘little ideas that are well tested’’ rather than complex ‘‘rules’’ or what we might refer to as ‘‘big ideas that are poorly tested.’’ These simple theories should ideally include the smallest number of constructs and variables possible and should explicitly incorporate entities, systems, or levels of analysis. As noted by Chaitin, ‘‘a theory has to be simpler than the data it explains, otherwise it does not explain anything . . . The simpler the theory, the better you understand something’’ (2006, pp. 76–77). In this sense, we are well served by William of Occam and Occam’s razor – a rule of thumb that states when faced with two hypotheses (theories or ‘‘rules’’) that explain the data or evidence equally well, one should choose the simpler one. So, following the tradition of Occam, Sagan, and Wolfram, we offer four simple theories and a comprehensive approach for testing and gathering better evidence about them for a new kind of OB.
A NEW KIND OF OB: THE VARIENT APPROACH
Endorsing the notion that simple rules, ideas, and theories are better and explain as much or more than complex ones (e.g., Einstein’s famous equation E ¼ mc2), we wish to formulate theories with a minimal number of constructs that explain the behaviors and actions of entities or systems. In fact, the absolute minimum (simple) specification for a ‘‘theory’’ is two constructs, with a relationship specified between them, about something (i.e., entities or objects of study), as exemplified by Einstein’s equation for energy. Our four proposed theories have these characteristics and are notions that have ‘‘deep roots,’’ as they are linked to traditional or classical ideas. We begin this discussion with a focus on the entities or levels of analysis.
Levels of Analysis
Levels of analysis issues and multiple-level approaches are becoming increasingly important in many areas of OB and closely related research (see 22 FRANCIS J. YAMMARINO AND FRED DANSEREAU
Dansereau & Yammarino, 1998a, 1998b, 2003, 2005, 2007; Yammarino & Dansereau, 2002a, 2004, 2006). Various scholars (Dansereau et al., 1984, 1999; House, Rousseau, & Thomas-Hunt, 1995; Klein, Dansereau, & Hall, 1994; Rousseau, 1985; Yammarino et al., 2005) have noted the importance of clearly specifying the levels of analysis at which phenomena are expected to exist theoretically, and have stated that it is critical to ensure that the measurement of constructs and data-analytic techniques correspond to the asserted levels of analysis, so that inference drawing is neither misleading nor artifactual. Levels of analysis are inherent in theoretical formulations. In some formulations, the levels of analysis are implicit or assumed. In other cases, levels of analysis are used to formulate the boundary conditions under which a theory is expected to hold. In still other instances, theories, propositions, and hypotheses explicitly incorporate levels of analysis as an integral component of the formulation. Understanding how and if levels are specified permits an examination of the potential for or degree of prevalence of theoretical misspecification. Moreover, identification of relevant levels of analysis issues may help account for mixed, inconsistent, and contradictory findings in prior research. Without explicit incorporation of levels of analysis issues, incomplete understanding of a construct or phenomenon may lead to faulty measures, inappropriate data-analytic techniques, and erroneous conclusions. Theoretical revolutions in science often emerge when other levels of analysis are considered. For example, a revolution in biology occurred when some theorists suggested, and subsequently demonstrated, that evolution can occur at a level of analysis higher than the organism level. Likewise, a well-known revolution in physics arose when some theorists asserted, and subsequently demonstrated, that quantum mechanics operate at a level of analysis lower than the atomic level. In this same way, OB theory building can advance when we include lower and higher levels of analysis in theory development and hypothesis generation. Levels of analysis are the entities or objects of study. In the current work, we are interested in human beings in work organizations. Entities are typically arranged in hierarchical order such that higher levels (e.g., groups) include lower levels (e.g., persons), and lower levels are embedded in higher levels (see Dansereau et al., 1984; Yammarino, 1996; Yammarino & Bass, 1991). In the various areas of OB research, four key levels of analysis of human beings are relevant: individuals or persons (independent human beings), dyads (two-person groups and interpersonal relationships), groups (workgroups and teams), and organizations (collectives larger than groups A New Kind of OB 23 and groups of groups) (see Dansereau et al., 1984; Yammarino, 1996; Yammarino & Bass, 1991). First, human beings in organizations can be viewed as individuals or persons, independent of one another. In this case, we can focus on an employee, a manager, a leader, or a follower/subordinate, or how these individuals differ from one another. Individual differences are of interest here. Second, human beings in organizations can be viewed as dyads,ortwo individuals who are interdependent on a one-to-one basis. A dyad is a special case of groups – that is, a two-person group. In this case, we can focus on superior–subordinate dyads, leader–follower dyads, peer–peer dyads, coworker–coworker dyads, or interpersonal relationships, indepen- dent of the formal workgroup. Third, human beings in organizations can be viewed as groups or teams. While there are some potential differences between groups and teams, we view them similarly here – as a collection of individuals who are interdependent and interact on a face-to-face or ‘‘virtual’’ (non-colocated) basis with one another. Formal workgroups or teams generally consist of a leader or a manager and his or her immediate followers or direct reports. Fourth, human beings in organizations can be viewed as collectives.In this case, the focus is on clusterings of individuals that are larger than groups and that are interdependent based on a hierarchical structuring or a set of common or shared expectations. Collectives include groups of groups, departments, functional areas, strategic business units, and organizations. They often do not involve direct interaction among people (as in groups), but rather are held together by echelons or hierarchies. These four levels of analysis – person, dyad, group, and collective – represent different perspectives on the human beings who make up organizations. In this sense, they can be thought of as different lenses through which human beings can be observed. A key characteristic of these levels is their embeddedness; for example, two persons make up a dyad, multiple persons make up a group, multiple dyads make up a larger group, and multiple groups make up a collective. In other words, as one views human being from increasingly higher levels of analysis, the number of entities decreases (e.g., there are fewer collectives than groups in an organization), and the size of the entities increases (e.g., collectives include a larger number of human beings than do groups).
Wholes and Parts
In our approach, there are four alternatives to consider for each level of analysis (see Table 2). Two of these alternatives are plausible views of the 24 FRANCIS J. YAMMARINO AND FRED DANSEREAU
Table 2. Summary of Single-Level Formulations.
Alternative Members of Associations among Between-Entities Within-Entities Views of Units Unit Members Differences Differences Entities
Wholes Homogeneous Positive Systematic Error Parts Heterogeneous Negative Error Systematic Equivocal Independent Independent Systematic Systematic Inexplicable Not relevant Not relevant Error Error
focal entities (parts and wholes as units of analysis), and two of them indicate that focal entities are not relevant but that other entities may be plausible (equivocal and inexplicable). We distinguish conceptually between two different views of any level of analysis (also see Lerner, 1963). A wholes view is defined as a focus between entities but not within them; differences between entities are viewed as valid, and differences within entities are viewed as error (random). This perspective can be described as a between-units case (Glick & Roberts, 1984; Pedhazur, 1982). In this instance, members of a unit are homo- geneous, the whole unit is of importance, and relationships among members of units with respect to constructs of a theory are positive. Relationships among theoretical constructs are a function of differences between units. A parts view is defined as a focus within entities but not between them; differences within entities are valid, and differences between entities are erroneous. This perspective can be described as a within-units case (Glick & Roberts, 1984; Pedhazur, 1982)orafrog pond effect (Firebaugh, 1980). In this instance, members of a unit are heterogeneous, a member’s position relative to other members is of importance, and relationships among members of units with respect to constructs of a theory are negative. Relationships among theoretical constructs are a function of differences within units. These two views – wholes and parts – are conceptually different ways to indicate that a particular level of analysis is relevant for understanding constructs and variables of interest. In addition to permitting effects at a particular level of analysis, various authors indicate that effects may not be evidenced at that level (Lerner, 1963; Miller, 1978; Pedhazur, 1982). Thus the focal level is considered not relevant, and other levels must be considered. In one case, there is a focus both between and within entities at a focal level. Determining whether a wholes or parts view is occurring is difficult because both between- and within-entities differences are valid. Thus the A New Kind of OB 25 focal level of analysis does not clarify our understanding of the constructs and variables of interest. Consequently, other levels must be considered. If the assumption is made that only one level of analysis can be considered, then seemingly both conditions (wholes and parts) are occurring. Because there are always other levels of analysis to consider (Miller, 1978), however, this condition must be viewed as equivocal – between- and within-entities differences are equally likely. The more parsimonious conclusion is that neither wholes nor parts views at the focal level are appropriate (Dansereau et al., 1984; Yammarino & Markham, 1992). In this instance, members of a unit are independent, members are free of the unit’s influence, and relationships among members of units with respect to constructs of a theory are independent. In short, relationships among theoretical constructs are a function of differences between members (e.g., persons) independent of higher-level units (e.g., groups). Another possibility – namely, error or lack of focus between and within entities – is an inexplicable or traditional null view of a focal level. In this case, the focal level also is not relevant for understanding the theoretical constructs of interest; instead, other levels of analysis should be specified conceptually. In summary: Wholes are homogeneous entities that display similarity among members, where between-entities differences are systematic and within-entities differences are error. Parts are heterogeneous entities that display complementarity among members, where within-entities differences are systematic and between- entities differences are error. Equivocal reflects independence among members, where between- and within-entities differences are systematic and other entities should be considered. Inexplicable indicates a null case where between- and within-entities differences are error and other entities should be explored. Given these alternatives, it becomes a matter of selecting among them based on theory and data analysis.
Multiple Levels
Beyond these single levels of analysis (i.e., individuals, dyads, groups, or collectives viewed separately), a key issue is that of multiple levels of analysis. In other words, levels can be viewed in combination or simultaneously 26 FRANCIS J. YAMMARINO AND FRED DANSEREAU
Table 3. Summary of Multiple-Level Formulations.
Multiple-Level Formulation Lower-Level View Higher-Level View
Cross-level wholes Wholes Wholes Cross-level parts Wholes Parts Level-specific wholes Wholes Equivocal Level-specific parts Parts Inexplicable Emergent wholes Equivocal Wholes Emergent parts Equivocal Parts Equivocal Equivocal Equivocal Inexplicable Inexplicable Inexplicable
Source: See Dansereau et al. (1984, p. 186) for eight additional (null) alternatives and their interpretation.
(see Table 3). In these cases, we are concerned with multi-level or cross-level effects, as well as with mixed determinants and mixed-level effects (for details and a review, see Dansereau et al., 1984; Dansereau & Yammarino, 2000; Klein et al., 1994; Rousseau, 1985). For us, multi-level or meso formulations (theories, propositions, and hypotheses) are explanations linking variables, which operate at different levels of analysis (e.g., person-level X is positively related to group-level Y) (see Behling, 1978). Rousseau states that such theories specify ‘‘relationships between independent and dependent variables at different levels’’ (1985, p. 20). (Rousseau calls these cross-level – not multi-level or meso – formulations.) Models of this type provide among-level explanations because they link variables in terms of multiple levels of analysis. Included here are mixed-effects models, in which a single variable of interest may have effects at multiple levels with multiple criteria of interest, as well as mixed-determinants models, in which multiple predictor variables at various levels of analysis affect a single criterion at a single level of analysis. For us, cross-level formulations (theories, propositions, and hypotheses) are statements about relationships among variables that are likely to hold equally well at a number of levels of analysis (e.g., X and Y are positively related for individuals and for groups) (see Behling, 1978; Dansereau et al., 1984; Miller, 1978). Rousseau notes that such cross-level formulations ‘‘specify patterns of relationships replicated across levels of analysis’’ (1985, p. 22). (Rousseau, however, calls these multi-level – not cross-level – formulations.) Models of this type are uniquely powerful and parsimonious (simple) because the same effect is manifested at more than one level of analysis (e.g., E ¼ mc2, which holds at multiple levels of analysis). A New Kind of OB 27
Assuming only one level of analysis in a study, or choosing only one level without consideration of other levels, can either mask effects or indicate an effect when none truly exists (Lerner, 1963; Miller, 1978; Pedhazur, 1982; Roberts, Hulin, & Rousseau, 1978). These issues are especially important when individuals are embedded within larger units such as dyads, groups, and collectives in organizations. Thus considering only one level of analysis is insufficient. Instead, multiple levels should be identified in combination. Regarding the particular formulations in Table 3, relationships among constructs may be hypothesized to hold at a lower (e.g., person) level but not at a higher (e.g., group) level. These relationships are discussed as a discontinuity thesis (Miller, 1978), as level-specific formulations (Dansereau et al., 1984; Miller, 1978), or empirically as disaggregated, individual,or level-specific effects (Pedhazur, 1982; Robinson, 1950). In these cases, the higher level of analysis is not relevant for understanding the theoretical constructs. In contrast, relationships among constructs may not be asserted at a lower level but may be hypothesized to manifest themselves at a higher level of analysis. These relationships also are discussed as a type of discontinuity thesis (Miller, 1978), as emergent formulations that hold at a higher (e.g., group) level after not being asserted or found to hold at a lower (e.g., person) level (Dansereau et al., 1984; Miller, 1978), empirically as a higher-level effects that do not disaggregate, or as emergent effects (Miller, 1978; Robinson, 1950). In these cases, the lower level of analysis is not relevant for understanding the theoretical constructs. Thus, in the case of level-specific and emergent formulations, even though a single level of analysis is of primary concern, other levels are considered but defined as not relevant. Alternatively, relationships among constructs may be hypothesized to hold at higher (e.g., collective) and lower (e.g., group) levels of analysis. These relationships are discussed as a homology thesis (Miller, 1978) or empirically as aggregated or ecological effects (Glick & Roberts, 1984; Pedhazur, 1982; Robinson, 1950). As noted pre- viously, they are of two types: