Interpersonal Networks in Organizations: Cognition, Personality, Dynamics, and Culture (Structural Analysis in the Social Sciences)

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Interpersonal Networks in Organizations Cognition, Personality, Dynamics, and Culture This book brings a social network perspective to bear on topics of leadership, decision making, turnover, organizational crises, organizational culture, and other major organizational behavior topics. It offers a new direction for organizational behavior theory and research by drawing from social network ideas. Across diverse research topics, the authors pursue an integrated focus on social ties both as they are represented in the cognitions of individuals and as they operate as constraints and opportunities in organizational settings. The authors bring their twenty years’ worth of research experience together to provide a programmatic social network approach to understanding the internal functioning of organizations. By focusing a distinctive research lens on interpersonal networks, they attempt to discover the keys to the whole realm of organizational behavior through the social network approach. Martin Kilduff is the Kleberg/King Ranch Centennial Professor of Management at the University of Texas at Austin. He is also editor of Academy of Management Review (2006–8) and coauthor of Social Networks and Organizations (with Wenpin Tsai; 2003). He has served on the faculties of Penn State and INSEAD, and he has been a visiting professor at Cambridge University, London Business School, Keele University, and Hong Kong University of Science and Technology. David Krackhardt is Professor of Organizations at the Heinz School of Public Policy and Management and at the Tepper School of Business at Carnegie Mellon University. Prior appointments include faculty positions at Cornell’s Graduate School of Management, the University of Chicago’s Graduate School of Business, INSEAD (France), and the Harvard Business School (Marvin Bower Fellow).

Structural Analysis in the Social Sciences Mark Granovetter, editor The series Structural Analysis in the Social Sciences presents approaches that explain social behavior and institutions by reference to relations among such concrete entities as persons and organizations. This contrasts with at least four other popular strategies: (a) reductionist attempts to explain by a focus on individuals alone; (b) explanations stressing the causal primacy of such abstract concepts as ideas, values, mental harmonies, and cognitive maps (thus, “structuralism” on the Continent should be distinguished from structural analysis in the present sense); (c) technological and material determination; and (d) explanations using “variables” as the main analytic concepts (as in the “structural equation” models that dominated much of the sociology of the 1970s), where structure is that connecting variables rather than actual social entities. The social network approach is an important example of the strategy of structural analysis; the series also draws on social science theory and research that is not framed explicitly in network terms but stresses the importance of relations rather than the atomization of reduction or the determination of ideas, technology, or material conditions. Though the structural perspective has become extremely popular and influential in all the social sciences, it does not have a coherent identity, and no series yet pulls together such work under a single rubric. By bringing the achievements of structurally oriented scholars to a wider public, the Structural Analysis series hopes to encourage the use of this very fruitful approach.

Recent Books in the Series Philippe Bourgois, In Search of Respect: Selling Crack in El Barrio (Second Edition) Nan Lin, Social Capital: A Theory of Social Structure and Action Roberto Franzosi, From Words to Numbers Sean O’Riain, The Politics of High-Tech Growth James Lincoln and Michael Gerlach, Japan’s Network Economy Patrick Doreian, Vladimir Batagelj, and Anujka Ferligoj, Generalized Blockmodeling Eiko Ikegami, Bonds of Civility: Aesthetic Networks and Political Origins of Japanese Culture Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj, Exploratory Social Network Analysis with Pajek Peter Carrington, John Scott, and Stanley Wasserman, Models and Methods in Social Network Analysis Robert C. Feenstra and Gary C. Hamilton, Emergent Economies, Divergent Paths Ari Adut, On Scandal: Moral Disturbances in Society, Politics, and Art

Interpersonal Networks in Organizations Cognition, Personality, Dynamics, and Culture

MARTIN KILDUFF University of Texas at Austin

DAVID KRACKHARDT Carnegie Mellon University

CAMBRIDGE UNIVERSITY PRESS

Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521866606 © Martin Kilduff and David Krackhardt 2008 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2008

ISBN-13 978-0-511-42908-8

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ISBN-13

978-0-521-86660-6

hardback

ISBN-13

978-0-521-68558-0

paperback

Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

Contents

Acknowledgments 1 Introduction I. Perceiving Networks 2 A Network Approach to Leadership 3 An Analysis of the Internal Market for Reputation in Organizations 4 Systematic Biases in Network Perception 5 Effects of Network Accuracy on Individuals’ Perceived Power II. 6 7 8 III. 9 10 11

The Psychology of Network Differences Social Structure and Decision Making in an MBA Cohort The Social Networks of Low and High Self-Monitors Centrality in the Emotion Helping Network: An Interactionist Approach Network Dynamics and Organizational Culture Network Perceptions and Turnover in Three Organizations Organizational Crises The Control of Organizational Diversity

12 Future Directions

page ix 1 13 39 59 84 101 131 157 181 208 236 259

References

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Index

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vii

Acknowledgments

We drew upon a number of published articles in preparing this book. We are happy to acknowledge the sources of these articles here. We thank our coauthors on these articles for their contributions and thank the journals for permission to reuse these materials. We also thank Ranjay Gulati, David A. Harrison, and Ajay Mehra for helpful comments during the preparation of the book. Chapter 2 draws from Balkundi, P., and Kilduff, M. 2005. The ties that lead: A social network approach to leadership. Leadership Quarterly, 16: 941–61. Chapter 3 includes material from Kilduff, M., and Krackhardt, D. 1994. Bringing the individual back in: A structural analysis of the internal market for reputation in organizations. Academy of Management Journal, 37: 87–108. Chapter 4 (and parts of Chapter 1) draws from Krackhardt, D., and Kilduff, M. 1999. Whether close or far: Social distance effects on perceived balance in friendship networks. Journal of Personality and Social Psychology, 76: 770–82. © 1999 by the American Psychological Association. Adapted with permission. Chapter 5 contains material reprinted from Krackhardt, D., Assessing the political landscape: Structure, cognition, and power in organizations, Administrative Science Quarterly, 35 (2) by permission of Administrative Science Quarterly, © 1990 Cornell University. Chapter 6 draws from the following three articles: Mehra, A., Kilduff, M., and Brass, D. J. 1998. At the margins: A distinctiveness approach to the social identity and social networks of under-represented groups. Academy of Management Journal, 41: 441–52; Kilduff, M. 1990. The interpersonal structure of decisionmaking: A social comparison approach to organizational choice. Organizational Behavior and Human Decision Processes, 47: 270–88; and Kilduff, M. 1992. The friendship network as a decision-making resource: Dispositional moderators of social influences on organizational choice. Journal of Personality and Social Psychology, 62: 168–80. © 1992 by the American Psychological Association, adapted with permission. Chapter 7 ix

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contains material reprinted from Mehra, A., Kilduff, M., and Brass, D. J., The social networks of high and low self-monitors: Implications for workplace performance, Administrative Science Quarterly, 46 (1) by permission of Administrative Science Quarterly © 2001 by Cornell University. Chapter 8 draws from Toegel, G., Anand, N., and Kilduff, M. 2007. Emotion helpers: The role of high positive affectivity and high self-monitoring managers. Personnel Psychology, 60: 337–65. Chapter 9 draws upon the following two articles: Krackhardt, D., and Porter, L. T. 1986. The snowball effect: Turnover embedded in communication networks. Journal of Applied Psychology, 71: 1–6 © 1986 by the American Psychological Association (adapted with permission); and Krackhardt, D., and Porter, L. T. 1985. When friends leave: A structural analysis of the relationship between turnover and stayers’ attitudes. Administrative Science Quarterly, 30 (2) © 1985, adapted and reprinted by permission of Administrative Science Quarterly, Cornell University. Chapter 10 includes material from Krackhardt, D., and Stern, R. 1988. Informal networks and organizational crises: An experimental simulation. Social Psychology Quarterly, 51: 123–40. Chapter 11 draws from two sources: Krackhardt, D., and Kilduff, M. 1990. Friendship patterns and culture: The control of organizational diversity. American Anthropologist, 92: 142–54; and Krackhardt, D., and Kilduff, M. 2002. Structure, culture and Simmelian ties in entrepreneurial firms. Social Networks, 24: 279– 90. Finally, Chapter 12 includes material adapted from the following sources: Ibarra, H., Kilduff, M., and Tsai, W. 2005. Zooming in and out: Connecting individuals and collectivities at the frontiers of organizational network research. Organization Science, 16 (4): 359–71. © 2005, the Institute for Operations Research and the Management Sciences, 7240 Parkway Drive, Suite 310, Hanover, MD 21076, USA, reprinted by permission; and Kilduff, M., Tsai, W., and Hanke, R. 2006. A paradigm too far? A dynamic stability reconsideration of the social network research program. Academy of Management Review, 31: 1031–48.

1 Introduction

Human beings are social creatures who depend on links to others to accomplish many of life’s tasks. The networks of relations within which each person is embedded include family, friends, and acquaintances. The embeddedness of human activity in such networks is true not just for primal activities such as child-rearing but also for economic activities such as finding a job (Granovetter, 1974). Indeed, business organizations themselves are held together not only by formal relations of authority but also by informal links that connect people across departmental and hierarchical boundaries. Starting with the Hawthorne studies (Roethlisberger and Dickson, 1939), researchers have investigated the importance of informal networks for job satisfaction (e.g., Roy, 1954), organizational conflict (e.g., Whyte, 1948), worker output (e.g., Jones, 1990), organizational power (e.g., Brass, 1984), and many other aspects of social and organizational life (see Kilduff and Tsai, 2003, for a review). Only recently, however, has research attention focused on actors’ perceptions of the structure of relations in social settings and on how actors’ individual differences may affect the network positions they occupy. These topics – actor perceptions and actor individual differences – provide the inspiration for our book. Actors’ perceptions of social networks within which they are embedded affect the decisions they make (see the discussion in Burt, 1982, chapter 5), and these perceptions are subject to considerable bias (Krackhardt, 1987a). How other people perceive the structure of relations surrounding the individual affects not only the individual’s power to act (Krackhardt, 1990) but also the individual’s reputation (Kilduff and Krackhardt, 1994). Actor individual differences can range from the visible attributes of ethnicity and gender (shown to affect patterns of centrality and exclusion in social networks – e.g., Mehra, Kilduff, and Brass, 1998) to specific personality characteristics such as self-monitoring (Snyder, 1974) that may be particularly 1

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Interpersonal Networks in Organizations

predictive of individuals’ network positions (Mehra, Kilduff, and Brass, 2001). This is a book about the cognitive and personality distinctiveness of individuals and the ways in which such distinctiveness affects relationships in organizations. The different chapters in the book unfold stories about how people perceive themselves and others in networks of friendship and advice, the biases people exhibit in their mental representations of who is connected to whom, the rewards and penalties that people experience as a result of such biases, and ways in which individual differences affect network positions and outcomes. We draw from cognitive network theory and an emerging personality approach to social network positions to examine (in organizational contexts) perceptions of networks, the psychology of network differences, and the dynamics of social network turnover, crisis, and culture. Unlike conventional network studies that tend to focus on interchangeable position holders, our focus throughout is on individual human beings and their distinctive patterns of network thinking and interaction. Across diverse research covering organizational behavior topics, we pursue an integrated focus on social ties both as they are represented in the perceptions of individuals and as they relate to individual differences.

Perceiving Networks Cognitions concerning social networks are important to the extent that people are uncertain concerning who is connected to whom. People may try to reduce such uncertainty by paying particular attention to the connections of those who are prominent. Savvy network entrepreneurs can take advantage of such uncertain knowledge to create social capital that may be merely fleeting but can, nonetheless, be valuable. The following story illustrates how a prominent banker used his visibility to bestow social capital that could be traded by his prot´eg´e for financial capital: At the height of his wealth and success, the financier Baron de Rothschild was petitioned for a loan by an acquaintance. Reputedly, the great man replied, “I won’t give you a loan myself; but I will walk arm-in-arm with you across the floor of the Stock Exchange, and you soon shall have willing lenders to spare” (Cialdini, 1989: 45). The baron in this story assumed that perceivers scan the social network connections of individuals for signals concerning difficult-to-discern underlying quality – such signals including connections to prominent

Introduction

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others. Research interest in such cognitive interpretations of network connections increased throughout the 1990s, concurrent with the cognitive turn in sociological approaches more generally (e.g., DiMaggio, 1997; Schwarz, 1998). Research concerning interorganizational relationships has increasingly focused on how network links affect perceived reputation and status (Zuckerman, 1999). Social networks are not just pipes through which resources flow; these networks are also potentially distorting prisms through which actors’ reputations can be discerned (cf. Podolny, 2001). Interest in a cognitive approach to social networks developed earlier in organizational behavior approaches than in more macro-oriented approaches. Pioneering work suggested that organizations and environments interacted as networked cognitions in the minds of participants: “what ties an organization together is what ties thought together” (Bougon, Weick, and Binkhorst, 1977: 626). Social equals in organizations tend to change their perceptions to establish consensus concerning environmental changes, whereas people connected to high-status individuals tend to be overly influenced by these high-status individuals’ perceptions of environmental change (Sampson, 1968; Walker, 1985). A recent review of the relationship between network connections and perceptions of the environment suggested that “knowledge emergence, as opposed to knowledge transfer, may occur . . . between social equals from different social circles, rather than between dyads divided by differences in mutual esteem and power” (Ibarra, Kilduff, and Tsai, 2005: 366). Building on this legacy of work in organizational behavior, our cognitive emphasis in this book is predicated on the finding that different individuals looking at the same networks tend to see different sets of connections (cf. Krackhardt, 1987a). To the extent that each individual occupies a specific position in a social network, the complexity of the network is likely to be viewed differently by each individual (Kilduff, Tsai, and Hanke, 2006). Some of these idiosyncratic views are likely to be more accurate in terms of mapping more closely on to a consensually validated representation of the network determined by the agreement of members of each interacting dyad. Such accuracy with respect to the organizational advice network can correlate with the power to influence others (Krackhardt, 1990). The perception of social networks begins as soon as an individual enters a new organizational context. People are motivated to generate an overall picture of a social group that they have joined, they seek to identify subgroups that might complicate or facilitate their putative plans, and they look for others to whom they can attach themselves (cf. von Hecker, 1993). Seeing the new interacting group into which they have just stepped as a distinct social system (cf. Campbell, 1958), people bring with them

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preconceptions from their interactions in previous social systems concerning the expectation that friendship overtures are likely to be reciprocated and the “transitivity” expectation that people who share a mutual friend will be friends themselves (Heider, 1958). These expectations bias the cognitive maps that people develop to represent social networks (Krackhardt and Kilduff, 1999). But people are not slaves to default expectations about friendship reciprocity and transitivity – people can also learn from vivid experiences (Ahn, Brewer, and Mooney, 1992) that social life can be riven with gaps where one might have expected ties (Janicik and Larrick, 2005). Each of us brings to our organizational sense making a different recipe for constructing representations of social networks. To the extent that people are cognitive misers who try to economize on memory demands (Fiske and Taylor, 1991), their mental representations of social networks are likely to exhibit simplifications such as excess clustering of people into densely connected groups and overattribution of popularity to people perceived to be central (Kilduff, Crossland, Tsai, and Krackhardt, forthcoming).

Individualizing Networks In bringing the individual back into social network research, we emphasize in this book not only the importance of individual cognition but also raise questions concerning how different types of people establish different network positions and experience different network outcomes. People differ with respect to whether or not they occupy brokerage positions in social networks (Burt, 1992) and outcomes from brokerage include both benefits such as higher job performance ratings (e.g., Mehra, Kilduff, and Brass, 2001) and potential costs such as reputation loss (e.g., Podolny and Baron, 1997). Despite this exploration in prior literature on the outcomes of brokerage, we still know relatively little about why some individuals rather than others are more central in social networks and occupy brokerage positions (Burt, 2005: 28). We explore in this book the likelihood that the patterning of social relations in organizations – including the elevation of some individuals to positions of centrality and brokerage – derives from stable individual differences. Visible individual differences such as ethnicity and gender function as bases for identification and network formation (Hughes, 1946). People tend to interact with similar others in organizations and this is particularly true for relations, such as friendship, that are more expressive than instrumental (Blau, 1977). Together with exclusionary pressures from the majority, this preference for similar, or “homophilous,” others

Introduction

5

may contribute to segregation within informal networks (Brass, 1985) and the marginalization of minority members. But going beyond this emphasis on demographic differences, we also explore in the book the likelihood that brokerage is related to selfmonitoring personality orientation. Those high in self-monitoring resemble successful actors in their ability to play different roles for different audiences (Snyder, 1987). Self-monitoring, in comparison to other personality variables, may be particularly relevant to the prediction of brokerage because of the theoretical (Day and Kilduff, 2003) and empirical (Flynn, Reagans, Amanatullah, and Ames, 2006) emphases on how personal identity affects the structuring of relationships. Other major personality variables tend to suffer from limited predictive validity when it comes to explaining why some individuals are more central than others (see, for example, the exemplary investigation of the network correlates of the Big Five personality constructs by Klein, Lim, Saltz, and Mayer, 2004). Because high self-monitors compared to low self-monitors tend to adapt their underlying personalities to allow themselves to become part of distinct social groups (Snyder and Gangestad, 1982), self-monitoring orientation is one key factor in understanding how individuals span across social divides in organizations.

Positioning the Book Interest in social networks has increased rapidly over the past decade, but few books focus specifically on interpersonal networks within organizations, and none pursue the topics we cover here. There are some excellent recent research monographs. The book by Noah Friedkin (1998) entitled A Structural Theory of Social Influence is unusual in bringing a social psychology approach to bear on questions of influence from a social network perspective. But there are few topics of overlap between that book and our own. The recent book by Peter Monge and Noshir Contractor (2003) entitled Theories of Communication Networks takes a programmatic approach in synthesizing the authors’ collaborative research in developing a multitheoretical and multilevel model. Again, there are few topics of overlap here. We see both of these books as companions to our own rather than as rivals. One of us has coauthored a recent social network book that critiques and extends social network theory in general in the context of offering a theoretical and methodological introduction (Kilduff and Tsai, 2003). There is one chapter in that book (pages 66– 86) that urges researchers to pursue structural research from a cognitive and individual difference perspective in pursuit of questions that have often been neglected. We see that chapter as whetting the appetite for

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Interpersonal Networks in Organizations

a more programmatic and comprehensive treatment of such topics as they apply to organizational behavior. Finally, the recent edited book by Cross, Parker, and Sasson (2003) focuses on networks in the knowledge economy with a particular appeal to managerial rather than research concerns. In studying interpersonal networks within organizations, we embrace a realist philosophy of science in terms of a research focus on three levels: the actual, the perceived, and underlying structures. The actual network of relationships in an organization can be perceived and experienced by individuals in many different ways, and, thus, actual and perceived networks can be discrepant with each other for any specific individual. In terms of the tendency for perceived networks to adhere to structural patterns, we know that perceptions of social relations tend to be shaped by cognitive heuristics such as the balance schema that individuals employ to make sense of complex realities (Krackhardt and Kilduff, 1999). Actual networks are also structured by underlying tendencies – for example, the tendency for people to cluster themselves together on the basis of similarity on dimensions that are considered important (such as ethnicity and gender – cf. Mehra et al., 1998). Our research engages all three levels of analysis, and investigates the discrepancies and tensions between these levels. We anticipate that the book will advance theory and research concerning organizational behavior and also push forward the social network research program itself. In tackling issues at the microbehavior level within organizations, we bring a traditionally sociological approach (structural social network theory) to dwell on topics (such as organizational turnover) typically studied from a more psychological approach. This book synthesizes research interests across the micro–macro divide to open new arenas for social network theory and methods. In bringing a distinctive research lens focused on interpersonal networks, we hope to unlock the whole realm of organizational behavior to the social network approach.

Overview of the Book This book emphasizes the importance of interpersonal networks, particularly friendship networks, for understanding people’s behaviors in organizations. There are three major sections, following this introduction. In the first part – “Perceiving Networks” – we focus on how individuals perceive networks in organizations, and explore the consequences of such perceptions. In the second part – “The Psychology of Network Differences” – we analyze how individuals differentially draw upon network resources, with particular attention on how network position and individual

Introduction

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personality contribute to performance outcomes. In the third part – “Network Dynamics and Organizational Culture” – we study how individuals in organizations respond to network influences, looking at turnover, crisis, and culture. A common theme runs throughout the book: We are bringing the importance of individual cognition, personality, and action back into a network research area that has tended to neglect if not completely ignore the importance of the microfoundations of structural constraint. Chapter 2, “A Network Approach to Leadership,” is a key resource for the whole book in providing a focused review of our major themes and their relevance for leadership in organizations. In this chapter, we articulate four interrelated principles that generate network theories and hypotheses and present a theoretical framework of leader effectiveness from the perspective of cognitive network theory. In Chapter 3, “An Analysis of the Internal Market for Reputation in Organizations,” we address whether perceptions of networks matter more than reality. We address how network perceptions are aggregated to create “real” networks, and how misperceptions of networks affect competitive outcomes in organizations, such as the reputations of individuals as good performers. We look specifically at the question of whether, if you are perceived by others in the organization to have a prominent friend, will this affect others’ perceptions of your job performance. In Chapter 4, “Systematic Biases in Network Perception,” we continue our focus on the systematic biasing of perceptions of organizational networks. We develop the theme of whether boundedly rational people in organizations tend to rely on heuristics to establish the friendship boundaries around themselves and others. In Chapter 5, “Effects of Network Accuracy on Individuals’ Perceived Power,” we examine the consequences of accurate perceptions of social networks in relation to individuals’ political power in organizational settings. The second part of the book, “The Psychology of Network Differences,” focuses on the use of networks with respect to decision making, individual performance in organizations, and helping behaviors. In terms of bringing the individual back in, we examine the possibility that individuals’ network positions are, to some extent, an expression of individual personality. In Chapter 6, “Social Structures and Decision Making in an MBA Cohort,” we address the issue of how people make decisions about complex issues, drawing upon network research that investigated such decision making in an environment overflowing with relatively complete information. We trace how individuals group themselves into clusters on the basis of ethnicity and gender, examine the extent to which the cohesion and structural equivalence perspectives predict these individuals’ decision making, and look at whether self-monitoring personality orientation offers a basis for understanding why some people

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Interpersonal Networks in Organizations

relative to others tend to draw more heavily upon network resources in making complex decisions. We follow up this self-monitoring theme in Chapter 7, “The Social Networks of Low and High Self-Monitors,” in our examination of whether low and high self-monitors build distinctly different network structures and whether self-monitoring and network position combine to affect individual performance in organizations. This chapter continues our attempt to open a productive new seam of structural research that brings together psychological richness at the individual level and sociological context at the network level. In Chapter 8, “Centrality in the Emotion Helping Network: An Interactionist Approach,” the last chapter in Part II, we again examine the twin effects of network position and personality, this time with respect to centrality in the emotion helping network in organizations. The third part of the book, “Network Dynamics and Organizational Culture,” takes a more dynamic perspective concerning how individuals in organizations are influenced in their behaviors and attitudes by those to whom they are connected either cognitively or actually. Chapter 9, “Network Perceptions and Turnover in Three Organizations,” investigates, from a social network perspective, the process and consequences of people leaving organizations. If someone occupying a role similar to my own leaves, how likely am I to also quit the organization? If I decide to stay despite the fact that a friend has left, what will be my attitude toward the organization – more or less committed? Chapter 10, “Organizational Crises,” continues the theme of network influence between and within organizational units in focusing on how internal and external friendship ties affect organizations’ responses to crises. Chapter 11, “The Control of Organizational Diversity,” advances a distinctive approach to organizational culture as a cognitive system developed and supported within local social networks. From this perspective, the organization resembles a magnetic field within which individual components attract and repel each other, with friends establishing mutually reinforcing interpretive systems. Our emphasis is on the local construction of cultural meaning within an overarching set of shared cultural understandings and the extent to which individuals’ cultural attitudes are controlled by their network ties. Finally, Chapter 12, “Future Directions,” looks forward to further research in terms of new approaches and phenomena to be addressed within the evolving research program that we have articulated.

Motivation for Writing This Book Because of the eclectic nature of the social network field, our research has appeared in leading journals in a variety of different areas including

Introduction

9

anthropology, psychology, sociology, and management. Indeed, we know of no other research program that has encompassed such different audiences. We have not had a chance to bring our different contributions together to emphasize the programmatic nature of our research interests. In this book, we bring our research themes under one overarching umbrella so that the significance of the work can be appreciated as a whole rather than in the particular fragments that happen to show up in each discipline’s journals. Rather than just reprinting articles, however, we have integrated material from different sources, updated our arguments, reduced redundancy, and emphasized core themes throughout. A major motivation for us in writing this book is the opportunity to comment on the different themes that we have been working on together for twenty years. We have synthesized and edited so that the book adds value beyond what has already been published. The book offers a theoretical and empirical alternative for organizational behavior research that often gets lost in the intricacies of microlevel attitudes at the expense of perceived and actual social context. Social network research has often critiqued other approaches in the social sciences. But it is time we went beyond critique to offer our fellow researchers a clear alternative that addresses topics they hold dear. In this book, we provide a blueprint for how theoretically motivated research can be accomplished on both traditional topics such as turnover and organizational culture as well as new topics such as the perception of social relations.

Target Readership This book is targeted at the research community of scholars interested in social network research. A primary audience consists of professors in schools of management, psychology departments, and sociology departments who want an up-to-date, theory-driven treatment of network research on organizational behavior topics. The book will also be of interest to doctoral students in the same areas. We are honored to have this book included in the distinguished Structural Analysis in the Social Sciences series edited by Mark Granovetter. In summary, the potential synergy between micro-organizational behavior research and social network approaches is huge. A focus on the social networks – both cognitive and actual – of organizational members is likely to enhance our understanding of organizational behavior, given the importance of social structures of interaction to the understanding of attitudes and behavior. The social network perspective has

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Interpersonal Networks in Organizations

traditionally avoided a focus on specific people, preferring to examine systematic patterns of interaction. Our aim in this book is to bring the individual back into the picture – to account for the cognitions and personalities of individuals in connection with the structural patterns that constrain and enable.

I Perceiving Networks

2 A Network Approach to Leadership

Good administrators sometimes fail to understand social structure and fail to anticipate its consequences for organizational survival. This can leave organizations vulnerable to manipulation by skilled political entrepreneurs. In one example, the entire top management team of a manufacturing company learned from a network analysis that the bomb threats, shootings, and vandalism threatening the future of the company were instigated by partisans of a lower-ranking manager, who had systematically recruited family, friends, and neighbors into the company over a thirty-year period. In a district desperate for jobs, these partisans felt loyalty to the informal leader, who had provided them information that allowed them to be first in line for vacancies on Monday morning. The CEO, confronted with an analysis of the deep cleavages existing in the social structure of the organization resulting from the informal patterns of recruiting over decades, had this to say about those who had been hired: “. . . they just seemed like waves of turtles coming over the hill; hired as they made it to our door” (Burt, 1992: 1). This story illustrates the gap at the heart of our understanding of organizational behavior. It illustrates how important it is for managers and would-be leaders to accurately perceive the network relations that connect people, and to actively manage these network relations. This story also illustrates how informal leaders who may lack formal authority can emerge to frustrate organizational functioning through the manipulation of network structures and the exercise of social influence. Our goal in this book is to investigate the implications of new directions in network theory that emphasize networks as both cognitive structures in the minds of organizational members and opportunity structures that facilitate and constrain action. In this chapter, we emphasize the importance of individual cognition for understanding social networks. We do this through an exploration of how the cognitions in the mind of the individual influence the network relationships negotiated by the individual 13

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Perceiving Networks

and how this individual network contributes to leadership effectiveness both directly and through informal networks. We understand “leadership” to be a general concept applicable at many different levels in the organization, and to include both formally designated leaders as well as informal leaders. We link together social cognitions and social structure to forge a distinctive network approach to leadership that builds upon, but extends, previous work in both the network and the leadership realms.

Organizational Network Research Core Ideas The organizational network perspective is a broad-based research program that continually draws inspiration from a set of distinctive ideas to investigate new empirical phenomena. The “hard-core” ideas at the heart of network research define its special character and distinguish it from rival research programs (cf. Lakatos, 1970). What are these ideas familiar to all organizational network researchers? At least four interrelated principles generate network theories and hypotheses: the importance of relations between organizational actors, actors’ embeddedness in social fields, the social utility of network connections, and the structural patterning of social life (Kilduff et al., 2006). An emphasis on relations between actors is the most important distinguishing feature of the network research program. As a recent historical treatment of social network research (Freeman, 2004: 16) pointed out, a core belief underlying modern social network analysis is the importance of understanding the interactions between actors (rather than a focus exclusively on the attributes of actors). An early treatment of network research on organizations stated that “the social network approach views organizations in society as a system of objects (e.g., people, groups, organizations) joined by a variety of relationships” (Tichy, Tushman, and Fombrum, 1979: 507), whereas the importance of understanding relationships as constitutive of human nature was stated as follows in a recent book: “Human beings are by their very nature gregarious creatures, for whom relationships are defining elements of their identities and creativeness. The study of such relationships is therefore the study of human nature itself” (Kilduff and Tsai, 2003: 131). Our network approach locates leadership in the relationships connecting individuals. The second principle that gives organizational network research its distinctiveness as a research program is the emphasis on embeddedness. For organizational network researchers, human behavior is seen as embedded in networks of interpersonal relationships (Granovetter, 1985; Uzzi, 1996). People in organizations and as representatives of organizations tend to enter exchange relationships not with complete strangers but

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with family, friends, or acquaintances. Embeddedness at the system level can refer to a preference for interacting with those within the community rather than those outside the community. We emphasize that people’s perceptions of others as leaders are reflected through the sets of embedded ties within which people are located. The third driving principle of social network research is the belief that network connections constitute social capital that provides value – including economic returns (Burt, 2000). As a previous review of network research on leadership pointed out, “Social capital is at the heart of social network analysis” (Brass and Krackhardt, 1999: 180). Depending upon the arrangement of social connections surrounding an actor, more or less value can be extracted (Burt, 1992; Gnyawali and Madhavan, 2001). At the system level, a generalized civic spirit emerges from and contributes to the many interactions of trust and interdependence between individual actors within the system (Coleman, 1990; Portes, 2000). Leadership, from the network perspective we develop, involves building and using social capital. The fourth leading idea distinctive to the social network research program – the emphasis on structural patterning – often leads social network research to be referred to as the “structural approach.” Network researchers look for the patterns of “connectivity and cleavage” in social systems (Wellman, 1988: 26). Not content with merely describing the surface pattern of ties, researchers look for the underlying structural factors through which actors generate and re-create network ties. At the local level surrounding a particular actor, the structure of ties can be described, for example, as relatively closed (actors tend to be connected to each other) or open (actors tend to be disconnected from each other) (Burt, 1992). At the system level, organizational networks can be assessed for the degree of clustering they exhibit and the extent to which any two actors can reach each other through a short number of network connections (e.g., Kogut and Walker, 2001). To understand who is a leader from a network perspective is to investigate the social-structural positions occupied by particular individuals in the social system. These four leading ideas – the importance of relationships, the principle of embeddedness, the social utility of network connections, and the emphasis on structural patterning – provide the common culture for organizational network research that allows the diversity of viewpoints from which fresh theoretical initiatives emerge (cf. Burns and Stalker, 1961: 119). Network research is also characterized by vigorous development of methods and analytical programs to facilitate the examination of phenomena highlighted by theory (see Wasserman and Faust, 1994, for a review of methods; and the UCINET suite of programs – Borgatti, Everett, and Freeman, 2002 – for statistical software).

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Perceiving Networks

The organizational network research program is progressive in the sense that new theory is constantly being developed from the metaphysical core of ideas that makes up the heart of the research program, highlighting new areas of application. It is the purpose of this chapter to highlight the area of leadership from a network perspective. The four leading ideas that comprise the intellectual source of theory development for organizational network research are best understood as mutually reinforcing core beliefs that, like the planks of a ship, keep the research program afloat – in terms of new theory development and exploration of new phenomena. At the level of network theory and research, all four ideas tend to be inextricably involved. We will invoke these ideas as appropriate throughout the chapter. In contrast to network research, traditional leadership research has focused on human capital attributes of leaders and situational attributes of leadership contexts. Human capital attributes of leaders include traits (e.g., House, 1977; Kenny and Zaccaro, 1983) and behavioral styles (e.g., Lewin, Lippitt, and White, 1939; Podsakoff, Todor, and Skov, 1982), whereas situational attributes of leadership contexts include task structure (Fiedler, 1971), the availability of leadership substitutes (Kerr and Jermier, 1978), the nature of the decision process (Vroom and Yetton, 1973), and the quality of leader–member exchange (Dansereau, Graen, and Haga, 1975; Graen, Novak, and Sommerkamp, 1982). A social network perspective does not eclipse the valuable results of conventional leadership research; rather, a network perspective can complement existing work without repeating it. In particular, in this review we amplify the voices that have called for a new understanding of leadership effectiveness to include leaders’ cognitions about networks and the actual structure of leaders’ ties (e.g., Hooijberg, Hunt, and Dodge, 1997; see also Bass, 1990: 19). As with all theoretical perspectives, the network approach has boundary conditions that limit its range of application. Social network processes are less likely to have the effects we discuss to the extent that organizations are characterized by perfect competition between equally informed actors all of whom have the same opportunities (see the discussion in Burt, 1992). (Even under conditions of perfect information, however, some actors are likely to be more influenced by social networks than others – see Kilduff, 1992.) A further limiting condition is the extent of work interdependence: Under conditions of low interdependence between actors and little or no social interaction, network processes and their effects will tend to be minimized. In network terms, leadership embodies the four principles that we articulated earlier. Leadership can be understood as social capital that collects around certain individuals – whether formally designated as leaders or

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not – based on the acuity of their social perceptions and the structure of their social ties (cf. Pastor, Meindl, and Mayo, 2002). Patterns of informal leadership can complement or complicate the patterns of formal leadership in organizations. Individuals can invest in social relations with others, can structure their social networks by adding and subtracting relationships, and can reap rewards both in terms of their own personal performance and organizational unit performance (Sparrowe, Liden, Wayne, and Kraimer, 2001). But embeddedness in social networks always involves the paradox that social relations, particularly those outside the immediate circle of the individual, may be difficult both to perceive accurately and to manage (cf. Uzzi, 1997). Thus, although the social structure of the organization determines opportunities and constraints for emergent leaders, the social structure is not within the control of any particular individual.

Leadership and the Structure of Ties We start our network approach to leadership theory with a discussion of actor cognitions concerning networks, move out to the inner circle around the actor, and then further zoom out to include progressively more of the social structure of the organization and the interorganizational realm. The theoretical framework is illustrated in Figure 2.1, and represents a tentative model of leadership effectiveness from a network perspective. We provide an overview of the causal connections of the model before zooming in to discuss in more detail the dynamics within each part of the model. As Figure 2.1 shows, the first step in the conceptual model indicates that leaders’ cognitions about social networks affect the “ego networks” that surround each leader. Cognitive network theory (see Kilduff and Tsai, 2003: 70–9, for a review) suggests that people in general shape their immediate social ties to others to be congruent with their schematic expectations concerning how relationships such as friendship and influence should be structured. The schematic expectations of leaders affect their ability to notice and change the structure of social ties (e.g., Janicik and Larrick, 2005). Thus, cognitions in the mind of the leader are the starting point for our theorizing concerning the formation of ties connecting the leader to others. The network cognitions of leaders concerning such crucial organizational phenomena as the flow of social capital within and across organizational boundaries and the presence and meaning of social divides are hypothesized to affect the extent to which leaders occupy strategically important positions in the organizational network. An accurate

18

•Range • Cohesion

•Accuracy

•Schemas

Leader Effectiveness

• Mentoring distributed leadership • Brokering

Organizational Network • Centrality

• Coalition-building

Intra-organizational Level

--------------------------------------

•Innovation

• Growth

•Survival

Organizational Level

Figure 2.1. Theoretical framework linking a leader’s network accuracy to leader-relevant outcomes.

•Density

Network Acuity

Ego Network

•Alliances

• Boundary spanning

Interorganizational Network

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perception of the informal influence network can itself be a base of power in the organization (see Chapter 5) and can facilitate the leader’s ability to forge successful coalitions (Janicik and Larrick, 2005). We extend these insights to hypothesize that the acuity of leader cognitions will affect the extent to which a leader plays a strategically important role in the relevant interorganizational network. We know of no research bearing on this thesis, although recent work concerning interorganizational relationships increasingly concerns itself with hypothesized perceptual processes such as organizational reputation and status (e.g., Podolny, 1998; Zuckerman, 1999). The extent to which a leader plays a role in these three actual networks – the ego network, the organizational network, and the interorganizational network – is hypothesized to affect leader effectiveness. This critical hypothesis derives from our basic understanding of how the four guiding principles of the network approach extend leadership theory. Modern concepts of leadership identify the relational content of the interaction between people as the key aspect involved in the structuring of situations and the altering of perceptions and expectations (e.g., Bass, 1990: 19). Modern network theory suggests that individuals who are central in the immediate networks around them and in the larger networks that connect them to others throughout the organization and beyond the organization are likely to acquire a particular type of expert power: knowledge of and access to those few powerful others whose words and deeds control resource flows and business opportunities (e.g., Burt, 2005). Leaders may not be able to move into the center of every important network, of course. Embeddedness in one social network may come at the price of marginality in another network. There are trade-offs involved in building social capital, particularly when brokerage across social divides may engender distrust rather than gains. One blow-by-blow account of an organizational power struggle contrasted the networking strategies of two combatants for sole control of the CEO position they currently shared. Whereas co-CEO Louis Glucksman was central within the Lehman Brothers organization as a whole and occupied a particularly strategic position among the traders, his rival and co-CEO Pete Petersen neglected internal networking in pursuit of connections with the leaders of other organizations (Auletta, 1986). Both men were effective leaders – Glucksman contributing to internal effectiveness and Petersen building and maintaining the external relationships that brought contracts to the partnership. But both had built quite different social network bases of power. The role of external affective ties with the representatives of other organizations in providing vital help to companies in financial trouble has been emphasized by research on the survival prospects of small firms

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Perceiving Networks

in the New York garment industry (Uzzi, 1996). More generally, the organizational theory and strategy literatures have examined the extent to which ties between organizations constitute a knowledge base important for outcomes such as firm growth (e.g., Powell, Koput, and Smith-Doerr, 1996), new ties (e.g., Gulati and Gargiulo, 1999; Larson, 1992), and innovation (Hargadon and Sutton, 1997). Thus, the extent to which leaders are effective in terms of accessing important resources is likely to depend on the social-structural positions they occupy in the key networks within and between organizations. What are the outcomes associated with leader effectiveness from a social network perspective? We have thus far mentioned such aspects of leader effectiveness as organizational growth, survival, and innovation. These are the responsibility of formal leaders and are outcomes at the organizational level of analysis. As Figure 2.1 summarizes, leader effectiveness from the network perspective that we articulate would also include such components of internal organizational functioning as coalition building, mentoring, and brokering. These are intrinsically networking outcomes of both formal and informal leadership that can enhance coordination across functions within the organization. We return to these internal measures of leader effectiveness later in the chapter. The model outlined in Figure 2.1 necessarily simplifies the relationships between cognition, social networks, and leadership effectiveness. We neglect, for example, the ways in which occupancy of social-structural positions in networks affects individuals’ cognitions and expectations about networks (see Ibarra et al., 2005, for a review). The organization and the environment within which it operates can be jointly considered a set of cyclical processes captured in networks of cognitions (cf. Bougon et al., 1977). We focus in this chapter on leadership, and therefore emphasize the proactive enactment of outcomes leading to leader effectiveness.

Network Cognition and Leadership A key discovery of modern social network research is that cognitions matter (see Chapter 3), and thus we start the in-depth discussion of the theoretical framework with an emphasis on network cognition, a topic relatively neglected within conventional leadership research (but see early leader-member exchange [LMX] work on whether peers within units accurately perceive the quality of dyadic leader–subordinate relations – Graen and Cashman, 1975). Depending upon how the boundary is drawn around a particular individual in an organization, that individual may or may not appear to be influential in the eyes of others. That implicit leadership theories may be triggered by the structural position

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of certain individuals in the eyes of others is a possibility hinted at in recent leadership theory (Lord and Emrich, 2001) but which has yet to be systematically examined. From the perspective of perceivers located in small groups, certain actors may appear influential, but perceivers surveying the larger context of the whole organization may dismiss these same actors as relatively inconsequential (see the discussion in Brass, 1992). Conversely, people who seem relatively powerless within one local group may be revealed to have close connections with powerful others outside the group. Thus, we organize our discussion by progressively zooming out from individuals’ network cognitions to include expanding social circles within and beyond the organization. From a network perspective that emphasizes the importance of relationships, embeddedness, social capital, and social structure, the ability of formal or would-be informal leaders to implement any leadership strategy depends on the accurate perception of how these principles operate in the social context of the organization. To be an effective leader of a social unit is to be aware of (a) the relations between actors in that unit, (b) the extent to which such relationships involve embedded ties including kinship and friendship, (c) the extent to which social entrepreneurs are extracting value from their personal networks to facilitate or frustrate organizational goals, and (d) the extent to which the social structure of the unit includes cleavages between different factions. The accurate perception of this complex social reality is fraught with difficulty, and, therefore, network cognition is an arena for innovative research. If a leader wants to use social network ties to lead others, the leader must be able to perceive the existence, nature, and structure of these ties – not just the ties surrounding the leader, but the ties connecting others in the organization both near and far. Actors who are perceived to have power in terms of the structure of their social ties to others may wield influence even though they seldom or never exercise their potential power (Wrong, 1968; see the discussion in Brass, 1992: 299). To a considerable extent, organizations and environments exist as cognitions in the minds of leaders and followers within organizations (Bougon et al., 1977; Kilduff, 1990) and in the interorganizational arena of reputation and status (Podolny, 1998; Zuckerman, 1999). Thus the question arises, how do people perceive network ties within and between organizations? How does anyone tell whether, for example, two individuals are personal friends? Even a small organization of fifty people represents a considerable cognitive challenge in terms of trying to perceive accurately the presence or absence of 2,450 friendship links between all pairs of individuals, links that may well be relatively invisible except to the individuals concerned. To create and manage the networks that promote leadership effectiveness, it may be necessary to possess an

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accurate representation of network links involving not just friendship and kinship, but also advice, communication, and other important network ties. What happens when formal leaders pay no attention to the four principles we have enunciated as representing the network approach to leadership? Is there any penalty consequent upon leader ignorance of social relations inside organizations, leader blindness to the embeddedness of working relationships in extra-organizational arrangements such as kinship, leader neglect of the extent to which social entrepreneurs manipulate embeddedness for their own ends, and leader unconsciousness of the social cleavages within the organization? The answer, provided in the case study alluded to in the opening paragraph of this chapter, is shocking in its illustration of diseased social capital. When the management fired, in a routine cost-cutting exercise, the informal leader to whom so many people were beholden not just for jobs but for the references necessary to actually get jobs inside the industrial plant, deep trouble ensued between employees loyal to the informal leader and those helping the management keep the industrial plant solvent. Shootings, bomb threats, and leakings of confidential management documents were the order of the day. The formal leadership team had no comprehension of what was happening, not having noticed that the workforce included so many people with strong social ties to a particular individual. (For the full case study, see Burt and Ronchi, 1990.) The CEO in this case was a good administrator and a skilled engineer who failed to understand the necessity of keeping track of the social structure of competition within and outside the organization. Social networks interpenetrate the boundary between employees and nonemployees, and the management of this boundary has important consequences for organizational functioning. Job applicants with social contacts (such as friends) inside the organization can exploit social capital advantages to extract critical information at both the interview and job offer stages. These referred individuals (compared to those who are not referred by current organizational members) tend to present more appropriate r´esum´es and to apply when market conditions are more favorable (Fernandez and Weinberg, 1997). Referred individuals have a significantly greater likelihood of being offered a job as a result of these advantages. Further, referrals (relative to nonreferrals) can use inside knowledge to boost their starting salaries in the negotiation process. Thus, what might appear to a corporate leader as a systematic process of institutionalized racism involving higher starting salary increases to ethnic majorities relative to ethnic minorities can be revealed through social network analysis as a function of who has friends inside the organization (Seidel, Polzer, and Stewart, 2000). The fairness of a hiring process

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may be fundamentally compromised because it is invisibly embedded in kinship and friendship networks. The perception of this otherwise invisible process of homophilous hiring is crucial to any effort by the leadership team to increase workforce diversity. The explicit management of external ties to recruit new members who are known to existing members of the organization can enhance the organization’s economic returns (Fernandez, Castilla, and Moore, 2000). If leaders comprehend the social network relationships not just among organizational employees but also between employees and those outside the organization, then leaders can build the social capital of the organization by putting individuals’ personal social networks to work for the organization’s benefit. Typically, managers are busy people whose work is fragmented and interrupted (Mintzberg, 1973). Much of our research in organization theory focuses on the formal arrangement of titles, offices, and reporting relationships, whether with respect to the integration and differentiation of the organization (e.g., Lawrence and Lorsch, 1967), the inertia of the organization (e.g., Hannan and Freeman, 1984), or the ceremonial fac¸ade created to be isomorphic with institutional demands (Meyer and Rowan, 1977). Leadership research, to the extent that it has considered social network relations, has also focused overwhelmingly (from an LMX perspective) on managers and the extent to which subordinates, for example, established networks that mirror those of their formally appointed managerial leaders (Sparrowe and Liden, 2005). The cognitive revolution in leadership research has focused not on the cognitions of leaders, but on leadership factors in the minds of followers (Eden and Leviatan, 1975; Lord and Emrich, 2001). There is an opportunity to extend both LMX research and cognitive approaches to leadership from the perspective of cognitive network theory (see Kilduff and Tsai, 2003: 70–9, for a review) with a focus on how leaders and followers comprehend (a) the structure of social relations (cf. Chapter 5), (b) the embeddedness of economic action in affect-laden networks (cf. Uzzi, 1996), and (c) the opportunities for social entrepreneurship across structural divides (Burt, 2005). A greater understanding of how leaders and followers comprehend the social structure from which action in organizations proceeds can enhance research on the management of relationships. Accuracy From a cognitive network theory perspective, leadership involves not just social intelligence (i.e., the accurate perception of social relationships in organizations) but also the management of others’ perceptions. First, let

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Perceiving Networks

us consider accuracy. People perceive the same network differently, with some individuals achieving a high degree of accurate perception, whereas other individuals lead their organizational lives in relative ignorance of the actual network of relationships within which work is accomplished (Chapter 3). In general, perceptions of networks involving sentiment relations such as friendship suffer from a series of predictable biases. People prefer to see their own relationships as reciprocated – they prefer not to perceive their friendship overtures as unrequited. Similarly, people prefer to believe that their friendship circles are transitively complete – they like to believe that their own friends are friends with each other (Heider, 1958). This cognitive balance schema operates also as a default mechanism for filling in the blanks concerning ties between relative strangers at the individual’s perceived organizational network’s periphery. In the absence of contrary information, people tend to assume that friendship ties of others are reciprocated, and that two friends of a distant stranger are themselves friends (Freeman, 1992; Chapter 4). These cognitive distortions can affect leadership emergence. People in organizations see themselves as more popular than they actually are (Krackhardt, 1987a), a tendency that can, perhaps, lead some individuals to neglect the vital process of maintaining their social capital (on the assumption that they are already popular), whereas other individuals, through a self-fulfilling prophecy process, may transform the illusion of popularity into actual friendship links that initially did not exist. Assuming that others like them, some people may reciprocate nonexistent liking and thereby create friends. Slight initial differences with respect to how people perceive their connections to others can potentially lead to cumulative advantages through this self-fulfilling prophecy process. Further, there may be a tendency to perceive popular actors as being even more popular than they really are (Kilduff et al., forthcoming). Human beings, in their perceptions of social networks, are “cognitive misers” (Chapter 4) who may tend to simplify networks by perceiving them as dominated by a few central actors even if the actual network has no dominant cluster. A misattribution of popularity to a few actors can result in these actors actually increasing their popularity. An emerging leader who is perceived to be popular may benefit from a bandwagon effect: People may want to associate with someone perceived to be a rising star. On the other hand, the perception that a social network is dominated by an elite group of leaders may discourage those who perceive themselves on the periphery from attempting to pursue leadership options.

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Schemas New research (Kilduff et al., forthcoming) suggests that individuals may tend to perceive friendship networks in organizations as small worlds. Small world network structures are unusual in that they exhibit both high local clustering and short average path lengths – two characteristics that are usually divergent (Watts and Strogatz, 1998). Clustering refers to the extent that actors are connected within local groups, whereas path lengths refer to the number of network connections between one actor and another in the network. A small world network resembles the huband-spoke structure of the U.S. commercial air traffic system: local hubs with lots of connections and short average path lengths because journeys from one city to another are routed through the hubs. (Compare this with the distinctly non-small world of the U.S. interstate highway system.) The small world effect, investigated originally in the 1960s by Milgram (1967), has become a burgeoning area of organizational social network research (e.g., Kogut and Walker, 2001; Uzzi and Spiro, 2005). As social networks become larger and more global, the discovery that some of the largest social networks such as the World Wide Web exhibit small world properties has excited considerable research interest (see Dorogovtsev and Mendes, 2003, for a review). Leadership within extremely large networks is a neglected topic but one that seems tractable from a small world perspective, given that small world networks are organized for efficient communication and coordination. We focus here on the possibility that some individuals more than others misperceive the extent to which organizational networks resemble small worlds (Kilduff et al., forthcoming). Such a bias has distinct implications for leadership research. Simplifying perceptions to perceive a friendship network as a small world offers a considerable advantage to the aspiring informal leader in terms of reducing the cognitive load required to keep track of so many different relationships. The rules for creating a cognitive map of the friendship network are relatively simple from this perspective: Put similar people (with similarity defined on some relevant dimension such as demography or interests) into clusters and connect the clusters. Further research is needed to examine the extent to which the match between the “small worldedness” of the individual’s cognitive network and the small worldedness of the actual network predicts leader effectiveness. Cognitive network schemas play a significant role in one important aspect of leadership, namely coalition building (cf. Stevenson, Pearce, and Porter, 1985). Leaders are constantly involved in appointing people to task forces and committees. Ensuring that these teams consist of the right

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Perceiving Networks

balance of people can make the difference between gridlock and effective action. In a pioneering set of studies, researchers found that individuals with experience of networks characterized by disconnections – structural holes – were better at perceiving the potential to bridge structural holes by identifying suitable collaborators – a key to successful coalition (Janicik and Larrick, 2005). By making sure that different constituencies are represented at the top of the organization, the leader may facilitate the engagement of widely different groups in the organizational mission. But in order to make these representative appointments, the leader must first be able to accurately perceive any existing social system cleavages. This recent research on the structural hole schema is interesting in suggesting that people are able to move beyond reliance on default modes of thinking (such as balance) when trying to make sense of the social network in organizations. People learn from experience to expect certain patterns in the social world, and tend to see new situations in the light of their anticipations. Thus, the leaders of an organization, familiar with the patterns of activity taking place from day to day, may impose on these patterns of interaction their own preconceptions of who shows up for meetings. Leaders anticipate that regular attendees will show up and remember these people as having showed up even if they did not, while forgetting that more peripheral members of the organization were actually present on a specific occasion (cf. Freeman, Romney, and Freeman, 1987). Further, people in general tend to perceive themselves to be more central in friendship networks in organizations than they actually are (Krackhardt, 1987a). Thus, network cognition can depart from actual patterns of network activity, with consequences for the leader’s ability to uncover political conflicts, spot communication problems between culturally divided groups, avoid reliance on problematic individuals for the transmission of important resources, achieve strategic objectives through the appointment of key people to influential positions, and manage relations within and across departments (Krackhardt and Hanson, 1993). Leaders who perceive important social networks accurately in their organizations are likely themselves to be perceived as powerful (Chapter 5). This perceived power can itself represent an important supplement to formal authority. But for those who want to span across structural holes and gain the reputed benefits of this activity, it may be crucially important to be perceived by others as not pursuing personal agendas (Fernandez and Gould, 1994). Social perceptions take place within reputational markets (Chapter 3) and, in the subtle battle to achieve prominence, individuals may strive to appear to others to be associated with leaders of high status. The perceived status of exchange partners can act like a distorting prism to filter attributions concerning the focal individual (cf. Podolny, 2001).

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Individuals move in and out of organizational contexts, and as they do so, their structural positions change. In one context, someone assumes a leadership position, but the same individual may be a follower in another context in the same organization. Partly this is due to shifting perceptions. Individuals self-perceive themselves as powerful in some contexts and as less powerful in other contexts, and their self-attributions may be concordant with or discrepant with others’ attributions. Actors in organizations may exert power without having to request compliance with their demands, simply on the basis of possibly false perceptions: Just as players can successfully “bluff” in poker, employees can also act as if they control scarce resources, as if they were potentially powerful. . . . Persons who are in a position to control information can withhold, disclose, and modify it in order to influence others’ attributions of power (Brass, 1992: 299). Thus, the importance of perceptions of leadership emergence and individual influence may reside in the extent to which they are never tested. In one recorded instance of a battle between dual CEOs for the exclusive control of the Lehman Brothers investment banking house, Louis Glucksman convinced his rival Pete Petersen that Petersen had lost friendships with board members, whereas Glucksman had retained their regard. But neither rival checked to see whether their perceptions of their social relations with the all-important board members were accurate (Auletta, 1986). To summarize our general ideas concerning the importance of acuity in leaders’ perceptions of social networks, we indicate in Figure 2.1 that accuracy is likely to improve the extent to which a leader occupies a strategic position in three social network structures relevant to organizational behavior: the ego network, comprising the individuals immediately connected to the leader; the complete organizational network, comprising not just direct connections but also the leaders’ indirect connections to everyone in the organization; and the interorganizational network of relationships important to the leader’s work outside the focal organization. In Figure 2.1, we also include the role of cognitive schemas in determining the match between leaders’ perceptions of networks and actual networks. We need more research concerning the extent to which cognitive schemas help or hurt leaders develop accurate maps of the social networks within which they operate. Whereas research on cognitive shortcuts implies that perceivers who rely on such shortcuts tend to make errors (Kahneman and Tversky, 1973), others see positive benefits deriving from the use of such schemas (e.g., Taylor and Brown, 1988), including greater satisfaction in close relationships (Murray, Holmes, and Griffin, 1996;

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see Kenny, Bond, Mohr, and Horn, 1996, for evidence concerning the effects of relational schemas on accuracy). We have spent considerable time on the social cognition of networks of relationships given the growing recognition within leadership research of how leader cognitions affect leader behaviors with implications for both leader effectiveness and organizational effectiveness (e.g., Hooijberg et al., 1997). Leadership research has long recognized the importance of implicit leadership schemas in the minds of followers (see Lord and Emrich, 2001, for review). Building on this emphasis on cognition and cognitive schemas, we seek to extend leadership research from a distinctively network emphasis on social relations, embeddedness, social capital, and social structure.

The Ego Network Moving on from the network cognitions in the head of the individual, we now consider the social circle of relations actually surrounding the individual. A strong argument could be made that it is this ego network that fundamentally affects all the other network relationships a leader forms and influences – hence the centrality of the ego network in Figure 2.1. It is this personal network that forms the basis of, for example, the influential structural hole perspective (Burt, 1992, 2005). A major task of future research is to assess whether the structure of direct connections leaders have with colleagues is as important as the structural hole approach implies, or whether more indirect connections involving intermediaries can dampen or enhance leadership effectiveness, as implied in embeddedness research (Burt, 2007; Uzzi, 1996). Density A key theoretical concept concerning how direct connections within the ego network relate to leadership is density, as indicated in Figure 2.1. Individuals whose social contacts are themselves connected to each other have dense social circles, whereas individuals whose social contacts have few connections among themselves have sparse social circles (Wasserman and Faust, 1994). Members of a dense network tend to share similar attitudes and values toward the leader of the organization (Krackhardt, 1999). From a network perspective, whether the members of a dense network tend to enhance or neutralize the leader’s effectiveness is likely to depend upon whether the shared attitudes toward the leader are positive or negative. A dense network of people favorably disposed toward the

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leader represents a pool of social capital available to the leader. Messages communicated to this group are likely to be favorably received and expeditiously transmitted. A dense network of people negatively inclined toward the leader represents a potentially distorting prism, likely to take any message or initiative from the leader and cast it in the most unflattering light. More research is needed on the ways in which dense networks distort or enhance leadership initiatives. Range Structural-hole theory (Burt, 1992), following on from the weak-tie hypothesis (Granovetter, 1973), suggests that individuals whose personal contacts include a diverse range of disconnected others gain benefits. These benefits (including faster promotions – Burt, 1992) derive from the information and control possibilities of being the “third in the middle” between other individuals who must pass resources and information through the focal individual. Thus, the focal individual has access to diverse communications within his or her immediate contacts. If the individual (conventionally referred to as “ego” in network research) is embedded in a clique, then the diversity of information and resources reaching ego from immediate contacts may be low. Further, the opportunity for ego to play an informal leadership role, distributing ideas and other valued resources throughout the immediate social circle, vanishes if ego is simply one more person in a highly connected group. As simple as the implied principle appears to be – connect oneself to diverse others who themselves are not connected to each other in order to enhance leadership potential in the informal network of relationships – it is much harder to realize than might at first be apparent. The principle of embeddedness operates strongly in this context. Simply stated, individuals prefer to associate with homophilous others – those who are similar to themselves (McPherson, Smith-Lovin, and Cook, 2001). This tendency is likely to be just as strong among putative leaders as it is among people in general – even economic transactions at the firm level tend to be embedded in kinship and friendship networks (Uzzi, 1996). Homophilous networks represent information restriction (Popielarz, 1999). Individuals embedded in such networks, established not just in terms of kinship but also on the basis of proximity (Festinger, Schachter, and Back, 1950), ethnicity, or gender (Mehra et al., 1998), are likely to experience strong cohesion (many ties among the similar others) but also information restriction. Groups as powerful as the dominant coalition (Cyert and March, 1963), the top management team (Hambrick and Mason, 1984), and the board of directors (Palmer, 1983) may exhibit in-group homogeneity under the pressures of ease of communication,

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shared backgrounds, and demographic similarity (see the review in Westphal and Milton, 2000). Social capital advantages are likely to be significantly diminished as leaders embed themselves in homogenous groups, leading to negative effects on market share and profits (Hambrick, Cho, and Chen, 1996). Business survival prospects tend to be better for those businesses whose owners establish a large range of personal contacts with important representatives of the task environment relative to those owners who establish a smaller range of such contacts (Oh, Kilduff, and Brass, 2005). Cohesion The cohesiveness of a dominant coalition may be sharply increased if the coalition perceives it is challenged by a set of actors (pursuing a hostile takeover, for example) or by negative outcomes of previous decisions (Kilduff, Angelmar, and Mehra, 2000). This increased homophily, while facilitating coordinated action by the top management team, may adversely restrict decision-making options. The extent to which leaders turn to their personal contacts for advice following poor firm performance predicts subsequent tendencies to minimize changes in corporate strategy (McDonald and Westphal, 2003). There are strong pressures in organizations for people to agree with their personal friends concerning important values and ideas. For an informal leader, embedded in a coalition of like-minded individuals, to challenge the hegemony of the official culture is always possible. But it is much more difficult for an informal leader to resist the social pressure from within his or her social circle to agree with close friends concerning how to interpret widely shared core values (Chapter 11). It is interesting to note that, from a network perspective, the social pressure on ego differs little irrespective of the size of the clique within which ego is embedded, given that the clique contains people who all have ties to each other within the clique but no common ties to those outside. Whether ego is embedded in a three-person clique or a larger clique, ego still experiences group pressure to conform (Simmel, 1950). This pressure becomes powerful as soon as a dyadic interaction (between two people) expands to include three people. To the extent that a leader belongs to two or more of these cliques (of three or more people), the leader is vulnerable to cross-pressures from the different cliques to which he or she belongs. Different cliques tend to reinforce different interpretations of reality, and these discrepant interpretations may place the leader, who links the two different cliques together and who may play a brokerage role between these different groups, in a complicated situation. Each clique

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may present the leader with demands that, considered jointly, may be difficult to meet. One case study described how an informal leader who strongly favored the ongoing unionization drive in an entrepreneurial company found himself unable to use his influential position in his personal social circle to influence others. This individual was a member of eight different threeperson friendship cliques and was thus “frozen by the set of constraints imposed by the numerous cliques” (Krackhardt, 1999: 206). Three of this person’s cliques contained vociferous opponents of unionization. So unpleasant was his position in his social circle that he resigned from the firm ten days before the unionization vote was taken and rejoined the firm two days after the vote had failed. This individual’s apparent power in the social circle of personal friends was stultified by his embeddedness in cohesive, but mutually discrepant, cliques. Informal Leadership Emergence Within the social circle surrounding the formal leader, there are likely to be some individuals who play informal leadership roles. These informal leaders tend to spring up in teams in which formally appointed leaders play little or no role in the coordination of team activity (perhaps because the formal leaders are focused on activities external to the team). Thus, informal leadership is likely to be a feature of teams in which formal leadership is, relatively speaking, absent. One study of leaderless teams found that informal leaders disproportionately influenced team efficacy – the extent to which team members evaluated their abilities to perform specific work-related tasks (Pescosolido, 2001). Such informal leaders also play a role in regulating team members’ emotions (Pescosolido, 2002). Key process variables, such as team efficacy and team emotions, affect team performance (Barsade, 2002; Gibson and Vermeulen, 2003). Given the potential power of these informal leaders to manage the cognitions and emotions of group members, even in the absence of any formal authority, formally appointed leaders’ relationships with these informal leaders become more important than perhaps approaches that have focused on leader–member exchange relations have recognized. We suggest that within the leader’s in-group there are some ties that are more crucial for leader effectiveness than others; and, outside the leader’s ingroup, neglect of individuals with considerable social influence is likely to imperil leader effectiveness. To summarize this section is to recognize that structural hole theory (Burt, 1992) suggests that would-be leaders should structure their interpersonal networks to reach diverse constituencies, using relatively few ties

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to expand the range of information and resources accessed. An effective network strategy, according to this interpretation of structural-hole theory, is likely to involve leaders building links to a variety of different constituencies and delegating to trusted “lieutenants” the task of managing relationships with the other members of each constituency. Information would flow to leaders through the trusted lieutenants from all around the organization. It is with each trusted lieutenant that the informal leader develops and maintains a strong tie (as suggested in the dyadic approach to leadership – see Dansereau, 1995, for a review). It is this emphasis on extending the leader’s ties throughout the organization that we turn to next.

The Organizational Network There are some caveats to the “divide and conquer” strategy advocated from the influential structural-hole perspective (Burt, 1992, 2005). From this perspective, would-be leaders are recommended to divide social networks in organizations into non-overlapping groups and to harvest social capital benefits from brokering information and other resources between these groups. However, as structural-hole theory recognizes, there are some groups (such as boards of directors) whose importance may require a much more intensive relational strategy. To the extent that all the members of a particular group have power over ego’s leadership effectiveness, it makes sense for ego to invest in a personal relationship with every member of the group. Second, the effectiveness of informal leadership is likely to depend not just on direct links to others but also on the pattern of links beyond the immediate ties. The important idea here, then, is that the structural position of ego in the social network affects the leadership potential of the individual in the organization, and this principle extends beyond the immediate social circle of the individual. From an embeddedness perspective (Uzzi, 1996, 1997), an effective leadership network is a multistep process, only one step of which is under the control of ego. First, ego needs to build ties to individuals who represent access to and from key constituencies within and outside the organization. But, second, ego needs to monitor whether representatives of these key constituencies themselves have access to networks. And third, ego must monitor the interrelationships between these representatives (cf. Sherony and Green, 2002; Sparrowe and Liden, 2005). Leadership success can crucially depend upon these secondary networks and the interrelationships between people beyond the leader’s ego network. At present, we know little about how a leader within an organization functions in the context of the social networks of informal leaders who

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may or may not be occupying positions of official authority. Informal leaders, typically of lower rank than the primary leaders (to whom they may or may not report directly), wield considerable influence derived from their positions in the social network (Mechanic, 1962). We can glean some insight into how a leader at one level can benefit or suffer from the activities of socially well-connected informal leaders by considering the literature on substitutes for leadership. Leaders whose subordinates possess expert power, for example, may find themselves to be relatively redundant. Subordinate expertise can act as a substitute for leadership in some cases and in other cases subordinates, representing the leader, can deputize for the leader (Gronn, 1999; Kerr and Jermier, 1978; Podsakoff and MacKenzie, 1997). This form of distributed leadership (Mayo, Meindl, and Pastor, 2003) is still poorly understood. Mentoring Distributed Leadership From the network perspective articulated in this chapter, leader effectiveness involves building social capital that benefits individuals in the organization and extending the social networks of subordinates to facilitate career advancement. One measure of leader effectiveness, therefore, is the success of the leader in promoting the social networks and leadership potential of subordinates. By systematically sponsoring subordinates’ development of social capital through introductions to key people in the organization and the environment, leaders can enhance the overall leadership potential in the organization and groom their subordinates for organizational success. Hence the emphasis on the mentoring of distributed leadership as an aspect of leader effectiveness in Figure 2.1. The perceived influence of prot´eg´es in the organization is likely to be related to the extent to which the prot´eg´es build links across demographic boundaries. Thus, helping a man build links to the network of women or a woman build links to the network of men within an organization can enhance the prot´eg´e’s leadership potential measured in terms of perceived power (Brass, 1985). Such sponsorship is likely to be especially important in the case of members of underrepresented groups whose own attempts at brokerage across social divides may rebound to hurt rather than help their careers, according to research in one firm (Burt, 1992). Members of underrepresented groups tend to form homophilous networks among themselves and may also experience discrimination from majority group members (Mehra et al., 1998). The mentoring of underrepresented group subordinates involves facilitating the development of the subordinates’ own networks that may expand in directions not covered by the leader’s own connections (cf. Higgins and Kram, 2001). Research suggests that such

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mentoring relationships can be successful even when the sponsor and the prot´eg´e are from different ethnic groups (Thomas, 1993). Network leadership, then, can be measured in terms of how much social capital it creates for others, especially those members of underrepresented groups whose social network ties may be restricted because of in-group pressures toward homophily and out-group bias (Chapter 6). A particularly important test of network leadership occurs in the case of isolates. G. K. Chesterton wrote, “There are no words to express the abyss between isolation and having one ally.” Members of work teams who consistently fail to communicate with their colleagues may represent wasted resources in today’s coordinated organizations whether or not they suffer the “abyss” of isolation. Research in three high-technology military organizations showed that isolates, relative to “participants,” tended to rely more on written and telephone communication, to withhold information, to express less commitment to the organization, to experience lower satisfaction with both communication and with their jobs, and to be rated as lower performers (Roberts and O’Reilly, 1979). Clearly, such isolated individuals represent a networking challenge. The extent to which such isolates are part of work groups may predict the extent of leader effectiveness in such groups. A related issue concerns the extent to which workgroups exhibit disconnects between subgroups. Although recent work suggests that too few or too many structural holes in a team may adversely affect communication (Oh, Chung, and Labianca, 2004) and team effectiveness, the question of how such structural holes affect team performance and functioning remains unanswered (Balkundi, Kilduff, Barsness, and Michael, 2007). Positive Emotion Isolates and structural holes in groups tend to signal the existence of emotional distress. Research attention has started to focus on the role of formal leaders in the emotion management network in organizations (Chapter 8). Vertical dyad linkage theory alerted researchers to the benefits – emotional and vocational – associated with membership in the leader’s in-group (see Dansereau, 1995, for a review). Building on this legacy, the positive psychology movement suggests that leaders have responsibility for maintaining the emotional health of all employees (Frost, 2003) rather than just those with privileged access to the leader. Yet, some people in formal leadership roles fail to attend to the toxic emotions created in organizational contexts and thereby fail to perform as effective leaders (Maitlis and Ozcelik, 2004). The question of the management of affective bonds and emotional health has been neglected in the leadership and in the network literatures and begs for more attention.

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The Interorganizational Network: Boundary Spanning and Alliances Leaders, both formal and informal, can potentially network within their organizational units and outside their units. As representatives of their organizational units, leaders forge interorganizational links that may or may not lead to or coincide with formally contracted relationships. Beneath most formal alliance ties between organizations “lies a sea of informal ties” (Powell et al., 1996: 120). Interpersonal friendships and other strong links such as kinship between CEOs can lead to business alliances, just as business alliances can lead to warmth and trust between representatives of different organizations (Larson, 1992; Uzzi, 1997). One dramatic case study, referred to earlier in this chapter, highlighted the danger of two individuals dividing the networking task between them into its internal and external components (Auletta, 1986). Lehman Brothers was a venerable Wall Street investment banking firm in which partner Louis Glucksman operated as the inside networker, maintaining cohesion and rapport with the company’s traders, whereas partner Pete Petersen operated as the outside networker, responsible for bringing in new business from the rich and famous. When both partners were appointed as joint CEOs, the ensuing battle for supremacy led to a financial crisis and a takeover by American Express, bringing to an inglorious end one chapter in the saga of a proud and independent institution. In the furious battle for control between the inside and outside networkers, Glucksman had the upper hand, having developed social capital within the organization among the partners who controlled the firm through their votes. As this example illustrates, managing the boundary between inside and outside networking is a crucial task for formal leaders. The formal leader can be considered a boundary spanner who manages not only an internal constituency within the organization but who also represents the organization in the community of organizations. Network links between organizations tend to build from within the existing network. Organizational leaders create stable relationships with trusted partners, and, over time, these stable ties accumulate into a network that provides to members of the network information about future alliance partners (Gulati and Gargiulo, 1999). Organizational leaders, for example, tend to recommend to one trusted partner the formation of a business relationship with another trusted partner, thus creating a three-member clique (Larson, 1992; Uzzi, 1996). With knowledge increasingly emerging from the interstices between hierarchical boundaries (Powell et al., 1996), leaders who pursue policies of splendid isolation are likely to see their organizations suffer “the liability of unconnectedness” (Baum and Oliver, 1992) in failing to capture intellectual developments as they arise and expand.

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An innovative organization such as Digital Equipment Company, once famed for its fortress-like culture and its devotion to in-house technical development (Kunda, 1993), is likely to fade away in a knowledge economy in which innovations are increasingly the product of industrial clusters rather than individual companies (Saxenian, 1990). Given the inertia of organizations relative to the speed of change in many environments (Hannan and Freeman, 1984), even large and apparently dominant organizations in knowledge-intensive industries need to build connections with a range of other organizations to access developing technology. However, leadership effectiveness in this knowledge economy may depend not just on the direct network links to other organizations under the leader’s control, but also on the links beyond the leader’s control. As we noted with respect to networking within the organization, it is often the links beyond the immediate social circle of the leader that affect many desired outcomes. Research suggests that the survival of the organization itself may be affected by the secondary links to organizations beyond the leader’s immediate control. For example, in the New York garment industry, CEOs who developed strong personal relationships with the heads of “jobbing” firms (that distribute work orders) increased the survival chances of their firms if they were able to access through these strong connections networks of balanced relationships. It was not just the primary ties to the jobbing firms that were important for the focal firms. Survival was enhanced for the firms of those CEOs strongly connected through a primary tie to a set of secondary ties that include a balanced mix of arm’s-length and close ties with a jobbing firm (Uzzi, 1997). Although the CEO may have some control over whether to develop close, personal ties or more market-based exchanges with heads of jobbing firms, the CEO may not even be aware of the types of business relationships that jobbers have with other firms. Thus, leadership effectiveness (and the survival of the organization) may depend on second-order network links beyond the control of the CEO. What of the leader’s centrality in the community of organizational leaders? Research shows that organizational leaders tend to interact with each other across a range of social events, with representatives of elite organizations tending to form their own elite social circles (Galaskiewicz, 1985; Kilduff and Tsai, 2003: 22). However, centrality in this community of leaders may distract leaders from the strategic management of their own organizations. One study of an ethnic community of Korean expatriate entrepreneurs showed that the extent to which organizational owners were central (in terms of spanning across divided social groups within the community) correlated negatively with performance and predicted organizational demise (Oh et al., 2005). Of compelling interest, however, is the extent to which the leader’s ties to organizational leaders

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outside the immediate community affect the flow of important resources and, thereby, organizational survival. It may be in the interorganizational arena that new network methods focused on social network dynamics emerge, given the strong interest in understanding the evolution of strategic alliances (e.g., Gulati and Gargiulo, 1999). Conventional wisdom suggests that networks tend to be relatively stable, but this apparent stability can mask many types of change that can be captured in network “movies” showing the dance of interactions over time (Moody, McFarland, and Bender-DeMoll, 2005).

Conclusion Leadership requires the management of social relationships. Starting with the cognitions in the mind of the leader concerning the patterns of relationships in the ego network, the organizational network, and the interorganizational network, social ties are formed and maintained, initiatives are launched or avoided, and through these actions and interactions, the work of the leader is accomplished. Building on the idea that networks are both cognitive structures in the minds of individuals and actual structures of relationships that link individuals, this chapter views organizational networks as constructed and maintained by boundedly rational actors, subject to biases in their perceptions. Leadership research from a network perspective has the opportunity to forge a new understanding of the interplay between the psychology of individuals and the complexity of the networks through which actors exchange information, affect, and other resources. Leadership research also has the opportunity to renew our understanding of how patterns of informal leadership complement or detract from the work of formally appointed leaders. If leaders rely solely on their formally assigned authority and bring into their leadership circles likeminded others, they may isolate themselves from new ideas (as represented by, for example, the slow learners investigated by March, 1991). Further, the influence of visible leaders, both informal and formal, is likely to be affected by network ties that may not show up at all in the organizational chart. The members of governing coalitions, for example, are likely to be tied to powerful individuals temporarily removed from positions of authority and deal makers who operate quietly to influence organizational outcomes. Only recently has research attention focused on these virtual actors whose “ghost” ties constrain network change and action (see, for example, Moody et al., 2005). The network approach articulated in this chapter emphasizes the extent to which individuals’ thoughts and actions are embedded in their

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perceptions of networks, in the immediate ego networks that surround them, in the organizational networks within which their ego networks are embedded, and in the interorganizational networks that connect them to leaders of other organizations. Leaders, we have emphasized, generate and use social capital through the acuity with which they perceive social structures and the actions that they take to build connections with important constituencies within and across social divides. To understand leadership effectiveness from a social network perspective is to study the individual’s position in the larger networks within which the individual is located. The network approach, therefore, allows a more macro focus on the full repertoire of network relationships than has been the case in previous leadership research. The network approach also incorporates actors within the network who may or may not be connected with the leader, but whose actions, in creating new ties, for example, can affect leader outcomes by changing the structures within which the leader operates. Clearly, the network perspective – in its emphasis on social relations, embeddedness, social capital, and social structure – both incorporates strands emphasized within previous leadership research and points in new directions. This chapter has emphasized the importance of individuals’ perceptions of network relations, and this theme is continued in the following three chapters. In the next chapter, we investigate the extent to which individuals who are perceived to have prominent friends gain advantages in terms of performance reputation in organizations.

3 An Analysis of the Internal Market for Reputation in Organizations

The basic idea we investigate in this chapter is whether the relative importance, reputation, and value of any particular individual in an organization (in the eyes of others) are affected by the company the individual is perceived to keep. The assessment of reputation, we suggest, is likely to be enhanced if the individual is perceived to have a high-status friend. Becoming the friend of a high-status person is not easy, and those who are fortunate to enjoy such access are likely to gain considerable social capital. High-status people are carefully scrutinized to see who their associates are. This is not a new insight. Shakespeare’s Falstaff, an intimate acquaintance of Crown Prince Harry in the Henry IV plays, is depicted as reveling in reflected glory. Certainly, the Baron de Rothschild (according to the anecdote in Chapter 1) was in no doubt concerning the value his apparent friendship would confer in terms of tangible financial capital becoming available from those impressed with his public social endorsement of the person with whom he walked “arm-in-arm.”

How Perceptions Affect Reputation The theoretical framework within which we investigated the determinants of reputation in organizational labor markets was balance theory (Heider, 1958). From this perspective, someone perceived to be the friend of a positively valued other is also likely to be perceived positively: There is a strain toward cognitive balance in the perceptions of observers. We argue that the performance reputations of people with prominent friends will tend to benefit from the public perception that they are linked to those friends. This basking-in-reflected-glory effect has been hypothesized to involve a deliberate strategy on the part of individuals to garner positive 39

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evaluations from those who perceive their ties to prominent others: “It is our contention that people make known their noninstrumental connections with positive sources because they understand that observers to these connections tend to evaluate connected objects similarly” (Cialdini et al., 1976: 374). Previous researchers have not investigated the basking-in-reflected-glory effect in a performance context, despite the phenonemon’s apparent relevance to such issues as performance rating. Building from this psychological base in balance theory, we propose to extend the study of the basking phenomenon to all the actors in a social system. The structural approach to social networks suggests looking at performance reputations in terms of the structure of relations in an entire organization. Structuralists are familiar with the use of the metaphor of the market to describe any competitive situation in which people jockey for valuable outcomes, such as a reputation as a good performer (cf. White, 1970). In looking at an organization as a market for reputation, one’s focus is implicitly on the process of exchange. The higher an individual’s reputation, the more valuable he or she becomes in the internal labor market. In looking for signals of quality (Spence, 1973), people ask: Does the person hold a high position in the organization? Is the person a friend of a prominent leader? In this cognitive assessment process, both individual attributes and social ties may contribute to the determination of performance reputation. To recapitulate, we are predicting that an observer’s perception of an individual’s performance will be significantly influenced by the degree to which the observer perceives that individual to have a prominent friend. The basis for this prediction at the psychological level is the strain toward cognitive balance in the mind of observers. Within the internal labor market of an organization, people are assumed to be jockeying to increase their reputations as high performers by publicizing links to prominent others. This assumption is supported by research on basking in reflected glory (see Cialdini [1989] for a review) showing that people actively seek to enhance their public images by proclaiming bonds to successful others: “It is as if strains toward cognitive balance are at some level of consciousness understood to exist by observers and action is taken to exploit the consequences of the balance process” (Cialdini and Richardson, 1980: 414). We assume that each individual is especially active in drawing attention to his or her most prominent friend because this friend offers the individual the most opportunity for basking in reflected glory. Organization members may also be alerting others to such relevant factors as their position in the organizational hierarchy and their organizational accomplishments. Further, members of the internal labor market are assumed to be searching for signals of the underlying performance quality of colleagues

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and competitors (cf. Spence, 1973) in an ongoing social comparison process (cf. Festinger, 1954). Formally stated, our first hypothesis is: Hypothesis 1: The prominence of an individual’s most prominent friend will influence the individual’s performance reputation in an organization, controlling for the individual’s formal status and job performance. However, this proposition can be further refined in accordance with balance theory to distinguish between perceived and actual friendship links. From a balance theory perspective (Heider, 1958), it is an individual’s perception of social relations, rather than the actual structure of social relations, that affects individual attitudes. What matters are the friends a person is perceived to have, not actual friendships. Balance theory suggests, therefore, that mental representations of patterns of relations will be more important determinants of attitudes than the actual patterns of relations within which individuals are located. From this perspective, perceptual measures of network relations should be more predictive of attitudes than objective measures. Social network links can be derived either from each observer’s cognitive map of how he or she perceives the connections between organizational actors or from an aggregate map built up from the agreement of each party to each link. We follow Weick and Bougon (1986: 105– 6) in using the term “cognitive map” to refer to an individual’s mental representation of relations within a system of connections. An individual’s cognitive map of a friendship network, for example, consists of the individual’s picture of who is friends with whom in a particular social system. Individuals are assumed to use these maps to negotiate their journeys through their social worlds. An alternative to deriving a separate set of network links from each observer’s cognitive map is to use a map of the actual network assembled in a conventional structural fashion from the agreement of each party to each link. The network map in this case is not idiosyncratic to any one individual. The aggregate network map represents reality because it is compiled from the observations of all relevant observers rather than from the observations of just one observer (Krackhardt, 1987a). Hypothesis 2: Measures of perceived network relations will lead to better predictions of performance reputation than will measures of actual network relations.

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Methods Silicon Systems (a pseudonym), the organization selected as the research site, was a small entrepreneurial firm located on the west coast of the United States in an area known for its many small startup companies. Silicon Systems specialized in the sale, installation, and maintenance of stateof-the-art information systems for clients such as local banks, schools, manufacturing firms, and research and development (R&D) labs. Not long before this research began, giant competitors, such as the International Business Machines Corporation (IBM) and the American Telephone and Telegraph Company (AT&T), had begun to focus attention on Silicon Systems’ market because of its perceived growth potential. According to the top managers of Silicon Systems, the small firm’s competitive edge remained its ability to respond more efficiently than its giant competitors to idiosyncratic customer demands. Silicon Systems was wholly owned by its three top managers, each of whom owned an equal share. All employees worked in the company’s single-floored building. The employees saw each other regularly and were familiar with each others’ work practices. The firm had grown from three to thirty-six people in fifteen years, with much of the growth occurring in the five years prior to this study. During those years, the firm had been generally profitable, and the owners anticipated no downward trend in their business. Of the thirty-six people in the company (twenty-eight men and eight women), thirty-three people, or 92 percent, accepted $3 each from us to complete a lengthy questionnaire. We described the research as a study of the effects of networks in organizations. All respondents were promised and given individual reports showing their cognitive maps of the networks and how those perceived networks compared to the actual networks. Measures Networks Network Indexes: Friendship and Advice Networks To capture respondents’ cognitive maps of the friendship and advice relations in this organization, we asked each person about his or her perceptions concerning every other person’s network links. For friendship, each person responded to the following question about every other person in the organization: “Who would this person consider to be a personal friend? Please place a check next to all the names of those people who that person would consider to be a friend of theirs.” For advice relations, the corresponding question was: “Who would this person go to for help or advice at work?” Thus, for the friendship network, John Meredith was asked a series of thirty-six questions of the form: “Who would Jane Asch

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Jim

Pat

Ev Irv

Fred

Zoe

Upton

Steve

Ivo

Chris

Figure 3.1. An employee’s cognitive map of the friendship relations at Silicon Systems.

consider to be a personal friend?” “Who would Jerry Bonavue consider to be a personal friend?” Each question was followed by the list of thirtyfive employees’ names. Meredith then checked the names that indicated, for example, his perceptions concerning who Asch considered to be her personal friends. Each respondent, then, gave us a complete cognitive map of his or her perceptions concerning who was friends with whom in the organization. To measure perceived friendship links, we used the following procedure: A friendship tie as perceived by person k existed between person i and person j only if k responded on the questionnaire that i considered j a friend. To measure actual friendship links, we determined the locally aggregated structure, or LAS (Krackhardt, 1987a) as follows: A friendship tie existed between persons i and j only if person i claimed person j as a friend and person j agreed that person i claimed person j as a friend. Thus, a friendship link from i to j was defined as existing when both parties agreed that it existed. Figure 3.1 presents an example of a respondent’s cognitive map of the friendship network. The striking aspect of this particular map is the relatively low number of connections that this individual perceived. Comparing this individual’s cognitive map with the actual structure of friendship

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relations that emerged from the reports of all respondents (see Figure 3.2) shows that perceptions concerning friendship links can be considerably discrepant from actuality (Krackhardt, 1990). In this case, the discrepancy is the result of the individual not perceiving many friendship links that actually existed. In other cases, the discrepancy occurs because an individual perceives friendship relations where none exist. To measure a perceived advice link, we followed the following procedure: A person was considered to go to another person for advice if the respondent’s cognitive map showed that person as going to the other for advice. That is, for respondent k, a perceived advice link existed between persons i and j only if respondent k perceived that person i went to person j for advice. To measure an actual advice link, we did this: A person was considered to go to another for advice only if that person claimed that he or she went to the other for advice. That is, person i was considered to actually go to j for advice only if i’s cognitive map showed i going to j for advice. This definition of an actual advice link is known as the row-dominated locally aggregated structure (Krackhardt, 1987a) and follows the standard procedure in network analysis in that it relies on the self-report of the individual concerned. This measurement preserves the asymmetry inherent in the relation, an asymmetry that is critical to our prominence argument, as discussed in the following subsection. Independent Variable: Friend’s Prominence Matrix We hypothesized that each person’s performance reputation would be influenced by the extent to which each person had a prominent friend in the organization. We chose to focus on each person’s most prominent friend rather than on an average of all friends’ prominence ratings because of the theoretical basis of the research. An average measure would not capture an individual’s ability to bask in reflected glory. With an average measure, two individuals might have the same friends’ prominence score even though one person had no prominent friends whereas the other had both highly prominent and highly obscure friends. We measured each friend’s prominence in four different ways and obtained four separate matrixes. Table 3.1 summarizes the differences among these four measurements. To contrast the predictive validity of the perceived and externalized structures, we measured prominence using both perceived and actual network links. To check for common method variance, we measured prominence both from questionnaire responses, as indegree centrality in the advice network – that is, the total number of others who went to the friend for advice (Scott, 1991: 72) – and from the organization chart, as formal status in the organizational hierarchy. The four measures of friend’s prominence were, therefore, (1) the indegree

45

Ovi

Bob

Nan

Wal

Vic

Gar

Hug

Chr

Rob

Ken

Ivo

Mel

Dal

Tom

Ric

Figure 3.2. The actual structure of friendship relations at Silicon Systems.

Ben

Jac

Ale

Ger

Jim

Dan

Ev

Upi

Pat

Zoe

Irv

Ste

Len

Fre

Car

Ear

Abe

Hal

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Table 3.1. Summary of Research Variables Variable Dependent Performance reputation matrix Independent Perceived friend’s indegree centrality matrix Actual friend’s indegree centrality matrix Perceived friend’s formal status matrix Actual friend’s formal status matrix Control Job performance matrix Formal status matrix

Definition of Each Cell in Matrix Respondent i’s perception of the job performance of person j, rated on a seven-point scale, for all js not supervised by i Advice indegree centrality of person j’s most central friend, based on friendship and advice networks perceived by i Advice indegree centrality of person j’s most central friend, based on aggregate (LAS) friendship and advice networks Level in organizational hierarchy occupied by person j’s highest-level friend, based on friendship network perceived by i Level in organizational hierarchy occupied by j’s highest-level friend, based on aggregate (LAS) friendship network Supervisor’s evaluation of the job performance of person j on a seven-point scale Level in the organizational hierarchy occupied by person j

centrality of the perceived friend, (2) the indegree centrality of the actual friend, (3) the formal status of the perceived friend, and (4) the formal status of the actual friend. The indegree centrality measure of prominence was derived from the advice network of relations. In social network research, “Prominent leaders are the objects of extensive relations from followers, while the latter are the objects of few relations” (Knoke and Burt, 1983: 199). To capture this kind of prominence, therefore, an asymmetric measure was needed, one that counted nonreciprocated ties. Further, our theoretical assumption was that individuals publicize the existence of friendship links to prominent others and that perceivers scan an organization for clues as to who the prominent actors are. We needed, then, a measure of visible prominence, one that emphasized direct ties rather than indirect ties. We wanted to capture the kind of prominence represented by someone whose desk is often surrounded by people seeking help and advice rather than the kind of prominence represented by someone with relatively invisible influence based on indirect links. Because of our concern with asymmetry and visibility, we chose to measure informal prominence in terms of indegree centrality in the advice network, which refers to the extent to which others seek help or advice about work-related matters from a focal person. Technically, indegree centrality can be defined as the number of

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other people who go to an actor for advice (Freeman, 1979). Indegree centrality has been widely used in organizational research when direct, asymmetric ties are being measured (e.g., Burkhardt and Brass, 1990), although measures that include indirect ties may be more appropriate in other situations (cf. Ibarra, 1992, 1993b). In the current research, we measured indegree centrality for both the perceived and actual networks. For the perceived measure, we looked at each respondent’s cognitive map of perceived relations. Within each cognitive map, we identified, for each person, the friend with the highest indegree centrality rating. This rating was then recorded as the first measurement of the independent variable. The second measurement of the independent variable – the actual friend’s indegree centrality – was based on the actual friendship and advice networks aggregated from the responses of all respondents. As described previously, the existence of a friendship link in the actual network meant that the two people involved both agreed that the friendship link existed. Similarly, the existence of an advice link from, for example, John to Bill meant that John had indicated on his questionnaire that he went to Bill for advice. For each person, therefore, we identified the actual friend with the highest indegree centrality rating and recorded that value. The third and fourth measurements of the independent variable were based on the friend’s formal status rather than on the friend’s indegree centrality. Because of potential common method variance, it was necessary to demonstrate that the critical variables in the study were not correlated simply because they were derived from the same source. The obvious remedy for common method variance is to use different sources for the independent and dependent variables, if doing so is consistent with the conceptual framework of a study (Sackett and Larson, 1990: 474). Following this strategy, we derived prominence ratings from the organizational chart recorded in company records. In many organizations, those higher up in the hierarchy are also more prominent because many others go to them for help and advice about work-related matters. Formal status has been shown to be predictive of organizational power (Brass and Burkhardt, 1993; Krackhardt, 1990) and to correlate highly with network centrality (Ibarra, 1992; Krackhardt, 1990). Formal status, then, provides an alternative to perceived measures of prominence in organizations. We were therefore able to test our hypotheses with the independent variable ratings derived from company records and our dependent variable ratings derived from questionnaire responses. In this way, we avoided the problem of common method variance. Also, we were able to assess the convergent validity of the independent variable by seeing whether

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different definitions of the same variable produced the same results (cf. Campbell and Fiske, 1959). At Silicon Systems, there were three levels of formal authority. The three owner-managers occupied the top level. Even though each ownermanager had different responsibilities and titles, all three were equal partners, and they made all major company decisions as a team. The next level consisted of five managers, each of whom had supervisory responsibility over certain operational features in the organization. The remaining twenty-eight employees had no formal supervisory titles or authority. Formal status, then, was rated as follows: We gave each of the three owners a status rating of 3, each of the five managers a rating of 2, and each of the remaining twenty-eight employees a rating of 1. We assigned formal status to both perceived friends and actual friends. For the perceived measure, we looked at each respondent’s cognitive map of perceived relations. Within each cognitive map, we identified, for each person, the friend with the highest formal status. This status rating was recorded as the third measurement of the independent variable. The measure of the actual friend’s formal status was based on the real friendship network aggregated from the responses of all respondents. For each person, we identified the friend with the highest status rating and recorded the rating as the fourth measurement of the independent variable. In summary, we measured each friend’s prominence in four ways, pitting perceived and actual network measures against each other and pitting a network measure of prominence against an organizational chart measure of prominence. For each of the four measures, we created a 36-by-36 matrix, with cell entries representing the prominence ratings of friends. For example, for the matrix of perceived friends’ indegree centrality ratings, a “9” in a cell formed by the intersection of row 12 and column 25 meant that, among all the friendships that person 12 perceived person 25 to be involved in, 9 was the highest indegree centrality rating that any of person 25’s friends achieved. Dependent Variable: Performance Reputation Matrix Each respondent provided his or her perception of the job performance of every person in the organization by circling numbers on a seven-point scale next to people’s names. We collected these performance reputation ratings in a 36-by-36 matrix. Each row in the dependent variable matrix represented the impressions in the mind of one respondent concerning the performance of those others not actually under the respondent’s supervision. Similarly, each column in the matrix represented the impressions of one individual held by all those respondents not actually supervising that

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individual. The performance reputation matrix contained the actual raw ratings that the respondents provided. Social network analysts typically retain raw ratings in matrix form rather than seeking to perform analyses on average scores (see Kilduff and Tsai, 2003, for an introduction to social network analysis). We elicited the raw ratings with the following instructions: “If you think the person is performing their job extremely well, you might circle the ‘7’ next to their name. If you think the person is performing their job reasonably well, you might circle the ‘4’ next to their name. If you think they are not performing their job at all well, you might circle the ‘1’ next to their name.” Each cell in the performance reputation matrix contained the rating provided by one respondent concerning one other person. For example, if person 12 rated person 25 as performing extremely well on the job, then a “7” would appear in the cell formed by the intersection of row 12 and column 25. Our reliance on a one-item measure of performance increases the possibility of random error and makes significant results harder to find. Our tests, therefore, are likely to be conservative assessments of the hypothesized basking-in-reflected-glory effect. First Control Variable: Job Performance Matrix Supervisors’ ratings of subordinates’ performance were excluded from the dependent variable matrix previously described because these supervisory ratings constituted the measurement of job performance. Supervisors therefore used the same seven-point scale that was used for the performance reputation measure. The job performance of people in organizations is typically difficult to ascertain, especially for work with many different aspects. However, one conventional measure of job performance in many companies is the supervisory rating: “The vast majority of performance ratings come directly from the immediate manager” (Bretz, Milkovich, and Read, 1992: 331). Previous research has shown that performance ratings obtained for research purposes are more reliable and valid than those obtained for administrative purposes (Wherry and Bartlett, 1982), perhaps because issues other than ratee performance bias official performance ratings (Longenecker, Sims, and Gioia, 1987; Tsui and O’Reilly, 1989: 410). The reporting relations between supervisors and subordinates were obtained from company records. The three owners of the company in the present research had nobody above them in the organizational chart to provide a supervisory rating. For each owner, therefore, we used the mean rating given by the other two owners as the supervisory rating. The owners’ ratings of each other did not differ in any case by more than two points on the seven-point scale.

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The supervisory ratings were collected in a column vector thirty-six cells long containing values from 1 through 7, indicating the job performance of each person in the company. Thus, each cell (i,j) in this matrix contained j’s supervisor’s rating of j’s performance. The vector was repeated thirty-six times to create a matrix of the same size (36 by 36) as the other matrixes in the analyses. Second Control Variable: Formal Status Matrix This variable controlled for the effects of formal status on the performance reputation of each focal person. In this small, organic organization, there was little apparent status differentiation based on educational differences or functional specialization. From our visits to the company, we concluded that the major status difference was between those who owned the company and those who only worked for it. Therefore, we defined formal status as the level in the organizational hierarchy that each person occupied (3 = owner-manager, 2 = manager, and 1 = nonmanager). The formal status scores were collected in a column vector thirty-six cells long containing the numbers 1 through 3. Thus, each cell (i,j) in this matrix contained j’s formal status. The vector was repeated thirty-six times to create a matrix of the same size (36 by 36) as the other matrixes in the analysis.

Analysis Social network data are often not amenable to standard statistical tests because the observations cannot be assumed to be independent. For example, in the current research, the matrix of friend’s indegree centrality ratings includes thirty-six ratings from each person in the study. Each of the thirty-six ratings within a row of this matrix derives from the same source – the cognitive map of the respondent – and therefore exhibits systematic interdependence. Indeed, in some of the matrices, the cell values are repeated across rows. Krackhardt (1988) showed that such row or column interdependence can bias ordinary-least-squares (OLS) tests of significance. The size of this bias is substantial: Results based on samples drawn from a population for which the null hypothesis is true (that is, there is no relationship between the independent and dependent variables) have a 70 percent chance of appearing significant under standard parametric methods. To deal with this problem of bias, we used the Multiple Regression Quadratic Assignment Procedure (MRQAP) suggested by Krackhardt (1993). The procedure builds on earlier bivariate work done by Hubert and others (Baker and Hubert, 1981; Hubert, 1987; Hubert and Schultz, 1976) and extended to the multiple regression case by Krackhardt (1987b,

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1988). (Note that the use of MRQAP in this book generally avoids the serious problems outlined by Dekker, Krackhardt, and Snijders, forthcoming, concerning the dependent variable permutations often used in social network research.) The method is straightforward. First, OLS estimates of regression coefficients are calculated in the usual manner. Then the rows and columns of the dependent variable matrix are permuted to give a new, mixed up matrix. The OLS regression calculation is then repeated with the new dependent variable. This new regression produces different beta coefficients and overall R2 values that are stored away. Another permutation of the dependent variable is then drawn, another regression is performed, and these new values are also stored. This permutation-regression process is repeated an arbitrarily large number of times (in our case, one thousand). The distribution of the stored betas and R2 s for each of the independent variables under the set of permuted regressions becomes the reference distribution against which the observed original values are compared. If fewer than 5 percent of the betas derived from the permuted regressions are larger than the observed beta, the beta is considered significant at the .05 level (one-tailed test). If fewer than 1 percent of the betas are larger than the observed beta, it is considered significant at the .01 level. The advantage of this simple procedure is that it is robust against varying and unknowable amounts of row and column autocorrelation in the dyadic data. That is, if a sample is drawn from an autocorrelated population in which the null hypothesis is true, the probability that the results will appear significant by this MRQAP test is .05 (where alpha equals .05). This remarkable feature of the MRQAP occurs because the test is a conditional nonparametric test. That is, each permutation of the dependent variable retains the structure of the original dyadic data and therefore preserves all the autocorrelation in each permuted regression; the test is conditioned on the degree of autocorrelation that exists in the data. The permutation version of MRQAP (Krackhardt, 1993) differs from the earlier analytic version (Krackhardt, 1988). The analytic solution to the multiple regression problem was based on Mantel’s formula (Mantel, 1967) for the first two moments of the distribution of all permutations. The current version has several demonstrated advantages. First, it permits an unbiased test of the overall R2 . Second, it is relatively powerful in the face of missing data. Finally, whereas the analytic test necessarily contains the assumption that the reference distribution of betas based on the permutations is normally distributed, the permutation-based sampling procedure used here does not have such a requirement. Permutation MRQAP is now available in user-friendly form in the UCINET social network analysis package (Borgatti et al., 2002).

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Table 3.2. Means, Standard Deviations, and Correlationsa Variables

Means

s.d.

1. Performance reputation 2. Friend’s prominence a. Perceived friend’s indegree centrality b. Actual friend’s indegree centrality c. Perceived friend’s status d. Actual friend’s status 3. Job performance 4. Formal status

4.93

1.39

6.70 7.87 1.46 1.55 4.91 1.31

8.86 7.00 0.73 0.83 1.15 0.62

a ∗

1

2a

2b

2c

2d

3

.23 .26 .28 .28 .33 .30

.22 .68 .15∗ .14∗ .17

.30 .83 .31∗ .54

.30 .28 .38

.49 .65

.47

All correlations are significant at p < .01, except for those with an asterisk. p < .05

One of the advantages of the permutation version of MRQAP is that it can handle missing values with much more statistical efficiency than the prior version. In the current research, several of the variables had values missing, either because there were three nonrespondents or because we assigned cells in a matrix missing value status when defining the variable. For example, in the case of the dependent variable, performance reputation was only considered in (i,j) pairs in which i was not j’s direct supervisor, and a missing value was inserted when i was the direct supervisor of j.

Results The descriptive statistics shown in Table 3.2 indicate a reasonably high level of performance at Silicon Systems, with both performance reputation and actual performance averaging around 4.9 on a seven-point scale. The zero-order correlations in Table 3.2 show that the two measures of perceived friend’s prominence – perceived friend’s indegree centrality and perceived friend’s formal status – were highly correlated (r = .68, p < .01), as were the two measures of actual friend’s prominence (r = .83, p < .01). Further, these correlations suggest that the actual friends of high-status individuals tended to also be of high status (r = .65, p < .01) and indegree centrality (r = .54, p < .01). Table 3.2 also shows that the dependent variable, performance reputation, was significantly correlated (at p < .01) with all four measurements of the independent variable (friend’s prominence), as well as with both control variables (job performance and formal status). To answer the question of whether these significant correlations would remain significant when other variables were controlled for, we conducted a multiple regression analysis.

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Table 3.3. Results of Multiple Regression Analysisa Status Models Variables Friend’s prominence Perceived friend’s indegree centrality Actual friend’s indegree centrality Perceived friend’s status Actual friend’s status Job performance Formal status Intercept R2

1

2

3

Centrality Models 4

5

6

7

.028∗∗

.026∗∗

.024 .319∗∗ .296∗∗ .407 2.93∗∗ .136

.109 .277∗ .326 2.96∗∗ .139

.273∗ .281 2.74∗∗ .161

.315∗∗ .090 .258∗ .217 2.76∗∗ .162

.286∗ .263 2.99∗∗ .146

.018

.284∗ .350 2.88∗∗ .166

.277∗ .245 2.92∗∗ .171

a

Beta coefficients are unstandardized. Their significance was determined by MRQAP (Krackhardt, 1993). p < .05, one-tailed test. ∗∗ p < .01, one-tailed test. ∗

Results of the first model, shown in Table 3.3, suggest that high performance on the job in this organization helped people achieve reputations as high performers (p < .01) but that formal status did not significantly affect performance reputations. The two control variables explained 14 percent of the variance in performance reputation. The question of interest, then, is whether the measures of the independent variable significantly increased explained variance above that already explained by the control variables. Did the existence of a friendship link to a prominent person boost individuals’ performance reputations in this organization, as hypothesis 1 predicts? Table 3.3 shows that friendship with prominent others did boost individuals’ performance reputations, but this effect depended on how the friendship links were assessed. Recall that hypothesis 2 predicts that perceived friendship links will lead to better predictions of performance reputation than actual links. The results shown in Table 3.3 support this prediction. Models 2, 3, and 4 in Table 3.3 employed two different definitions of the status of the highest-status friend to measure the independent variable. Model 2 shows that entering the status of the actual friend into the regression equation together with the control variables resulted in no significant increase in the variance explained. Model 3 shows that the introduction of the status of the perceived friend did increase explained variance significantly (p < .01), from 14 to 16 percent. Entering both measurements of friend’s status simultaneously (model 4) confirmed that only

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the perceived measure had a significant effect on performance reputation (p < .01). In support of hypothesis 2, then, these models show that, with individuals’ job performance and organizational status controlled, only the perceived measure of friend’s status had an effect on individuals’ performance reputations. Being perceived to have a friend at a high level in the organization helped boost an individual’s reputation as a high performer, whereas actually having such a friend had no significant effect on performance reputation. Models 5, 6, and 7 in Table 3.3 repeat the analyses already performed in models 2, 3, and 4, with a measure of the friend’s indegree centrality in the informal advice network substituting for a measure of the friend’s formal status. The results for models 5, 6, and 7 repeat the pattern seen in models 2, 3, and 4, indicating that the results favoring perceived friendship over actual friendship were not artifacts of the way that prominence was measured. Model 5 shows that entering the indegree centrality of the actual friend in the regression equation did not significantly increase explained variance. Model 6 indicates that the introduction of the indegree centrality of the perceived friend did increase explained variance significantly (p < .01), from 14 to 17 percent. Finally, model 7 confirms that when both the actual and the perceived measures of friend’s indegree centrality were entered together, only the perceived measure had a significant effect on performance reputation (p < .01). Paralleling the results from the status models, the results from the centrality models show that, with individuals’ job performance and organizational status controlled, only the perceived measure of friend’s indegree centrality had an effect on individuals’ performance reputations. In other words, being perceived to have a friend to whom many others go for help and advice helped boost an individual’s reputation as a high performer, whereas actually having such a friend had no significant effect on performance reputation. In summary, Table 3.3 shows that the status models (2, 3, and 4) and the centrality models (5, 6, and 7) are similar both in terms of the superiority of perceived measures of friend’s prominence over actual measures and in terms of the variance explained by each set of models. These consistent results support the convergent validity of our measures of perceived and actual prominence. The results show that it doesn’t matter whether the prominence ratings derive from the friend’s position in the organizational hierarchy or from questionnaire items concerning who goes to whom for advice at work. The robustness of the results across measures derived from two different sources supports the conclusion that the significant correlations are not artifacts of common method variance.

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One other concern, however, is that the effect of actual prominence might have been suppressed as a result of the correlational structure of the data. Table 3.2 shows that, relative to measures of perceived prominence, measures of actual prominence were more highly correlated with the control variable (job performance) that contributed significantly to explained variance in all the models of Table 3.3. To check whether the high correlations between measures of actual prominence and the control variable distorted the results, we conducted the analyses again without controlling for job performance and found the same pattern of results (albeit with less explained variance): Only the perceived measures of friend’s prominence significantly predicted performance reputation. The measures of actual friend’s prominence continued to be nonsignificant in all models.

Discussion In support of the hypothesized basking-in-reflected-glory effect, the results show that performance reputation is partly a function of an individual’s job performance and partly a function of the individual having a prominent friend. Perhaps the most intriguing aspect of the results is the finding that the actual existence of friendship links, recognized by both parties to the links, had no significant effect on performance reputation. Rather, it was the perceptions in the minds of organization members that mattered. To explain outcomes such as performance reputation in organizations, it may be necessary to explore the perceived networks that influence the attitudes of organization members. Structure, as it exists in the minds of individuals, may be more predictive of important outcomes than has been recognized. Bringing the individual back into structural analysis, therefore, may enhance rather than detract from the effectiveness of a structural approach. The results, then, support the utility of combining variables derived from individuals’ cognitive maps with more conventional structural variables. The thesis that psychological and structural approaches represent incommensurable paradigms militates against the kind of cross-level approaches that appear well adapted to the complex realities of organizations. We used MRQAP as one way to combine levels of analysis. This study demonstrates the use of the procedure as a flexible tool for combining multiple observations from each individual’s cognitive map with single measures on each individual within the same analysis. The theoretical basis for the current research is balance theory (Heider, 1958), which has a long history of use within social network analysis; Davis (1979) reviewed the relevant research. Much of this previous work

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modeled relations in social rather than cognitive space, following the influential mathematical extension of Heider’s ideas from the concept of cognitive balance to that of interpersonal balance (Cartwright and Harary, 1956). Social network analysts continue to develop sophisticated mathematical approaches to social structure (e.g., Boyd, 1991), but Blau’s warning remains pertinent: “There is a danger that the refined methods that network analysis . . . has developed will lead to sterile descriptive studies” (1982: 279). In examining Heider’s predictions concerning the strain toward cognitive balance, we have sought to return social network analysis to a theory-driven mode rather than a purely method-driven mode. The research presented here is both an example of how structural methods can incorporate individuals’ cognitive maps and a contribution to the literature on performance reputation. We have interpreted the results as supporting the idea that observers’ perceptions of individuals’ friendship links to prominent others positively influence the observers’ evaluations of the individuals concerned. This interpretation is compatible with balance theory in general and with research on the basking-in-reflected-glory effect in particular However, the data are cross-sectional and can support other causal arguments. For example, it is possible that individuals perceived by their colleagues to be high performers are assumed to have prominent friends. Without more detailed observations on the process by which perceptions concerning performance and friendship links are formed, the present results must remain suggestive rather than conclusive. Future research could investigate how reputations change over time in response to impression management techniques (cf. Tsui and Barry, 1986), and possible personality differences between individuals in their impression management strategies. For example, high self-monitors – individuals who are highly sensitive to social cues – may actively gather and use information concerning who is friends with whom; whereas low self-monitors – those who rely on their own attitudes and feelings for guidance – may be averse to trying to influence perceptions of their social relations (cf. Kilduff, 1992). A second limitation of the current research concerns the small size of the organization studied and the correspondingly high degree of interaction among its employees. Silicon Systems may be untypical because all the employees were at least weakly tied to each other, if Granovetter’s (1973) definition of interacting more than once a year is used. The question of whether the results generalize to large organizations will be difficult to answer given the methodological limitations of social network research. Typically, social networkers attempt to include the complete network of people in a social setting. For research concerning people’s cognitive maps

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of entire networks of relations, data collection and analysis constraints dictate an upper bound of about fifty people (Krackhardt, 1987a). However, in large organizations, where people may not know each other as well as did the people in our study and where, therefore, specific information about others may be scarce, performance reputations may be even more reflective of perceptions and impressions. Research has shown that when decision makers lack information about an employee, they rely on prevailing cognitions, such as stereotypes (Drazin and Auster, 1987), and that halo errors are more likely to occur when raters are evaluating people with whom they are unfamiliar (Kozlowski and Kirsch, 1987). Thus, we would expect individuals’ perceptions to be even more important in determining others’ reputations in large organizations than they were in this small organization. We assumed throughout this research that individuals act strategically to emphasize friendship links to prominent others. This assumption is compatible with the basking-in-reflected-glory effect and with evidence of wide variation with respect to how accurately people perceive network relations (Krackhardt, 1990). The relative opaqueness of friendship relations may provide opportunities for the strategic management of impressions. Research on impression management suggests that individuals perceived to be linked to prominent others may be credited with the ability to form powerful coalitions and the ability to influence higher-status persons (Tedeschi and Melburg, 1984). In other words, individuals perceived to have prominent friends may gain important advantages in the market for power and influence in an organization. Research on these phenomena in organizational settings is lacking, although anecdotes abound. For example, in the struggle for the control of the Lehman Brothers investment banking house, Louis Glucksman gained a crucial advantage by convincing his rival Pete Petersen that he, Petersen, had lost friendships with board members that Glucksman had retained. Neither Petersen nor Glucksman ever checked with the board members to see whether those impressions were accurate (Auletta, 1986). More empirical research on the impression management of friendship ties in organizations would be useful. The declared aim of structural analysis has been to reveal the structural form beneath the apparent content of social relations. According to structuralists, the unit of analysis is “the social network, never the individual” (Mayhew, 1980: 349). Structuralists have tended to “shun the ‘person’ construct as polluting” (White, 1992: 3). In this chapter, we have challenged the notion that structure can be understood apart from the cognitions of individuals. Our argument is compatible with the critique of structuralist claims by poststructuralists (see Agger, 1991, for a

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general introduction). In particular, by including each individual’s cognitive map in the analysis, we follow poststructuralist writers in rejecting the privileged status of any one particular interpretation of structure. We have also challenged the claimed incommensurability of individualism and structuralism by pointing to the influence on structural analysis of the psychology it has purported to reject and by providing an explicit demonstration of how a cognitive theory can guide the use of structural methods. In the next chapter, we continue our investigation of balance theory and the perception of network relations, looking systematically at how people distort perceptions close to and far from their own positions in friendship networks in organizations.

4 Systematic Biases in Network Perception

In Chapter 3, we predicted and found that the perceptions in people’s minds concerning whether a target individual was a friend of a prominent person significantly affected the target individual’s reputation concerning work performance in an organization (Kilduff and Krackhardt, 1994). The actual existence of friendship links, recognized by both parties in each link, had no significant effect on other people’s perceptions of an individual’s reputation as a high performer. This research showed that people’s perceptions of relations helped to determine reputations, whereas the actual structure of relations had no effect. In this chapter, we focus again on perceptions of the friendship network, this time investigating how perceptions are shaped by preexisting expectations. We chose the friendship network to study because this network affects important choices individuals make. We ask, under what circumstances are individuals’ perceptions of the friendship network shaped by schemas concerning how people typically behave in the friendship role? The role of friend is well understood in society, as indicated by the high level of agreement within societies concerning how friends should act in relation to each other (Argyle and Henderson, 1985: 92). People have access to a schema or strategy that specifies how individuals typically act in this role (see the discussions in DiMaggio, 1991; Swidler, 1986). Cognitive psychologists have described schemas as mental structures that enable people to anticipate the general features of recurring situations (Neisser, 1976: 51–78). Schemas allow people to search for and recognize relevant features of the person, situation, or process. The schema that has been most actively researched in the literature on friendship is the balance schema (for reviews, see Crockett, 1982; Markus and Zajonc, 1985; Wasserman and Faust, 1994, chap. 6). According to Heider’s explanation of the balance schema (1958: 205), perceivers tend to treat positive sentiment relations such as friendship as 59

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if they were symmetric and transitive. Symmetry refers to the perceiver’s assumption that friendship relations will be reciprocated. Thus, if the perceiver sees that A chooses B as a friend, the perceiver will anticipate that B will also choose A as a friend. Transitivity refers to the perceiver’s assumption that friendship relations will be complete. Thus, if the perceiver knows both that A is friends with B and that A is friends with C, the perceiver will anticipate that B and C will also be friends. The balance schema, then, consists of a set of cognitive expectations concerning the likely structure of the social world in terms of reciprocity and transitivity. Balance theory literature, however, offers several explanations for why people tend to perceive friendship relationships as balanced. We explore three perspectives: an emotional tension model, a cognitive miser model, and a composite model that combines the predictions of the other two. The Emotional Tension Model The first model emphasizes the emotional tension that results from discrepant cognitions, such as the perception of unbalanced friendship relations. People are motivated to resolve such cognitive discrepancies either by altering cognitions or by taking action in the world. Thus, if Jack perceives that his friendship overtures to his colleague Randolph are unreciprocated, the discrepant cognitions (e.g., “I’m Randolph’s friend, but Randolph doesn’t like me”) will prompt either a change in cognition (“Perhaps I’m not really his friend”) or a change in behavior (“I need to work harder to make this friendship work”). Individuals who perceive that their friendship relations are unbalanced may react with strong emotions rather than with cool analytical reasoning. The balance schema, from this perspective, functions as a deep-seated goal of human interaction (see the discussions in D’Andrade, 1992; Fiske, 1992). People strive to see friendship relations as balanced because the perception of unbalance induces feelings of uncertainty, instability (Festinger and Hutte, 1954), and nervousness (Sampson and Insko, 1964). As Heider suggested, ego’s perception of an unstructured region in the environment functions as a barrier that “makes action and therefore control difficult if not impossible” (1958: 71). The region closest to ego includes ego’s own personal friendships. Ego has power to directly influence whether these friendships are balanced or not. If, for example, Jane finds that her attempts at friendship with Ruby are unrequited, then Jane can sever the friendship link or try even harder to elicit tokens of friendship from Ruby. Ego has considerable potential power to balance friendship relations through direct action of this sort. Similarly, if Jane finds that her friendships with Alice and Shirley have not led Alice and Shirley themselves to become friends, then Jane can

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endeavor to bring her two friends together – over lunch in the cafeteria, for example. Within the region of the network where ego is connected to his or her friends, then, ego is potentially able to balance relationships through direct action. As ego surveys the friendship relations of his or her friends and of friends of friends, however, ego’s power to impose balance becomes considerably weakened. Further, if an alter (i.e., another individual) at some distance from ego is perceived to be involved in friendship relations that are unbalanced, this can disturb ego, because alter is still part of ego’s social world and as such is part of the mutually shared environment in which ego is involved every day. Perturbations affecting alter affect ego because ego encounters alter and alter’s friends in the daily round. The region occupied by an alter with unbalanced relations is likely to be perceived as one of uncertainty and tension. For relations close to ego, therefore, motivation is strong to balance relationships, and ego has the power to impose balance. As ego surveys relations at distances farther and farther from ego’s own position, however, the power to act is diminished, but the emotional uncertainty induced by perceived imbalance is also likely to be diminished. The unbalanced friendship relations of friends of friends represent areas of uncertainty and tension in the social world as perceived by ego. However, the prospect of uncertainty and tension derived from unbalanced distant relations is likely to be less troublesome than the immediacy of uncertainty and tension derived from unbalanced relations within ego’s own friendship circle. How quickly are the tension and uncertainty that are induced by perceived unbalanced friendship relations reduced as ego scans the social relations of friends, friends of friends, and so on out to the periphery of the social world? There has been some discussion of this issue. Heider (1958: 71) mentioned the problematic nature of unstructured regions anywhere in the mutually shared environment, whereas Insko (1981: 322–3) suggested that ego is likely to suffer little tension to the extent that ego has low involvement with individuals whose relations are unbalanced. Our working assumption is that the emotional pressure to perceive relations as balanced sharply diminishes but does not disappear as ego looks beyond his or her own friendship circle. Previous research has shown that people will alter relations or cognitions to preserve balance in close relations (Kumbasar, Romney, and Batchelder, 1994; Newcomb, 1961), and that individuals tend to seek out information that reduces dissonance and to avoid information that increases it (Ehrlich, Guttman, Schonbach, and Mills, 1957). Considerable evidence also indicates that people prefer balanced relations in general, even when they themselves are not directly connected to the

Perceiving Networks

Proportion

62

Distance Figure 4.1. Illustration of the emotional tension model’s prediction that the proportion of relations perceived by ego as balanced declines with social distance from ego.

individuals concerned (De Soto, 1960; Freeman, 1992). In the everyday world of social relationships, individuals are frequently brought into contact with acquaintances whose friendship relations may be unbalanced. In other words, individuals may be required to negotiate social pathways that are perceived to be unstructured and therefore problematic. Avoiding people with friendship problems may be either not possible or not compatible with, for example, a productive career. Thus, if Alice sees John as someone whose attempts at friendship are unreciprocated, she may want to avoid John; interacting with him may be bothersome because of the presumed tension he is under. However, Alice may have to work with John to accomplish her own tasks. Thus, the perceived imbalance in John’s friendships can affect Alice even if John himself is not a personal friend of Alice. We assume that the effect of alter’s unbalanced relations on ego diminishes sharply but does not disappear as ego considers alters farther and farther away from ego. To summarize, an emotional tension perspective on perceived balance leads to the prediction that ego’s close relations will tend to be perceived by ego as balanced, because ego has both the motivation and the power to arrange for them to be balanced. The curve in Figure 4.1 illustrates how ego’s perception of balance may be affected by social distance. As ego looks beyond the immediate circle of close friends, the emotional

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pressure to perceive relations as balanced sharply diminishes. Thus, as ego assesses the likelihood of balance among strangers on the remote horizon of ego’s social world, the degree of perceived balance should approach its minimum. The Cognitive Miser Model A contrasting perspective that represents a more recent paradigm in the field of social cognition views the person as a cognitive miser who, under circumstances of “unavailability or indeterminacy of important information” (Taylor, 1991: 195), relies on short cuts or heuristics to fill in the blanks in knowledge. The cognitive miser perspective emphasizes that even when people believe they are using complete information to form impressions or make decisions, they may be relying on only one or two salient cues (Dawes, 1976; Taylor, 1981; Taylor and Fiske, 1978). People are cognitive misers in the sense that they tend to avoid devoting the time and effort required to locate and use all relevant information prior to forming an opinion or perception. Applied to perceptions of friendship networks, this perspective suggests that people utilize schemas to help make sense of the mass of potential relations they observe. People may avoid expending cognitive energy keeping track of the potential relations characteristic of social groups. To the extent that an individual uses a well-developed schema, many details of the social world may be filled in by the schema rather than derived from actual perception (see the review by Mandler, 1979). The balance schema, then, provides ego with a way to infer the existence of relations when information is incomplete (Freeman, 1992). In particular, as people consider the friendship relations of those increasingly distant from themselves, they will have less and less knowledge of possible unbalanced relations (cf. McPherson, Popielarz, and Drobnic, 1992: 155). The farther away the relationship, the less information ego has regarding it and the more likely, therefore, ego is to assume that relations are balanced (Kuethe, 1962). There is a further reason why, from a cognitive miser perspective, people may rely increasingly on assumptions concerning balance as they scan distant relations: As people scan relations at greater and greater distances from themselves, they incorporate more and more people into their social world, and the number of possible relationships they must keep track of increases disproportionately. The effect of increasing group size on the number of possible relations in a group was dubbed “the law of family interaction” in an influential article by Bossard (1945: 292). As the group increases from four to eight members, for example, Bossard calculated that the number of possible relations increased from six to

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twenty-eight. Other researchers have offered refinements concerning how quickly the number of possible relations increases as each additional member is added to the group (e.g., Kephart, 1950), but all echo Bossard’s observation that the larger the group becomes, the more disproportionate the increase in possible personal relationships between members. From a cognitive miser perspective, people are likely to use the balance schema to fill in the blanks in their social knowledge rather than try to keep track of the large numbers of possible relations involving people at farther and farther distances from their own friendship circles. The law of family interaction suggests, therefore, that ego faces a daunting cognitive task in trying to keep track of relations of people at farther and farther distances. From this perspective, ego may tend to rely on the balance schema as a useful heuristic for making sense of distant relationships. Instead of keeping track of which relationships are reciprocated or transitive, ego may tend to assume that distant relationships are generally balanced. Within ego’s own social circle, however, unbalanced relations concerning ego’s own personal friends may be hard to ignore. Research suggests that people are more likely to notice evidence of unbalance than balance. For example, angry faces are found more efficiently in happy crowds than are happy faces in angry crowds (Hansen and Hansen, 1988). Heider suggested that unbalanced relations about which we have personal knowledge “stimulate us to further thinking” and “have the character of interesting puzzles” (1958: 180). In their review of the literature on the recall of schema-consistent and schema-inconsistent information, Markus and Zajonc (1985) suggested that schema-inconsistent information is likely to be recalled if it competes with the information in the schema and if the cognitive task requires the participant to make use of it. People are likely to remember the existence of unbalanced friendship relations in which they themselves are involved because this imbalance competes with the structures suggested by the balance schema, and the cognitive task of making sense of the immediate social world requires people to keep track of unbalance (cf. Janicik and Larrick, 2005). This is true, for example, in work organizations where individuals are likely to see their friends every workday and are therefore reminded daily of the absence of reciprocity and transitivity. In summary, the cognitive miser perspective suggests that people are likely to notice unbalanced relations among those close to themselves. However, as people scan distant relations, they are likely to rely on the balance heuristic to fill in the blanks of the relations of these distant others. Figure 4.2 offers one possible representation of the cognitive miser model, depicting an increasing probability of perceived balance for relations farther and farther away from ego.

65

Proportion

Systematic Biases in Network Perception

Distance Figure 4.2. Illustration of the cognitive miser model’s prediction that the proportion of relations perceived by ego as balanced increases with social distance from ego.

The Composite Model Despite the apparent contradiction between the emotional tension and cognitive miser models, there is a way to combine these two views: The balance schema may be imposed on close relationships (to avoid emotional tension) and attributed to the friendship relations of distant others (to fill in the blanks in social knowledge). If one accepts the extensive evidence that people are likely to suffer discomfort when they perceive their own friendship relations as imbalanced, then the major results of the emotional tension model are accommodated. According to this model, people are relatively unaffected by the perception of imbalance among those with whom they have no friendship ties. The motivation to change perceptions in favor of balance, then, is likely to affect mainly the perceptions of ego’s own friendship relations. If ego is not directly involved, little discomfort results from perceived imbalance. According to the cognitive miser model, however, while casting one’s gaze outward over the friendship relations of those with whom one has no direct links, one is likely to have less and less knowledge concerning such details as whether the relations are reciprocated or transitive. The less information that is available, the more one relies on the balance schema to fill in the blanks in one’s knowledge. The composite model, then, suggests that the hypothesized graphs in Figures 4.1 and 4.2 can be joined to display a curvilinear relationship between social distance and the degree of balance perceived. In summary,

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according to the composite model, individuals perceive both their immediate friendship circle and the periphery of their social networks as more balanced than social worlds of intermediate distance.

Method At each of the four sites described in this section, participants were promised and given an overview of the findings. At all four sites, the same questionnaire was used, as described in the “Perceived Friendship Network” section. Nonrespondents were excluded from all analyses. The relatively high response rates (which varied from 86 percent to 100 percent) reduced problems associated with nonresponse bias. Site 1: High-Tech Managers (HT) The participants at this site consisted of all twenty-one managers of a West Coast entrepreneurial firm of approximately 100 people employed in the manufacture of high-tech machinery. The managers were all men. David Krackhardt collected the data as part of an effort to explore the effects of a previous organizational development intervention conducted by external consultants. All twenty-one participants completed the questionnaire, and no compensation was offered to the participants. (See Krackhardt, 1987a, for further details.) Site 2: Government Office (Gov) This workgroup consisted of thirty-six professional staffers in the federal bureaucracy. Their job included advising the executive branch concerning courses of action that would facilitate the current public policy agenda. Each person in this workgroup had an advanced degree at the master’s level or higher. The group’s composition changed yearly as new staffers were added from different departments and others rotated out. The leadership of the group, however, had been in place for years. Thirty-one of the thirty-six people in this office completed a questionnaire, and no compensation was offered to the participants. Site 3: Silicon Systems (Sil) The participants included all thirty-six employees (twenty-eight men and eight women) of a small entrepreneurial firm located in the Bay Area of California. The employees were mostly semiskilled workers who installed computers and trained their clients in their use. Thirty-three of the thirtysix employees accepted $3 each to complete the questionnaire. (See Kilduff and Krackhardt, 1994, for more details.) Site 4: Pacific Distributors (Pac) The participants included all thirty-three supervisory and managerial personnel (fifteen men and eighteen women) located at the headquarters of

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67

a small, rapidly growing regional distributor of electronic components. The company employed 162 people in its headquarters and four branch offices. All thirty-three participants accepted $10 each to complete the questionnaire. (See Krackhardt and Kilduff, 1990, for more details.) Measures Perceived Friendship Network To capture participants’ perceptions of friendship relations, we used the same questionnaire across all four sites. At each site, every respondent answered the following question about every other person in the organization: “Who would this person consider to be a personal friend? Please place a check next to the names of those people who that person would consider to be a friend of theirs.” For example, John Meredith of the Sil sample was asked a series of thirty-six questions concerning the friendships of his thirty-six coworkers. The questions were in this form: “Who would Jane Asch consider to be a personal friend?” Each question was followed by the list of thirty-five employees’ names. John Meredith then checked the names that indicated his perceptions of who Jane Asch considered to be her personal friends. (For more details, see Kilduff and Krackhardt, 1994.) Each respondent, then, gave us a complete cognitive map of his or her perceptions concerning who was friends with whom in the organization. To measure perceived friendship links, we used the following procedure: A friendship tie as perceived by person k existed between person i and person j only if k responded on the questionnaire that i considered j a friend. Perceived Reciprocity We measured the extent to which each person in the network was perceived by every other person in the network to be involved in reciprocated friendships. We created a matrix of scores for each site, with each cell in the matrix indicating (according to person i’s perceptions) the proportion of person j’s dyadic relationships that were reciprocated. More formally, the perceived reciprocity matrix was defined as follows: Sij = NSij / (NSij + NNij ), where NSij is the number of reciprocated dyadic relations that i perceives j to be involved in, and NNij is the number of unreciprocated dyadic relations that i perceives j to be involved in. Perceived Transitivity We measured the extent to which each person in the network was perceived by every other person in the network to be involved in transitive friendship relations. We created a matrix of scores for each site, with each ij cell representing (according to i’s perceptions) the proportion of j’s triadic relationships that were transitive. Given that we separately analyzed

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perceptions of reciprocity from perceptions of transitivity, we chose the conservative path of considering only reciprocated ties in the transitivity analysis. Although there is a tradition within social network analysis of considering transitivity among unreciprocated relations as balanced (e.g., Holland and Leinhardt, 1977), it is clear from Heider’s (1958: 206–7) discussion of transitivity that he considered positive relations to be balanced only if the transitive relations were also reciprocated. Therefore, following Heider, when we refer to friendship relations in our definition of what constitutes a transitive triad, we are referring to reciprocated friendship relations. To compute transitivity, we temporarily symmetrized ego’s perceptions of friendship relations using the intersection rule that for a friendship relation between i and j to exist in ego’s perceptions, ego must perceive both a friendship link from i to j and a friendship link from j to i. Formally speaking, then, for any triple of actors i, j, and k, given that i and j are friends and j and k are friends, the triple ijk is transitive if and only if i and k are friends. Transitivity is violated (i.e., the triple is intransitive) if, given that i and j are friends and j and k are friends, i and k are not friends. Vacuously transitive triples, triples that do not meet the conditional requirement that i and j are friends and j and k are friends, are not considered in this analysis. The formula for computing each cell in the matrix T of perceived transitivity scores was as follows: Tij = NTij /(NTij + NTij ), where NTij is the number of transitive triples that i perceives j to be involved in, and NIij is the number of intransitive triples that i perceives j to be involved in. If NTij + NIij = 0 (i.e., if none of the triads perceived by i that include j meet the preconditions of transitivity), then Tij was set equal to a missing value. Actual Friendship Network To measure actual friendship links (distinct from perceived friendship links), we determined the locally aggregated structure (Krackhardt, 1987a) as follows: A friendship tie existed between persons i and j only if person i claimed person j as a friend and person j agreed that person i claimed person j as a friend. Thus, an actual friendship link from i to j was defined as existing when both parties agreed that it existed. Actual Reciprocity We created a matrix for each site in which each column in the matrix indicated the proportion of person j’s dyadic relationships that were actually reciprocated (as validated by both parties to the friendships). Thus, whereas person i might perceive that person j’s friendships were 40 percent reciprocated, if j’s friendships were in fact reported by j and j’s friendship partners to be 60 percent reciprocated, the column of scores for j in

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the actual reciprocity matrix would consist of .6 repeated in each cell of the column. Actual Transitivity We created a matrix for each site in which each column in the matrix indicated the proportion of person j’s triadic relationships that were actually transitive. We first symmetrized the actual friendship matrix, using the intersection rule that for a reciprocated tie to exist between persons i and j, person i had to report a friendship tie from i to j and person j had to report a friendship tie from j to i. Then, following the procedure outlined in the computation for perceived transitivity, we calculated the actual proportion of triads involving person j that were transitive. Each column in the matrix indicated the extent to which person j was involved in transitive triads. Social Distance We measured the extent to which each person in the network perceived himself or herself to be distant from every other person. Thus, our measure of social distance was a perceptual measure of how close or far ego perceived alter to be from ego. In a graph, the path distance between two points is the length of the shortest path (or geodesic) that connects them (Harary, 1969). As Feld and Grofman (1989) pointed out, when networks are represented as graphs, the path distance between any two points is a good proxy for social distance. We measured the shortest path distance between each pair of individuals i and j as perceived by i. Thus, if respondent Sam Berkowitz perceived that the shortest path connecting him to Alan Hobbs consisted of four lines, the distance from Berkowitz to Hobbs was measured as 4. We treated social distance within any individual’s cognitive map as a symmetric concept. That is, if ego perceived the distance from ego to alter as equal to some value x, then this implied that ego also perceived the distance from alter to ego as equal to x. Thus, we symmetrized ego’s perception of the friendship network before calculating social distance. For example, if ego perceived that ego was a friend of j and also perceived that j considered k a friend, then we deemed the social distance between ego and k equal to 2. Conversely, if ego perceived that k considered j a friend and that j considered ego a friend, then this was also deemed to be a distance of 2 between ego and k. In calculating the social distance measure used in predicting the degree of reciprocity in ego’s perceptions, we symmetrized ego’s cognitive map of the network using the union rule: A friendship relationship existed if ego perceived either of the people to have a friendship tie to the other. In contrast to the reciprocity analyses, the transitivity analyses were conducted

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on matrices that had already been symmetrized using the intersection rule: A friendship relation existed if ego perceived both of the people to have a friendship tie to each other. To be consistent, we calculated the social distance measure used in predicting the degree of transitivity in ego’s perceptions on the matrix symmetrized using the intersection rule. For both the reciprocity and transitivity tests, we considered distances of infinity (indicative of the absence of paths between the two nodes) to be missing values. We also performed analyses with the infinite distances recoded as distance N (the number of nodes in the network), and although the meta-analysis results were the same, the large distances tended to act as outliers, obscuring the true underlying relationships. In this chapter, we restricted our presentation of the data to those cases where distances were “real” (that is, the actors were mutually reachable) and not infinite. Distance squared was calculated in a straightforward manner but was mean-centered (i.e., the mean was subtracted from all values) before the term was squared. This reduced collinearity problems in the regression because the correlation between a variable and its mean-centered squared term is 0, whereas the correlation between a variable and its (non-meancentered) square can be high, resulting in unstable coefficient estimates. Density We assessed the density of each respondent’s cognitive map as the number of lines in the map divided by the maximum possible number of lines (Scott, 1991: 74). Some respondents perceived many friendship links, whereas other respondents perceived few links. We controlled for this variation in density across perceivers’ cognitive maps as follows: For each respondent, we calculated a number between 0 and 1 that indicated the proportion of all possible friendship links that were perceived to exist. As with the distance measure, the density measure was based on the specific matrix that predicted either transitivity or reciprocity. That is, densities in the models used to predict transitivity were based on the symmetrized friendship networks from which the transitivities were calculated. Densities in the models used to predict reciprocity, on the other hand, were based on the nonsymmetrized friendship networks from which the reciprocity proportions were calculated.

Data Analysis Social network data are often not amenable to standard statistical tests, such as ordinary-least-squares analysis, because the observations cannot be assumed to be independent. For example, in the current research, the transitivity matrix for the Pac site includes thirty-three scores from each person in the sample. Each of the thirty-three scores within a row of this

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matrix derives from the same source (the cognitive map of the respondent) and therefore exhibits systematic interdependence. To deal with this problem, we used the Multiple Regression Quadratic Assignment Procedure (MRQAP), which has been explained in detail in Chapter 3 and in previous work (e.g., Kilduff and Krackhardt, 1994; Krackhardt, 1987b, 1988). To assess the extent to which the combined results of our analyses across four sites offered support to the expected relationships between variables, we performed a meta-analysis (Hedges and Olkin, 1985). Typically, the null hypothesis for a meta-analysis is that all samples are drawn from populations in which there is no relationship between the variables of interest (these variables being, in our case, distance, distance squared, and proportions of balance). If the meta-analysis shows that the null hypothesis is rejected, the conclusion follows that for at least one of the samples there is a significant relationship between the variables of interest. However, finding an effect for only one of the samples scarcely ranks as “persuasive evidence of the efficacy of a treatment” (Hedges and Olkin, 1985: 45). However, the studies from four sites being combined in our analysis use exactly the same measurement instruments and replicate exactly the same regression model. In such a case, we can test the likelihood that the distance-squared coefficients that we are interested in are not significantly different across the four samples, and whether we can therefore interpret the combined p value to refer to a common population. Hedges and Olkin (1985) described many situations for which such a test can be performed using a Q statistic. However, the data that we collected, with their autocorrelated structure requiring a nonparametric MRQAP analysis, falls outside the situations described. This is unfortunate because the problems of autocorrelated data are common in the study of social networks. The arguments of Hedges and Olkin can nevertheless be extended to our case by using the information in the permuted values of the regression coefficients to replicate the weighted mean estimates of the population beta and the estimate of the standard error of the beta. Because this is the first time, to our knowledge, that such a Q test for meta-analysis has been applied to social network models such as ours, we describe here in detail the procedure that we used in calculating and testing Q. Notation is drawn from Hedges and Olkin (1985). Q is a test statistic that compares the observed betas β i from each sample i with a weighted estimate of the population beta β + :

Q=

  k  (βi − β+ )2 2

i=1

σˆ (βi )

(1)

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where k is the number of samples, and σˆ (βi) 2 is the estimated variance of each beta, which has been estimated by calculating the variance of the betas generated across all 999 permuted values of the dependent variable under the null hypothesis. The Q statistic is asymptotically distributed as a chi-square with (k − 1) degrees of freedom:   k  βi 2

β+ =

i=1 k 



σˆ (βi )

.

1 2

i=1

σˆ (βi )

The β + parameter is estimated by calculating a weighted average across the k sites, where each weight is inversely proportional to the variance of β i in each sample. For both the reciprocity and transitivity analyses, the following computations had to be made for each site i: β i , σˆ (βi) 2 , β i −β + , (β i −β + )2 , (β i −β + )2 /σˆ (βi) 2 . To test for the possibility (suggested by a colleague) that in calculating transitivity we might have created a positive correlation with distance (and distance squared), we randomly generated raw friendship data. For one hundred samples, the regression coefficients for distance squared in the prediction of reciprocity and transitivity were not significantly different from 0, and thus the distance-squared analyses appear to be unbiased. A slight but significant negative bias was uncovered for the coefficient for distance in the transitivity model. To ensure that the results were not affected by this bias, we recalculated the significance levels of this coefficient against a null hypothesis of the mean of the simulated samples, using the standard error generated by the simulations. The results of the meta-analysis become even stronger when we use this conservative test. Thus, the results that we report in the following section cannot be attributed to an artificial bias introduced by the analytic procedure itself.

Results Table 4.1 provides a summary of the variables used in this analysis. The proportions of reciprocity and transitivity perceived by individuals in friendship networks differed slightly across the four sites, as shown in Table 4.2. The mean proportion of perceived reciprocity ranged from .39 to .49, whereas the mean proportion of perceived transitivity ranged from .20 to .30. Tables 4.3 and 4.4 present information addressing the issue of whether the regression coefficients differed significantly across the four sites and whether it is therefore acceptable to interpret meta-analysis results as

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Table 4.1. Summary of Research Variables Variable Dependent Matrices Perceived reciprocity

Perceived transitivity

Independent Matrices Distance

Distance squared Control Matrices Density

Actual reciprocity and transivity

Definition of Each Cell in Matrix Respondent i’s perception of the proportion of pairs including j that were reciprocated Respondent i’s perception of the proportion of triads including j that were transitive Length of the shortest path between i and j as perceived by i Mean-centered distance squared Number of links in respondent i’s cognitive map divided by the maximum number of links possible Using the rule that both individuals must agree that each considers the other a friend before a friendship link is established, each cell contains the actual proportion of pairs (or trials) including j that were reciprocated (or transitive)

referring to a common population. The Q statistics at the bottom of Tables 4.3 and 4.4 are nonsignificant, indicating that the regression coefficients for distance and distance squared did not differ significantly across the four sites in either the reciprocity or the transitivity analyses. For example, in Table 4.3, the overall β + for distance squared was .016, which was calculated by summing the four entries for distance squared in the third column of the table. This yielded a nonsignificant Q of 0.476 ( p = .924, d f = 3). Thus we conclude that the four distance-squared coefficients in the reciprocity model were not significantly different from one another. On the basis of nonsignificant Q statistics for distance and

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Perceiving Networks Table 4.2. Proportions of Perceived Balance in Friendship Networks Site Variable Reciprocity M SD Transitivity M SD

HT n = 21

Gov n = 31

Sil n = 33

Pac n = 33

.39 .35

.44 .35

.44 .36

.49 .35

.20 .26

.30 .31

.25 .27

.24 .30

Notes: HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

Table 4.3. Summary of Q Analyses Determining Whether Reciprocity Regression Coefficients Differed across Four Samples Individual Site Statistics (βi − β+ )2 Variable Site 1 Distance Distance squared Site 2 Distance Distance squared Site 3 Distance Distance squared Site 4 Distance Distance squared

βi

Variance of βi

Variance of βi

−0.0894209 0.0111083

0.0017081 0.0003310

0.3814442 0.0790133

−0.0777464 0.0235878

0.0011510 0.0002434

0.1666685 0.2228960

−0.0717410 0.0145674

0.0005120 0.0000565

0.1202192 0.0484558

−0.0057950 0.0249318

0.0013735 0.0006016

2.4577374 0.1260871

All Four Sites Combined (df = 3) Distance Distance squared

All Four Sites Combined β+

−0.0638959 0.0162220

Q

p

3.127 .373 0.476 .924

distance squared in Tables 4.3 and 4.4, we can assume that the results of meta-analyses on these coefficients refer to a common population. Figure 4.3 presents the results of the reciprocity analyses for the combined data across all four sites and for each site individually. The overall graph shows a distinct curvilinear shape, indicating a tendency for ego to perceive close and distant relations as more reciprocated than relations in

Table 4.4. Summary of Q Analyses Determining Whether Transitivity Regression Coefficients Differed across Four Samples Individual Site Statistics (βi − β+ )2 βi

Variable Site 1 Distance Distance squared Site 2 Distance Distance squared Site 3 Distance Distance squared Site 4 Distance Distance squared

Variance of βi Variance of βi

−0.l242139 0.0640057

0.0039149 0.0016400

0.8911572 1.0929966

−0.1134550 0.0511434

0.0017719 0.0005701

1.3169683 1.5240775

−0.0484082 0.0164252

0.0011504 0.0004052

0.2494559 0.0678201

−0.0293083 −0.0029419

0.0012974 0.0003810

0.9900603 1.5893159

All Four Sites Combined (df = 3) Distance Distance squared

All Four Sites Combined β+

Q

p

−0.0651483 3.448 .328 0.0216671 4.274 .233

0.8 Pac

0.7

Gov Overall

Proportion

0.6 Sil

0.5 0.4 0.3 0.2

HT

0.1 0 1

2

3

4

5 Distance

6

7

8

9

Figure 4.3. Proportions of perceived reciprocity of people’s relations at four sites as a function of social distance from ego. HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

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Perceiving Networks 0.5 Overall HT

0.4

Gov

Proportion

0.3

Sil

0.2

Pac

0.1

0 1

2

3

4

5

6

7

Distance Figure 4.4. Proportions of perceived transitivity of people’s relations at four sites as a function of social distance from ego. HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

the middle distance of about two to five links from ego. This overall Ushaped curve provides support for a composite model that includes both the emotional tension model’s prediction (higher perceived reciprocity for close relations) and the cognitive miser model’s prediction (higher perceived reciprocity for more distant relations). As Figure 4.3 shows, the graphs reached their minima at values of social distance ranging from 2.12 (at the Pac site) to 5.8 (at the HT site). These minima were within the range of the data that we collected: The maximum values for social distance for each site were as follows: Pac = 5, Gov = 7, Sil = 9, and HT = 7. Figure 4.4 presents the results of the transitivity analyses for the combined data across all four sites and for each site individually. Again, the overall graph shows distinct U-shaped curvilinearity, supporting the predictions of the composite model. The graph for the Pac site, however, differs from the graphs for the other sites, showing a rather linear downward slope. At this site, therefore, the proportion of relations perceived as transitive tended to decrease with increasing distance from ego. As Figure 4.4 shows, for the three sites exhibiting positive curvilinear graphs, the graphs reached their minima at values of social distance ranging from 2.8 (at the HT site) to 3.5 (at the Sil site), all within range of the data that we collected. The maximum values for social distance for each site were as follows: HT = 5, Gov = 5, Sil = 7, and Pac = 7.

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Table 4.5. Summary of Multiple Regressions Predicting Proportions of Perceived Reciprocity in Friendship Networks B

β

p

Site 1: HT (n = 21) Distance Density Distance squared Actual proportion

−8.942 −2.443 1.111 9.768

−26.659 −0.370 8.600 9.895

.984 .502 .275 .170

Site 2: Gov (n = 31) Distance Density Distance squared Actual proportion

−7.775 46.564 2.359 −3.454

−21.294 12.767 15.605 −2.514

.990 .109 .069 .686

Site 3: Sil (n = 33) Distance Density Distance squared Actual proportion

−7.174 −27.498 1.457 17.616

−25.013 −3.883 16.381 16.718

.999 .693 .034 .033

Site 4: Pac (n = 33) Distance Density Distance squared Actual proportion

−0.580 21.742 2.493 14.174

−1.603 3.736 9.808 12.649

.542 .449 .169 .067

Variable

Note: Coefficients were multiplied by 100 for ease of presentation. Infinite distances are deemed missing values. All tests are one-tailed; thus, all negative coefficients have p values greater than .5 HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

Table 4.5 presents the results of regression analyses predicting proportions of perceived reciprocity at each of the four sites, whereas Table 4.6 presents the equivalent results for perceptions of transitivity. These results provide the basis for the meta-analysis results summarized in Table 4.7, where data from all four sites are combined. Consistent with the information evident in Figures 4.3 and 4.4, the meta-analysis confirms that the overall data exhibited curvilinearity (as assessed by the positive distance-squared term): The coefficients for overall distance squared were significant for both reciprocity (Z = 2.432, p = .008) and transitivity (Z = 2.301, p = .011). We can conclude from the evidence in the graphs and in the statistical analyses that the data are probably best fit by a U-shaped curve. In other words, the evidence lends support to a composite model that combines the downward curving prediction of the emotional tension model (less perceived reciprocity as ego looks beyond his or her immediate friendship

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Perceiving Networks Table 4.6. Summary of Multiple Regressions Predicting Proportions of Perceived Transitivity in Friendship Networks B

β

p

Site 1: HT (n = 21) Distance Density Distance squared Actual proportion

−12.421 281.260 6.401 6.666

−45.997 36.541 39.184 4.952

.973 .058 .065 .357

Site 2: Gov (n = 31) Distance Density Distance squared Actual proportion

−11.346 203.022 5.114 47.936

−38.802 47.681 31.453 28.180

.994 .004 .014 .012

Site 3: Sil (n = 33) Distance Density Distance squared Actual proportion

−4.821 152.721 1.643 21.258

−21.331 17.578 17.709 14.661

.929 .118 .167 .114

Site 4: Pac (n = 33) Distance Density Distance squared Actual proportion

−2.931 262.219 −0.294 12.161

−13.123 35.824 −2.999 7.965

.768 .122 .530 .278

Variable

Note: Coefficients were multiplied by 100 for ease of presentation. Infinite distances are deemed missing values. All tests are one-tailed; thus, all negative coefficients have p values greater than .5. HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

circle) and the upward curving prediction of the cognitive miser model (more perceived reciprocity as ego’s gaze includes the friendship relations between dyads relatively unfamiliar to ego). In the statistical analyses reported in the tables, we controlled not just for the linear effects of social distance and the density of ego’s network but also for the actual proportion of balance in specific friendship dyads. We were able to focus explicitly on the question of how social distance affected perceptions of balance in friendship relations while controlling for the possibility that perceptions might, in fact, align with reality. Controlling for people’s tendency to perceive balance where the members of the friendship pair confirmed that it existed, we found evidence for a curvilinear effect of social distance on perceived balance. In other words, the analyses allow us to reject the possibility that curvilinearity in the data derives not from perceptions but from the distribution of actually occurring friendship reciprocity and transitivity.

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Table 4.7. Summary of Meta-Analysis Results across Four Sites Predicting Proportions of Perceived Balance in Friendship Networks Reciprocity Variable

Transitivity

p, one-tailed

Z

p, one-tailed

Z

Site I: HT (n =21) Distance Distance squared

.984 .275

−2.144 0.598

.973 .065

−1.927 1.514

Site 2: Gov (n = 31) Distance Distance squared

.990 .069

−2.326 1.483

.994 .014

−2.512 2.197

Site 3: Sil (n = 33) Distance Distance squared

.999 .034

−3.090 1.825

.929 .167

−1.468 0.966

Site 4: Pac (n = 33) Distance Distance squared

.542 .169

−0.105 0.958

.768 .530

−0.732 −0.075

All Four Sites Combined Distance Distance squared

.999 .008

−3.833 2.432

.999 .011

−3.320 2.301

Note: All tests are one-tailed; thus, all negative coefficients have p values greater than .5. HT = high-tech managers; Gov = government office; Pac = Pacific Distributors; Sil = Silicon Systems.

Discussion The results of both the graphical and statistical analyses suggest that individuals tend to perceive both close and distant relations as balanced. We found support for a composite model that includes both an emotional tension effect (close relationships tend to be perceived as balanced) and a cognitive miser effect (distant relationships tend to be perceived as balanced). The results of the meta-analyses were consistent for both perceived reciprocity and perceived transitivity and suggest a unifying perspective on how individuals cognitively structure their social worlds. Previous research has shown that people tend to prefer balanced rather than imbalanced relations in both perceived networks (De Soto, 1960; Freeman, 1992) and behavioral networks (Davis, 1979). The current research across work organizations suggests that this general preference has specific significant effects on ego’s perceptions of friendship relations both close to and distant from ego. Close to ego, the motivation to perceive one’s own interpersonal world as balanced may be to avoid emotional upset. Far from ego, the motivation to perceive the relations of relative strangers as balanced may be to fill in the blanks in social

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structure. Thus, the explanation of balanced structures in social networks can combine both hot (emotional) and cold (knowledge) approaches to social cognition. One of the puzzles of the current research concerns the anomalous result for perceptions of transitivity in site 4. The sample for this organization differed from the samples from the other organizations in that we collected data only from the managerial core at headquarters, not from all the people at headquarters. The composite model that we present may well apply only to bounded groups such as those in sites 1, 2, and 3. Site 4 was also different in being a relatively large organization compared with the other three sites. In larger groups, the task of organizing the relations among the large set of alters may be difficult. Extensive previous research (reviewed by Moreland and Levine, 1992) has shown that most natural groups are quite small, averaging two to three members and rarely exceeding five or six members. People appear to have difficulty coordinating social interactions that involve more than five persons (Despartes and Lemaine, 1986). The minimum for reciprocity varied more than the minimum for transitivity across the different sites. Transitivity, as an indicator of balance, may be difficult to assess beyond a distance of four because it involves organizing six directional ties rather than the two ties involved in reciprocated relations. The task of mapping transitivity relations is relatively complex even in small organizations once ego’s gaze travels beyond his or her familiar acquaintances. Our study differs from previous research in the way that we measured social distance. Whereas in the present study we used a continuous measure of distance, previous work (Kumbasar et al., 1994) dichotomized alters into those who were at a distance of one from ego and those who were at a distance greater than one from ego. The dichotomization of distance prevents discovery of a curvilinear relationship even if one exists in the data. In the present research, we aimed to go beyond the laboratory to study the effects of schema use in actual social settings, in keeping with calls for more field-based studies of human cognition (e.g., Funder, 1987). We tested our models in four quite different social arenas rather than resting content with the standard single setting common in social network studies (e.g., Burkhardt and Brass, 1990; Kilduff, 1992; Krackhardt, 1990; Walker, 1985). A further strength of the current research is the inclusion in the statistical tests of variables derived from naturally formed networks of friendships as well as perceptions of those networks. This inclusion allowed us to focus on how schemas shape perceptions while taking account of the possibility that reality shapes perceptions. One of the strengths of the current research – data collected from actual social settings – is accompanied by a potential weakness. Because we

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have not experimentally manipulated the causal factor (social distance) to which we attribute the findings, the possibility remains that our causal logic could be reversed. Thus, it is possible that people tend to either draw close to or keep quite distant from those whose relationships they perceive as balanced. In the current cross-sectional analyses, we are unable to track dynamic processes of this sort, and this suggests that future work could explore the effects of social distance on perceived balance in more controlled settings. The attempt to understand transitivity in triads has a long but rather confused history. One of the leading researchers in the field was led to declare that “after a decade of matrix grinding, I have no more idea of why triads are transitive than I did when I began” (Davis, 1979: 60). Whereas reciprocity is well established as a defining feature of human society (Gouldner, 1960) and is especially evident among adults in the world of work (Gouldner, 1973: 268), transitivity appears most prominently in groups of junior high school students (Davis, 1979: 61). Transitivity, of course, involves an ordering of relations among a three-person group, whereas reciprocity involves relations among only two people at a time. Ego has greater control over whether a friendship link from alter to ego is reciprocated than whether two of ego’s friends decide to complete the third link of a transitive triplet. In other words, it is easier for ego to impose reciprocity relative to transitivity on perceptions of friendship relations (Doreian, Kapuscinski, Krackhardt, and Szczypula, 1996). The current research, in proposing that perceived transitivity is a function of social distance, offers a parsimonious explanation for when transitivity in social organizations is likely to be found, an explanation that works equally well for transitivity as for reciprocity. The importance of reciprocity and transitivity as structural principles of group organization has been widely recognized. Gouldner (1960) suggested that reciprocity functions to counter bureaucratic impersonality and to maintain the division of labor in work organizations. He quoted Simmel to the effect that all contacts among people “rest on the schema of giving and returning the equivalence” (Gouldner, 1960: 162 162). Recent work examining social relations across diverse studies has confirmed the pervasiveness of the reciprocity heuristic in perceptions of liking (Kenny et al., 1996; Kenny and DePaulo, 1993). The principle of transitivity has been described as the “key structural concept in the analysis of sociometric data” (Holland and Leinhardt, 1977: 49–50). The expectation that friendships will be balanced may serve to stabilize but not rigidify organizational systems in which patterns of interaction are reproduced daily. The assessment of perceived friendship in our research is two-valued, consistent with Heider’s (1958) discussion: People are either friends or not

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friends. Transitivity, therefore, can be understood as an instance of the logical principle known as the multiplicative rule. This rule implies that, for example, the multiplication of two positives (i.e., friendship relations between A and B and between A and C) results in a positive (i.e., a friendship relation between B and C). Because a two-valued approach to balance theory is perfectly compatible with traditional logic (as Insko, 1999, and Runkel and Peizer, 1968, point out), a preference for perceiving two-valued relations as transitive can be understood as a preference for perceiving the world as a logical, ordered place. One potentially valuable extension of the current research would be to examine preferences for balance using a many-valued rather than a two-valued approach (for two experimental investigations, see Tashakkori and Insko, 1979, 1981). In focusing on perceived balance in work organizations, we are helping to uncover the ways in which people structure the social worlds where careers are established and where much of the business of the modern world is conducted. The current research suggests that if people in organizations perceive unbalanced relations close to themselves, they will act to balance these relations either by changing relationships or by changing cognitions. Further, people tend to perceive friendship relations far from ego as balanced because of increased reliance on the balance schema to organize perception. It is in the middle ground – the area around the minimum – that ego is likely to be troubled by persistent imbalance. In this middle area, ego has no power to act decisively to change relationships, and ego may know too much about the relations of these people on the margins of ego’s world to be able to organize their relations using the principles of balance. Future research, then, could focus on this area around the minimum as the site of ego’s perceived dissatisfactions and opportunities. Ego is likely to be unhappy at work to the extent that he or she perceives relations in the middle distance as unbalanced. However, unbalanced relationships represent structural holes to be bridged (see the discussion in Burt, 1992). To the extent that ego perceives, for example, that groups of individuals who should be communicating with each other are not doing so or are doing so ineffectively, ego may be able to seize the initiative to bridge the gap and bring the people together. As Weick (1995) has emphasized, perceptions have a way of becoming reality. Thus, perceived gaps in communication and friendship patterns may lead to actual movements of people to bridge perceived gaps, irrespective of whether such gaps actually exist. In a striking example of the “grass is greener” effect, people in organizations may perceive more opportunities for entrepreneurial action just outside their own friendship circles. The reproduction and transformation of structure in social systems depend in part on the systemwide effects of the positions (Brass, 1984) and roles (DiMaggio, 1991: 94) occupied by individuals. A sense-making

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perspective emphasizing the perception of relations can help explain how individuals structure the social worlds to which they belong. Individual perceptions of social structure are important because such perceptions shape reputations across internal labor markets (Kilduff and Krackhardt, 1994). The process we have described connects the intimate world of friends and acquaintances with the distant world of relative strangers. The extent to which the perceiver finds that the periphery of the social world resembles the proximate may enable individuals to anticipate familiar patterns of interaction across social boundaries and structural holes. The individual, then, in extending a vision of a balanced world to the relations between comparative strangers, may sustain a logic of confidence that promotes action across social divides. In the next chapter, we tackle the question of accuracy: Given the biases that we have documented, does it help the individual to perceive accurately the friendship and advice relations in an organization? What benefits flow to those who see more clearly the connections among others?

5 Effects of Network Accuracy on Individuals’ Perceived Power

In the previous two chapters, we showed that perceptions of social networks matter and that such perceptions are systematically biased. But some people are more accurate than others in perceiving network patterns. If this is so, do these accurate people gain benefits in organizational arenas of competition and power? This is the theme we investigate in this chapter. We expand the discussion to include perceptions of both friendship and advice networks, and investigate whether an accurate perception of the political landscape – including who are the central players – predicts who has power in the organization. How does one assess the political landscape in an organization? One way of addressing this question is to identify the key political actors in the organization (Pfeffer, 1981). But simply identifying the most powerful actors may not give sufficient information to anticipate the overall dynamics of resistance and support for political acts. Additional questions about these actors come to mind: Are these powerful actors organized such that they tend to act in unison? Do they represent different political constituencies? Precisely whom does each have influence over? Beyond knowing who is powerful, it is useful to know how the powerful and powerless are organized or structured (Bailey, 1969: 108). One way to approach the answers to these deeper questions about the political landscape is to study access to and the control of information flow in the organization (Pettigrew, 1973). As far back as 1965, Hubbell derived both a measure of the power of individual actors and an identification of powerful coalitions, using the actors’ networks of ties. Laumann and Pappi (1976) documented how power accrued to those in central network positions in a community of elites. Brass (1984) discovered that centrality in work-related communication networks was a robust predictor of power in a printing company. As Pfeffer (1981: 130) stated: “Clearly, the power that comes from information control . . . derives largely from one’s position in both the formal and informal communication networks.” 84

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More to the point, the study reported in this chapter suggests that power accrues not only to those who occupy central network positions in organizations but also to those who have an accurate perception of the network in which they are embedded. An individual who has an astute knowledge of where the network links are can have a substantial advantage. First, this information provides a good assessment of who is powerful in the organization, because the central actors in the network can be easily ascertained. Knowing who the central – and powerful – actors are in the organization is essential political knowledge. Second, this information can be used to identify where the coalitions are in an organization. Knowing where the coalitions are, how large they are, and where their support comes from gives one an edge in anticipating resistance and in mobilizing support for action or change. Third, an accurate assessment of the network can also reveal the weaknesses in political groups by exposing holes, gaps, and locations of lack of support for any particular coalition. Thus, understanding the network provides a source of power independent of centrality in the network. The central point in this chapter is precisely that: Cognitive accuracy of the informal network is, in and of itself, a base of power. Both the concepts of power and cognitive accuracy are further developed in this chapter. In addition, we will argue that these two concepts are embedded in a structural context that must be taken into account in any empirical exploration.

Power There has been much disagreement as to the precise meaning of power. Some writers have referred to it as the ability to get things done despite the will and resistance of others, the ability to “win” political fights, or a capacity to outmaneuver the opposition (Bierstadt, 1950; Emerson, 1962). Others (e.g., Kanter, 1979; McClelland, 1975; Roberts, 1986) have stressed the positive sum nature of power, suggesting that it is the raw ability to mobilize resources to accomplish some end (without specific reference to organized opposition). Still others refer to power as the ability to control premises of actions, such that power becomes almost unobservable (Bachrach and Baratz, 1962; Lukes, 1974; Mizruchi, 1983). Salancik and Pfeffer (1977) preferred to ignore these distinctions, noting that, while academics may quibble over the definition of power, those actually experiencing the effects of power in the real world seem to exhibit a consensus as to who has it. Without fully resolving this debate, it is reasonable to assume that the answer to the question of who has power depends in part on an

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answer to the question, Power to do what? If the influence being sought is within the routine operation of the organization, then people who are “experts,” people in “authority,” and, generally, people who know how things work around the organization are likely to be seen as powerful. If, however, the influence entails a radical departure from prior operations, then the uncertainty that emerges is likely to arouse emotional responses to influence attempts. Affect-laden issues such as trust, respect, or liking may become important in evaluating who has the ability to mobilize support for the radical change (Chapter 10; Krackhardt and Stern, 1988). In such cases, the powerful person may be someone who has referent power (French and Raven, 1959) or charisma (Bradley, 1987; Fiedler and House, 1988; House, 1977) in the organization rather than someone who simply has authority or expertise. We included multiple kinds of power in this study (as recommended by Pfeffer, 1981). The assumption is that some actors are powerful because they are acknowledged as adept at getting things done in the organization, despite some resistance (e.g., Brass, 1984) and that some actors are influential because of an ascribed individual trait that reflects intangible qualities of trust and personal charm. These two different assessments of power are offered as ones that actors will readily recognize as influence bases in organizations: the ability to get things done in spite of resistance and the ability to influence people through personal appeal and magnetism (which is termed charisma).

Cognitive Social Structure and Accuracy The current study was motivated by the question, How closely does each person’s perception of the network approximate the “actual” network and how does this relate to power? To address this question, two types of aggregations were employed: The set of N individual perceived maps of the whole network, called “slices,” of Ri,j,k ; and the “actual” network, as defined by the two people actually involved in the relationship, referred to as the locally aggregated structure, or LAS (Krackhardt, 1987a). Just as power itself is a multidimensional concept, network relationships may be assessed on several dimensions. But the specific question is, What network relations are critical for the assessment of power? For example, a network composed of incidental communication links, such as perfunctory “hello’s,” may not be as rich in power information as a network composed of critical advice relationships. The study reported here was based on the cognitive social structures for two different types of networks that have been shown to be useful in understanding the

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dynamics of informal organizations (e.g., Brass, 1984; Burt, 1982: 25; Krackhardt and Porter, 1985, 1986; Lincoln and Miller, 1979). First, the advice network (who goes to whom for work-related advice) represents the instrumental, workflow-based network in the organization. The second network assessed was the friendship network, or what Lincoln and Miller (1979: 186) called the “primary network,” which we have focused on in the previous three chapters. The friendship network captures important affective and social bonds that can affect trust, especially in times of change (Chapter 10; Krackhardt and Stern, 1988).

Structural Influences In pursuing issues of power, one cannot ignore critical contextual and structural factors that also operate to give certain actors privilege and power in an organization. Brass (1984) found that centrality in the informal network itself predicts power. But centrality also has important theoretical links to cognition (see Krackhardt, 1987a, for a comparison of different types of centrality). A series of studies has found that central involvement in a social system increases one’s ability to “see” the social system accurately (Freeman and Romney, 1987; Freeman et al., 1987). Freeman, Freeman, and Michaelson (1988) noted that “social intelligence,” the ability to discern social groups and boundaries, evolves over time as participants gain experience in the social group. Freeman and Romney (1987) demonstrated that people’s ability to recall social structure accurately was a function of whether they were members of the core group or were peripheral, transitory members. These results, combined with Brass’s (1984) findings, suggest that centrality in the informal structure can lead to both cognitive accuracy and power. Another structural power base that cannot be ignored is the formal position that a person holds in the organization. Clearly, those with more authority will have more power, on the average, than those with less authority. In addition, those higher in the organizational chart are responsible for a larger part of the organization. A first-line supervisor is responsible for the activities of his or her immediate subordinates. A manager of several supervisors is responsible for these supervisors and ultimately for the activities of all their subordinates. People’s positions require them to pay attention to the way in which those under them work together and relate to each other. Thus, those higher up in the organization will have, by virtue of their position, a better opportunity to observe and take note of a larger part of the informal network. Consequently, they are likely to have a more accurate picture of the informal network.

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STRUCTURE

COGNITION

POWER

Formal Power

Cognitive Accuracy

Reputational Power

Informal Network Centrality Figure 5.1. Model relating structure, cognition. and power.

This should be particularly true in a small, entrepreneurial firm, where the owners-managers are known to be heavily involved in the details and day-to-day workings of the entire organization. Those higher in the formal organization are forced to relate to a wider base of people. A first-line supervisor must coordinate the activities of a limited number of people, all of whom are likely to interact informally with each other and be doing similar work. A top-level manager must coordinate the activities of supervisors and managers from different functions and sectors of the organization. This responsibility gives higher-level managers more central positions in the formal organization, in that they will find themselves dealing with more issues that surface between departments or groups. This formal role is likely, in turn, to lead to opportunities to be in the middle of the informal network, acting as a bridge between groups of employees. Therefore, it is expected that formal hierarchical level will also contribute to network centrality. There are thus both structural and cognitive power bases in an organization. Although it is proposed here that cognitive accuracy is a power base in and of itself, one must take into account the fact that this cognitive power base is influenced by formal and informal structural factors. Because these structural factors are sources of power in their own right, these sources are explicitly included as part of the cognitive model of power presented here. Figure 5.1 displays this model, which relates structure, cognition, and power. Formal structure is shown as an exogenous variable leading directly to informal structure, cognitive accuracy, and power. Informal structure, in turn, contributes to cognitive accuracy and power. Finally, in accordance with the central theme of this chapter, cognitive accuracy

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is predicted to contribute to power over and above the power already explained by the structural factors. This last link represents the main proposition of this chapter: Proposition: Controlling for formal and informal bases of power, cognitive accuracy of the informal network will be correlated with individual power in the organization. To test the model in Figure 5.1 and the proposition posed above, a network study was conducted of a small high-tech firm. Questionnaire and interview data were collected from which the cognitive social structures and “actual” networks were determined, and each employee provided assessments of how powerful and charismatic every employee was in the organization. From these data, the central proposition and model were tested directly.

Method The company studied and the sample were identical to that studied in Chapter 3: thirty-six members of the high-tech company Silicon Systems, of whom thirty-three filled out our questionnaire. Reputational Power Previous work (Brass, 1984) established internal consistency and predictive validity for a reputational measure derived from ratings of supervisors and peers. Building on this previous work, we asked each employee to rate all the employees (including himself or herself) on the two dimensions of power: the ability to get things done despite resistance and the ability to influence through personal magnetism (charisma). This procedure avoided the problem of availability bias, incomparable sources, and dichotomization. Moreover, with this multiple-source method, the internal reliability of the two power scores can be estimated. Each person rated each other person on a seven-point Likert scale on both charisma and the ability to get things done (potency). Two anchors were provided for each scale: “Not at all charismatic” to “Highly charismatic” for charisma, and “Not at all powerful” to “Highly powerful” for potency. To assess the reliability of the two measures, Cronbach’s alpha was calculated for charisma and potency (for the formula, see Carmines and Zeller, 1979: 44). Both charisma and potency had high reliability coefficients (Cronbach’s alpha = .96 and .99, respectively), demonstrating that there was very high consensus in the organization on who was

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influential on each of these dimensions. The correlation between the two power indicators was .63, indicating considerable overlap between the two measures. For this reason, the two measures were combined into a single dependent variable, overall power, using the factor scores from the first component of a principal components analysis of the two variables. Formal Position Although power derived from formal position may be ambiguous in some larger organizations, this organizational base of power was quite clear in Silicon Systems. There were three distinct levels of formal authority. At the top level were the three owner-managers. Even though they took on different responsibilities and had different titles, they were equal partners and made all major company decisions jointly. The next level consisted of five managers, each of whom had supervisory responsibility over certain operational features in the organization. The remaining twenty-eight employees had no formal supervisory title or authority. Formal position, then, was scored as follows: Each of the three owners was given a formal position score of 3; the five managers were given a formal position score of 2; and the remaining twenty-eight employees were given a formal position score of 1. Cognitive Social Structure The cognitive social structure is a three-dimensional array of linkages, Ri,j,k , among a set of N actors, where i is the sender of the relation, j is the receiver of the relation, and k is the perceiver of the relation. Using Krackhardt’s (1987a) methodology, a questionnaire was designed to assess the cognitive social structure of two relations in the organization: friendship and advice (see Chapter 3 for more details). Actual Network Although work in the area of recall of network relations has cast doubt on an informant’s ability to relate accurately to whom they actually talk on any given day (see Bernard, Killworth, Kronenfeld, and Sailer, 1984, for a review), Freeman et al. (1987) have shown that people are remarkably good at recounting enduring patterns of relations that they have with others. Thus, although people may not remember whom they talked to today or this week, they can accurately tell you whom they are in the habit of relating to over an extended period of time. Consistent with these results, Brass (1984) found that the workflow network in his study closely corresponded to the network reported by respondents. Because it

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is these enduring relational patterns that are of interest – as evidenced by the wording in the questions – the locally aggregated structure, or LAS (Krackhardt, 1987a), was used as a proxy for the “actual” network. The LAS is an aggregation defined by the local participants in the network. It mimics the typical form in which network data are collected. (See Chapter 3 for technical details.) Both i and j must agree that i goes to j for help and advice before the i → j link is recorded as existing in the “actual” advice network. Similarly, both i and j must agree that i considers j a friend before the i → j link is recorded as existing in the “actual” friendship network. Because the relationship is defined as existing when both parties agree that it exists, this measure of the “actual” network is direct and has obvious face validity. In the case of Silicon Systems, data were missing for three of the thirty-six employees, so we adopted the following procedure to deal with these cases. If information concerning a link between two people was missing from one but not both parties, then the existence or nonexistence of a link is determined by the information provided by the reporting party. If information was missing from both parties, then a link was deemed to exist if five or more people in the network reported that it existed. Cognitive Accuracy Each participant’s cognitive map of the network (representing each participant’s “perceived network”) was taken from the set of responses that he or she selected on the network questionnaire. We then correlated cognitive maps of the network with the actual network to derive a measure of accuracy between perceived and actual networks for each participant. The measure that we used was the point correlation coefficient and is equal to the value obtained by computing a Pearson correlation coefficient between the elements of the matrix representing each participant’s cognition of the network and the elements of the matrix representing the “actual” network. (See Gower and Legendre, 1986, for a review of correspondence measures.) Centrality Of the many different ways to measure of centrality, betweenness is the one most closely aligned with the idea of power (see Freeman, 1979, for the formula). The individual who is in between other actors has more control over information flow from one sector of the network to another. That person becomes a gatekeeper of information flow. Moreover, betweenness is an indication of the nonredundancy of the source of

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Mean

Standard Deviation

Power Advice accuracy Friend accuracy Advice centrality Friend centrality Formal position

0 .406 .326 14.443 17.014 1.333

1.00 .0624 .0704 27.3039 25.1941 .6454

Correlation Structure Variable

Power

1

2

3

4

1. Advice accuracy 2. Friend accuracy 3. Advice centrality 4. Friend centrality 5. Formal position

.340∗ .146 .453∗∗ .506∗∗ .656∗∗∗

.282∗ .210 .172 .240

.031 .236 .041

.222 .566∗∗∗

.161

∗

p < .05. p < .01. ∗∗∗ p < .001. ∗∗

information. To the extent that a person is connected to different parts of the network and therefore has access to different, nonredundant sources of information, that person will have a wider variety of information at his or her disposal. The higher the betweenness score of an actor, the greater the extent to which the actor serves as a conduit connecting others in the network. Formally, betweenness centrality measures the frequency with which an actor falls between other pairs of actors on the shortest or geodesic paths connecting them (Freeman, 1979: 221). Measures of betweenness centrality are difficult to interpret for nonsymmetric data. In preparing the matrices prior to the calculation of betweenness centrality, the networks were symmetrized according to the rule that if either member of a pair nominated the other, the pair was considered to have a tie – reflecting the assumption that the presence of even an asymmetric relationship represented an opportunity for exchange of information in both directions.

Results The means, standard deviations, and intercorrelations among all the variables used in this study are presented in Table 5.1. To test more completely the model in Figure 5.1, a set of hierarchical regressions was performed on the dependent variable, overall power. The

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Table 5.2. Hierarchical Regression Analysis of Reduced-Form Equations with Reputational Power as Dependent Variablea Equation Independent Variables

(1)

Formal position Advice centrality Friend centrality Advice accuracy Friend accuracy R2

1.107∗∗∗ (.210)

Hierarchical Test of Model R2 F df p

.431

(2) .879∗∗∗ (.222) .0015 (.005) .161∗∗∗ (.0048)

.597 .166 5.966 2,29 .007

(3) .782∗∗∗ −.0004 .0195∗∗∗ 5.091∗∗ −.559 .678

(.210) (.005) (.0049) (2.02) (1.74)

.082 3.425 2,27 .047

a

Standard errors are in parentheses. p < .05 ∗∗ p < .01 ∗∗∗ p < .001. ∗

results are presented in Table 5.2 as reduced-form equations (Cohen and Cohen, 1983: 361–6). Formal position explains 43 percent of the variance in overall power. The two informal structure sources of power, centrality in the advice and friendship networks, add another 17 percent of explained variance (significant at the .007 level). Note, however, that advice centrality is not significant in the equation; only centrality in the friendship network is significantly related to power when controlling for formal position (rho < .01). It appears, then, that any advantage that a person has by being central in the routine advice network is attributable to his or her formal position of power in the organization. In equation 3 of Table 5.2, cognitive accuracy in the advice and friendship networks explains an additional 8.2 percent variance (p