Rider (2012). How Employees’ Prior Affiliations Constrain Organizational Network Change: A Study of U.S. Venture Capital and Private Equity

Christopher I. Rider – Georgetown University, McDonough School of Business

Daniela Lubatti – IESE Business School
Paola Zappa – University of Lugano

Article link: http://asq.sagepub.com/content/57/3/453

Question 1. The fascinating view on the formation of new organizational relationship in your paper enables to understand not only how networks form, but also how they evolve over time. Nevertheless, an important aspect of a relationship is that it might be terminated. According to the theory you built in your paper, how would you explain the ending of a relationship between organizations? And how does it affect organizational positions in the network?

Agreed. Relationship formation is more often studied and, therefore, understood better than termination. The 2012 paper provides some insights on how shared prior affiliations shape information asymmetry between two organizations but – for at least two reasons – not a clear prediction.
First, with respect to relationship formation, the 2012 study addressed ex ante information asymmetry but, presumably, ex post asymmetry would influence termination. If organizational members’ shared prior affiliations alleviate only ex ante asymmetry then I don’t think we should expect a correlation between shared affiliations and termination. But, if shared affiliations also facilitate some ex post information-sharing then we might expect a negative relationship between shared affiliations and termination. I lean towards the latter possibility, which raises another consideration.

Second, two organizations that shared many affiliations among their members at time of relationship formation might share no affiliations in later time periods as members exit both organizations. So we face a classic person-group duality puzzle: are inter-organizational relationships owned by organizations or their members? We must answer that question to address the implications for ex post information asymmetry.

If relationships are more inter-personal than inter-organizational and two organizations’ shared affiliations decrease, then asymmetry should increase and the hazard of termination probably increases. But, if relationships are more inter-organizational than inter-personal, then we shouldn’t necessarily expect the hazard of termination to be affected. Of course, this logic applies if members exit exogenously. Otherwise, expected termination might cause some members to depart (e.g., “I created this alliance and now we’re ending it.”) and expected formation might cause others to join (e.g., “She was hired to lead that partnership.).
You’ve asked a question that is very difficult to answer but also clearly worth answering. As you imply, the distribution of shared affiliations across network nodes should be systematically related to nodal positions. I’d be pleased if someone took up this research inquiry…

Question 2. Moving toward a more micro-level, you argue that organizations are more likely to hire individuals that had the same educational and professional background of their current employees. Since you suggest that this occurs recursively, hiring individuals with similar educational and professional background is not unlikely to cause some redundancy in the organizational stock of knowledge. Would you expect this hiring strategy to affect organizational performances? If so, do you think that this strategy would be detrimental for peripheral organizations only or would somehow affect also organizations occupying central network positions?

Fascinating question. There are two comparisons to consider here before addressing the central vs. periphery comparison. First, do organizations that embed employment relationships in members’ prior affiliation networks out-perform organizations that do not do so or don’t do so as much (i.e., the between-organization comparison)? Second, will a focal organization enhance its performance by embedding relationships in employees’ prior affiliation networks (i.e., the within-organization comparison)?

The second question seems easier to answer. If one believes that embedding employment relationships in prior affiliation networks is common (I do) and also believes that if this practice is performance-diminishing then it would not be so common (I do) then, on average, an organization is better off doing so than not. This logic implies the same answer for the first question but you raise an interesting possibility – performance benefits of embedding employment in members’ prior affiliations might vary with an organization’s network position. So, the between-organization comparison is more complex.

I suspect that network position (i.e., central versus peripheral) matters most when organizations face strong countervailing individual preferences for working with affiliated others. Consider two scenarios in which “affiliation redundancy” might result from person-organization matching. First, organizations are indifferent but individuals prefer to work with their affiliates so that organizational preferences are constrained by individual ones. Second, individuals are indifferent but organizations prefer to hire employees’ affiliates so that individual preferences constrain organizational ones.

David Tan and I argue in a paper that individuals consider organizational status a nonpecuniary employment benefit and network centrality is a proxy for high status. If organizations prefer to hire employees’ affiliates and individuals are indifferent (scenario #2 above), then we might expect peripheral organizations to realize less beneficial employee matches than higher status competitors do. In this scenario, we’d expect all organizations to perform better by embedding employment in affiliations but the benefits to accrue largely to more central organizations. In contrast, if organizations are indifferent to the embedding practice then we wouldn’t necessarily expect performance to vary with organizational network positions.

Again, a fascinating question and one I’d like to see others answer – especially in a setting that offers better insights into the people-organization matching process than my data do.

Question 3. In your article, hiring individuals is considered one of the strategies to improve organizations’ positions as a way to overcome information asymmetry. In your opinion, do the positions of the individuals inside the prior organizations affect their ability to improve their current organizations’ positions? In other words, individuals that were peripheral in the information network inside their previous organizations might not be as effective in enabling their current organizations to create new relationships and strengthen their positions as more central individuals.

Yes, we agree on the logic. Several nice studies support your “hierarchical heterogeneity” argument (e.g., Phillip 2001 AJS; Rosenkopf, Metiu & George 2001 ASQ; Broschak 2004 ASQ; Dokko & Rosenkopf, 2010 OS; Bermiss & Murmann 2015 SMJ paper). This would make for a nice study and especially if one could tease out the direction of causality: does hiring cause positional improvement or do expectations of positional improvement cause hiring?
For example, Nobel Prize winner George Akerlof joined Georgetown University’s faculty in 2014. I’m certain that hiring someone so central to the economics field enhanced my employer’s competitive position in the academic labor market (much, much, much more so than peripheral me joining the Georgetown faculty in the same year). I also recognize that a $100M naming gift for the McCourt School of Public Policy made it possible for Georgetown to hire him (and is completely unrelated to my employment). In this example, we find details consistent with your intuitions about hierarchical heterogeneity and also my concerns about causality. It would be great if someone cleverer than me found a way to isolate the hiring effect from the expected improvement effect.

Question 4. One aspect that makes your study so interesting is that it emphasizes the multilevel nature of organizational networks. By making explicit – for instance – the constraint that interpersonal employment relations can exert on inter-organizational co-investment relations, your paper seems to show the greater deal of information that is made available by accounting for the interdependences between the micro- and meso-levels of analysis. In your opinion, how important is adopting such multilevel perspective in studying networks within organizations? Which kind of organizational issues could benefit from such a perspective?

Thank you for your kind words. My training in Organizational Behavior & Industrial Relations at UC Berkeley’s Haas School of Business instilled in me the view that all organizational issues are multilevel issues. I was heavily influenced by not only my advisors John Freeman and Heather Haveman, but also micro scholars like Jenny Chatman and Barry Staw, who all theorize about people and organizations and bridge levels of analysis in their work. So, I don’t think it occurred to me to study inter-organizational networks in a way that was not multilevel. I also benefited greatly from detailed and thoughtful guidance from ASQ Associate Editor Phil Anderson, who kindly but forcefully pointed out that the multilevel nature of this study should become a defining feature.

In my view, the study of inter-organizational and intra-organizational networks would benefit greatly from focusing on how individual and organizational network positions are occupied. This focus would include explicit study of how individuals’ prior experiences and affiliations influence (1) their initial positions within organizations and (2) their organizations’ positions within industries and markets. Network positions are not randomly assigned but the process is not a complete mystery to organizational scholars either – we often expect that some people and their organizations to become central than others (e.g., old boys’ clubs). Systematically studying these positional determinants will enable organizational researchers to make stronger causal claims in networks studies. And those who take on this challenge will soon provide much better answers than I’ve provided to your questions.

Question 5. Your paper uses a unique and extensive dataset, which seems to lend itself well to address a variety of research questions. What advice would you give to young scholars in order to select an empirical setting and consequently build a dataset that could be used in a multi-year empirical research project?

First, assemble a small army of research assistants to help you hand-collect the data. I will be forever grateful to the many UC Berkeley undergraduates who helped me collect this dataset. Do not try to take on a data collection project of this scale on your own.

Second, identify multiple research questions that fit under a broader theme, third, use overlapping data.

My 2009 and 2012 ASQ papers were both dissertation chapters; one examined venture capital fundraising and the other venture capital employment and investing. I began collecting the data set for the 2012 paper and realized (John Freeman “gently” reminded me) that my doctoral funding would run out before I finished. But, the 2009 paper only required the control variables for the 2012 paper. So the 2009 paper became my job market paper, which I wrote while RAs finished data collection. This was possible because the two studies were so closely related in terms of theme (i.e., network positions and processes) and setting (i.e., venture capital).

I definitely didn’t figure this out on my own — I had great advising at Berkeley. But, I continue to apply this “broad theme/overlapping data” approach in my studies of personnel matters in the legal services industry with Adina Sterling and David Tan. Oh, that reminds me…fourth, work with great co-authors who are smarter than you but kind enough to not remind you too often of that fact.

Thanks so much for your interest in my study and for asking such thought-provoking questions. I really enjoyed the opportunity to revisit this study!

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