Ajay Mehra

Network Analysis in the Social Sciences

Over the past decade, there has been an explosion of interest in network research across the physical and social sciences. For social scientists, the theory of networks has been a gold mine, yielding explanations for social phenomena in a wide variety of disciplines from psychology to economics. Here, we review the kinds of things that social scientists have tried to explain using social network analysis and provide a nutshell description of the basic assumptions, goals, and explanatory mechanisms prevalent in the field. We hope to contribute to a dialogue among researchers from across the physical and social sciences who share a common interest in understanding the antecedents and consequences of network phenomena.

Network Churn: The Effects of Self-Monitoring Personality on Brokerage Dynamics

The apparent stability of social network structures may mask considerable change and adjustment in the ties that make up the structures. In this study, we theorize and test—using longitudinal data on friendship relations from a radiology department located in the Netherlands—the idea that the characteristics of this “network churn” and the resultant brokerage dynamics are traceable to individual differences in self-monitoring personality. High self-monitors were more likely than low self-monitors to attract new friends and to occupy new bridging positions over time. In comparison to low self-monitors, the new friends that high self-monitors attracted tended to be relative strangers, in the sense that they were unconnected with previous friends, came from different functions, and more efficiently increased the number of structural holes in the resultant network. Our study suggests that dispositional forces help shape the dynamic structuring of networks: individuals help (re)create the social network structures they inhabit.

The Price Chameleons Pay: Self-monitoring, Boundary Spanning and Role Conflict in the Workplace*

The vast majority of research on self-monitoring in the workplace focuses on the benefits that accrue to chameleon-like high self-monitors (relative to true-to-themselves low self-monitors). In this study, we depart from the mainstream by focusing on a potential liability of being a high self-monitor: high levels of experienced role conflict. We hypothesize that high self-monitors tend to choose work situations that, although consistent with the expression of their characteristic personality, inherently involve greater role conflict (i.e. competing role expectations from different role senders). Data collected from a 116-member high-tech firm showed support for this mediation hypothesis: relative to low self-monitors, high self-monitors tended to experience greater role conflict in work organizations because high self-monitors were more likely to occupy boundary spanning positions. To help draw a more realistic and balanced portrait of self-monitoring in the workplace, we call for more theoretically grounded research on the price chameleons pay.

The Transformative Power of Network Dynamics: A Research Agenda

The emergence and proliferation of network forms of organization has sparked interest and debate in organization studies. We have learned much about the effects of networks but our understanding of how they are formed, how they change, and how networks can themselves possess agential properties that make them complex social actants is limited. In selecting papers for this special issue, we were persuaded by arguments that our understanding of networks and their transformative power can benefit from greater attention to culture and discourse, which provide meaning and direction to network participants and are indispensable agentic resources. The special issue contains two sets of papers. The first set debates the articulation between the organized and emergent dynamics of networks and its impact on knowledge exchanges and innovation. The second set seeks to inform our understanding of the manifestations of power in network dynamics. For each section, we provide a tentative research agenda. Our hope is that this special issue will both advance our ability to conceptualize, measure and manage network evolution and enhance our understanding of the transformative impact of network dynamics on organizations and society.

Imaginary Worlds: Using Visual Network Scales to Capture Perceptions of Social Networks

Abstract Social networks are not just patterns of interaction and sentiment in the real world; they are also cognitive (re)constructions of social relations, some real, some imagined. Focusing on networks as mental entities, our essay describes a new method that relies on stylized network images to gather quantitative data on how people “see” specific aspects of their social worlds. We discuss the logic of our approach, present several examples of “visual network scales,” discuss some preliminary findings, and identify some of the problems and prospects in this nascent line of work on the phenomenology of social networks.

Brokering Trust to Enhance Leadership: A Self-Monitoring Approach to Leadership Emergence

What kind of person is likely to emerge as an informal leader in the workplace? Experimental research shows that high self-monitors—who tend to adjust their attitudes and behaviors to the demands of different situations—emerge as informal leaders in temporary groups. By contrast, low self-monitors—who tend to be true to themselves in terms of consistency in attitudes and behaviors across different situations—are less likely to emerge as leaders. But this prior research does not address the criticism that the emergence of high self-monitors as leaders represents ephemeral impression management in the context of laboratory experiments. To address this issue, we collected and analyzed data from a 116-member high-technology firm. Our results show that self-monitoring is related not only to leadership emergence, but also to the provision of advice to co-workers. Further, people who occupied brokerage positions (being trusted by those who did not trust each other) tended to be seen as leaders if they were high rather than low self-monitors. From these results, we build a picture of the high self-monitoring emergent leader as someone who notices problems and ameliorates them through the provision of advice and the brokerage of relationships across social divides. The occupation of a structurally advantageous position may well be more advantageous for some (i.e., high self-monitors) relative to others (i.e., low self-monitors).

A Network Perspective on Mega-Engineering Projects

The use of network theory and methods to explain and predict outcomes related to complex systems is on the rise across a range of sciences, from physics and biology to sociology and psychology. Indeed, the applicability of network ideas across seemingly disparate systems is one of the most distinctive and promising features. Network theory represents systems in terms of nodes (which can be molecules, individual persons, companies, nation states, etc.) and the set of ties or relations that bind the nodes into a complex whole. Using graph-theoretic tools, network research can then be used to represent and analyze the topography of the resulting network, and to examine the consequences of this topology both for individual nodes and for the system as a whole. The purposes of our essay are twofold. First, we seek to provide an introduction to network research and methods. Second, we wish to sensitive researchers to the promise of a network perspective for understanding the structure and consequences of megaengineering projects.