ZHELYAZKOV (2017). INTERACTIONS AND INTERESTS: COLLABORATION OUTCOMES, COMPETITIVE CONCERNS, AND THE LIMITS TO TRIADIC CLOSURE

Author:

Pavel Zhelyazkov – Hong Kong University of Science and Technology

Interviewers:

Heli Helanummi-Cole – University of Oxford

Patrizia Vecchi – Washington University in St. Louis

Article link: http://journals.sagepub.com/doi/abs/10.1177/0001839217703935

Question 1. Your study shows that an intermediary is unlikely to facilitate a connection between a partner and a highly attractive competitor for fear of being substituted. Less attractive competitors do not pose a threat, so are more likely to be introduced and form ties with common third parties.

Do you have any insights about how your findings at the triadic level may translate at the level of the whole network structure? Should we expect to see the formation of separate clusters around the best-performing actors?

Although the paper focuses on micro-level processes, one can certainly draw out macro-implications from the findings. Of course, there is one important caveat. When we talk of networks, we typically think of horizontal networks, that is, the nodes play similar roles; for example, all venture capital (VC) firms or all investment banks. By contrast, my study looks at how a horizontal network, that is, VC syndication, shapes a vertical network between the Limited Partner (LPs) and the VC firms in which they invest. Very few studies have examined such multilevel networks (Shipilov and Li, 2012, who investigate the interaction of the horizontal network between investment banks and the vertical network between investment banks and issuers, is a rare example of such study). As I noted in the paper’s closing, it is an open question how well the insights of such a setting translate to traditional horizontal networks. So, assuming all the insights transfer to traditional networks, what do they imply about global horizontal network structures?

The first macro implication relates to relationship performance as a hidden source of disturbance in the cohesion of a network. Conventional theory presumes that a company’s relationships radiate out of its initial core of exchange partners, which provide introductions and referrals to their own partners. In a way, you can visualize every exchange relationship as a branch that can lead to other relationships. From that perspective, the first insight of the paper is that certain branches are likely to wither for performance reasons. The idea of how different disturbances in relationships can burn bridges and thus have long-term implications on network evolution has animated me for a long time. In fact, it was a major motivation behind one of the papers from my dissertation (later published in AMJ), which explored how VC firms’ decision to withdraw from syndicates can similarly preclude them from syndicating with partners of the abandoned co-investor (Zhelyazkov and Gulati, 2016).

Going beyond performance outcomes, the second macro implication from the study is that connections to higher-reputation actors are more likely to lead to ties with more of their partners, creating the denser clusters that you anticipate; this is certainly a testable hypothesis that can be tackled by future research. Last but not least, the third macro implication stems from the finding that actors are more willing to facilitate connections for dissimilar others. This is important because dissimilar collaborators often can be associated with different network clusters. Typically, prior research has attributed the instability of structural holes that span different clusters to the preference of actors to cut out the middleman and access the heterogeneous knowledge available in other clusters themselves (e.g., Buskens and van de Rijt, 2008; Gulati, Sytch, and Tatarynowicz, 2012). The intermediary’s diminished competitive concerns about dissimilar others, however, can increase its willingness to introduce them to its own partners within its cluster and thus serve as an alternative mechanism behind the instability of structural holes.

Question 2. You found that LPs were more likely to invest in VCs that had a lower reputation than the intermediary VCs in which they had already invested. You interpreted this finding as due to VCs’ reluctance to provide referrals for competitors with a higher reputation. Does this mean that VCs provided inaccurate referrals or that they were able to maintain some secrecy about their relationships with other VCs? Could ‘secrecy’ be a boundary condition of your theory?

I definitely think secrecy plays a role—the industry is known as “Private Equity” for a reason—although the secrecy operates not as much at the level of who is transacting with whom, but what happens in the course of the interactions. Investments are made in privately-held companies, whose ongoing performance is opaque and the reasons for their eventual successes and failures are even murkier. This makes it possible for VCs to present their own stories as to what happens behind closed boardroom doors and who can take credit for the successes and blamed for the failures.

A second level of secrecy that is even more important is the opaqueness of who is saying what about whom. Most commentary about other VCs given during LPs’ due diligence process is given under strict confidence. Although a VC may observe the ultimate outcome, that is, an LP refuses to make an investment, it generally has very little insight into the reasons for that decision. Was there any negative information that swayed the LP’s decision? If there was negative information, which of its partners may have possibly supplied it? The flipside of such secrecy is that a VC firm can pass distorted or selective information about a certain partner to its LPs and not necessarily risk spoiling the collaborative relationship. Obviously, the dynamics would completely change if such references were public!

Question 3. You discuss the interviews you conducted as part of the research project briefly in the paper, mainly to describe the fundraising process. How did the qualitative data influence the overall development of your study?

The qualitative research was quite important for three reasons. First, it stimulated my interest in the subject. Keep in mind that the earliest conversations occurred in the aftermath of the 2008 financial crisis. As I heard from VCs about how challenging fundraising can be and from LPs about the importance of soft information collected during the due diligence process, I was convinced that the phenomenon was substantively important and that social networks play a significant role. It also gave me important background information, such as what other factors play a role in the LP decision-making process and therefore should be included as controls.

Second, when I started thinking about the potential implications of competitive concerns, one of the interviewees directed me to a critical analogy—the Moskowitz (1952) portfolio selection model, which implied that both expected performance and correlations should figure in the LP’s selection process. This inspired me to think about relative attractiveness, that is, the stand-in for expected performance, versus replaceability, that is, the extent to which one VC can replace another with minimum impact on the diversification level of the overall LP portfolio.

Third, the interviews were very helpful after the initial rounds of data analysis. After I had more quantitative results, the role of the qualitative interviews changed. I emphasized to a much greater extent getting the respondents’ reactions and interpretations of the results, as well as feedback of my emerging explanations.

Question 4. Research projects seldom progress in a linear fashion. Did you experience a significant ‘a-ha’-moment at which point the pieces of the puzzle started to fall into place? If so, what triggered this?

My initial motivation for collecting the data was to understand how indirect ties via different channels—LP-mediated and VC-mediated ties—affect the likelihood of forming vertical relationships between VCs and LPs. I was also exploring how different features of the VCs and the LPs, such as centrality, reputation and experience moderate this process. To my knowledge, this was the first project that considered the network influences on the investment decisions of LPs, so there was a lot of open space to consider.

The first breakthrough in my thinking, which also heavily affected the future AMJ paper I mentioned earlier (those two papers proceeded on fairly parallel timelines), was the idea that network tie heterogeneities may change the effect of ties. Several papers that came out around that time (Baum, McEvily, and Rowley, 2012; McEvily, Jaffee, and Tortoriello, 2012; Greve, Mitsuhashi, and Baum, 2013) were all influential in directing my attention to the importance of tie heterogeneity. I would especially credit Greve, Mitsuhashi, and Baum (2013) for inspiring the analytical technique I used in both papers: separating counts of different types of ties as different variables in the same regression rather than using conventional interaction terms.

I initially zeroed in on the triadic implications of dyadic performance outcomes and the corresponding boundary conditions. The initial ASQ reviews were encouraging, but raised a critical issue: what are the incentives for VCs to recommend any of their partners to their LPs? This simple question inspired what I consider the second critical a-ha moment and encouraged me to think about the competitive concerns part of the puzzle. I then used some of those questions in my later qualitative interviews, which directed me to the importance of relative attractiveness and replaceability as critical concerns.

All told, my paper was completely transformed in the course of the peer review. In the end, the network implications of performance outcomes were reduced to a single hypothesis, even though they constituted the core of the earlier version. Instead, the competitive concerns, which were completely absent from the initial draft, became the conceptual heart of the paper. Such a dramatic evolution in the course of the review process may be atypical, but was instructive. It is critical to keep an open mind and make the most of critical feedback, even if it seemingly takes the paper in directions you have not previously anticipated.

References:

Baum, J. A. C., B. McEvily, and T. J. Rowley 2012 “Better with age? Tie longevity and the performance implications of bridging and closure.” Organization Science, 23: 529-546.

Buskens, V., and A. van de Rijt 2008 “Dynamics of Networks if Everyone Strives for Structural Holes.” American Journal of Sociology, 114: 371-407.

Greve, H. R., H. Mitsuhashi, and J. A. C. Baum 2013 “Greener pastures: Outside options and strategic alliance withdrawal.” Organization Science, 24: 79-98.

Gulati, R., M. Sytch, and A. Tatarynowicz 2012 “The rise and fall of small worlds: Exploring the dynamics of social structure.” Organization Science, 23: 449-471.

McEvily, B., J. Jaffee, and M. Tortoriello 2012 “Not all bridging ties are equal: Network imprinting and firm growth in the Nashville legal industry, 1933-1978.” Organization Science, 23: 547-563.

Moskowitz, H. M. 1952 “Portfolio selection.” Journal of Finance, 7: 77–91.

Shipilov, A. V., and S. X. Li 2012 “The missing link: The effect of customers on the formation of relationships among producers in multiplex triads.” Organization Science, 23: 472-491.

Zhelyazkov, P. I., and R. Gulati 2016 “After the break up: The relational and reputational consequences of withdrawals from venture capital syndicates.” Academy of Management Journal, 59: 277-301.

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