Authors:
Rekha Krishnan – Simon Fraser University, Department of International Business / Innovation and Entrepreneurship
Karen Cook – Stanford University, Department of Sociology
Rajiv Krishnan Kozhikode – Simon Fraser University, Department of International Business / Management and Organization Studies
Oliver Schilke – University of Arizona, Department of Management and Organizations

Interviewers:
Matthew Sutter – Iowa State University, Department of Management and Entrepreneurship
Huiqing Ju – Iowa State University, Department of Management and Entrepreneurship

Article link: https://journals.sagepub.com/doi/full/10.1177/0001839220970936

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1. What can practitioners and accelerators take away from this insightful work? 

Dr. Krishnan: Start-up ecosystems, such as Silicon Valley, are inherently mixed motive contexts. Despite being portrayed as strategic actors who engage in instrumental networking, entrepreneurs in the beginning stages of their venture are often lonely and in need of social support. The Silicon Valley networking landscape reflects this too. On the one hand, there are meet-ups that help entrepreneurs form resource rich ties and are geared toward instrumental networking. On the other hand, there are social support meetups that encourage entrepreneurs to talk about their struggles with other entrepreneurs. I have seen the tension between cooperation and competition come alive in accelerators. Often the mission statements of accelerators state, “We give first before we ask,” but entrepreneurs are asked to give without expectations in an environment where they compete for funding, mentorship, and clients. How can you foster collaboration and support in an environment like this?

It is important to note that accelerators are becoming such a key part of the entrepreneurial ecosystem that the social environment they foster might also influence the start-up ecosystem outside since entrepreneurs from these accelerators eventually go out into the real world. The bigger question then becomes one of whether accelerators contribute to a competitive start-up ecosystem, or do they give rise to an Anna Lee Saxenian world where entrepreneurs learn to help each other despite the competition? We find that tournament-like rituals that compare entrepreneurs on their weekly progress and promote an instrumental networking mindset hinder community building. What do entrepreneurs take away from weekly progress meetings? Does an entrepreneur walk out of these meetings wondering how I can get ahead of my peers? Or do these weekly meetings make them sympathetic to the problems of their peers? “These are the challenges my peers are facing, and I have a solution. Let me step forward to help them.” What do they take away from these weekly meetings? When entrepreneurs engage in bonding rituals, they tend to view weekly progress meetings differently. Once entrepreneurs are exposed to bonding rituals, it tempers competition. During bonding rituals, entrepreneurs are able to let their guards down and share challenges they face. Since tournament-like rituals are a feature of many accelerator programs, accelerators should also work to promote bonding rituals.

2. Could you talk more about the broader implications and future opportunities for research? 

Dr. Krishnan: A broader implication of our study is that interaction rituals are far more important for social order than we think. In our research based in a Silicon Valley accelerator, interaction rituals played a pivotal role in the emergence, disruption and sustenance of micro social order in nascent entrepreneur networks. For instance, we know that prior ties between actors encourage future ties. That’s only one part of the story. In our dataset, there were prior ties that did not lead to future ties. And that was systematically shaped by the type of interaction rituals prevalent in different camps. The shared emotions that are regularly triggered in situational encounters in a network can change the trajectory of network evolution.

In terms of future research opportunities, research on accelerators suggests that mentor feedback accelerates venture failure as much as it accelerates business growth. Mentor feedback is a social process that often occurs in the presence of other entrepreneurs, so it is worthwhile asking how the feedback effect unfolds in accelerator programs. In one of our ongoing research projects in a start-up accelerator in Canada, we found that entrepreneurs used backstage rituals to cope with entrepreneurial failure.  Mentor led periodic meetings consciously encouraged bonding among entrepreneurs. Entrepreneurs were encouraged to share their feelings, insecurities, and progress with their mentors and their peer group. But entrepreneurs diverged in how they responded to these mentor meetings. Those who progressed well sought social support in their mentors rather than in their peers. But entrepreneurs who lagged behind participated in backstage rituals where they discussed issues such as their decision to quit their start-ups and seek employment; issues they were too embarrassed to discuss with successful peers and mentors. These backstage lunch rituals served as coping mechanisms for entrepreneurs who were lagging behind.

At a more macro level, let’s consider the larger networking landscape. Consider the Hackathon as an example. Building communities is one of the primary goals of these big networking events. Are they really building communities, though? Or are they just making people more competitive? Afterall, many coders come together to compete, and someone who does well will become the winner. What are these events reinforcing? It might be useful to examine the interaction dynamics at these larger social events.

3. Could you share with us how the research question emerged and evolved through the research process? Was it driven by the theory or the phenomenon?

Dr. Krishnan: It was driven by theory. Considering that entrepreneurs compete for resources, we were interested in understanding how social support networks emerged and evolved among entrepreneurs. Our research question largely revolved around this theme throughout but was sharpened and fine-tuned over the course of the review process. The accelerator was an exemplary setting that helped us explore these ideas. It was a time when start-up accelerators were beginning to emerge as an important phenomenon in the entrepreneurial landscape. In a typical start-up accelerator, entrepreneurs are expected to give to their fellow entrepreneurs without expectations, but participating entrepreneurs often find themselves competing for resources.

The accelerator also used an open-office concept, which worked well for us. Instead of having their own cubicles, entrepreneurs from three different camps occupied this huge open space. The best thing about this setting was that we didn’t observe a snapshot of a network, but we got to observe how networks organically emerge and evolve over time. When they started the program, these entrepreneurs (except for one camp) didn’t know each other. Thanks to the finite duration of the program there was a definite start time and end time. If ties were to emerge organically in an open workspace, you’d expect the usual tie formation mechanisms like proximity and homophily to kick in. However, if you are going by the argument that entrepreneurs are strategic actors, then you might see a more instrumental approach to networking. But entrepreneurs in each camp experienced different starting conditions, and their programs during the study period were structured differently. These differences shaped how entrepreneurs from different camps interacted in the open space and supported one another.

When we initially submitted the paper to ASQ, we placed our work in social network research. Although the quantitative portion of the paper reflected this, the qualitative portion that explained the differences in tie formation patterns across camps contained fine-grained and rich details on the kind of support entrepreneurs sought, received or failed to receive from their peers. The review team found that resource exchange dynamics were central to our story and recommended we expand on the social resource exchange angle. Although our research question revolved around social support, based on reviewer feedback we sharpened it and asked how unilateral giving can emerge and be sustained in an exemplar mixed-motive context—the start-up accelerator.

4. What advice would you give to the Ph.D. students or junior scholars who are interested in conducting an abductive study?

Dr. Krishnan: When you use an abductive approach, you come in with a broad research question and theoretical priors, but you don’t have fully developed hypotheses. You start with inductive grounded open coding. Surprising findings that diverge from existing theory begin a process of deduction where you collect more data or re-analyze your existing data. In the process, you also draw on alternate theories that help you explain the findings better.  Describing our journey will be useful in this regard. In our case, we were surprised by how interaction dynamics in social events played a key role in shaping unilateral giving and workplace interactions, which prompted us to collect more data and draw on interaction ritual theory.

One of the best things we did was collect quantitative network data from day one. My initial idea was to conduct a weekly survey on who talked to whom and who helped whom. But the accelerator did not grant us permission to do a survey because they felt it would take up too much of the entrepreneurs’ time. That’s when Rajiv, one of my co-authors, suggested I collect data on workplace interactions as and when it happened. And that decision helped our project immensely. Workplace interactions are unlike interactions in a social networking event. In a social networking event, it will be hard to keep track of interactions because there is likely to way too many interactions. In a workplace setting, individuals are generally mindful of another person’s time and interactions don’t occur for interaction’s sake but occur for a reason.

In our study, the entrepreneurs occupied an open office space and were free to interact with one another. Yet, while interactions were more organic in two of the camps, entrepreneurs in the third camp (Camp C) acted quite differently. Their interactions dwindled over time, even though they interacted early on. Over time, entrepreneurs in Camp C avoided each other; they did not even nod or smile at each other. We didn’t quite figure out what accounted for such stark differences in interaction patterns across camps until I began the exit interviews with entrepreneurs.

It wasn’t until the final exit interviews that shared emotions generated in social events emerged as an important theme. In the exit interviews, entrepreneurs in camps who interacted often in the workspace repeatedly mentioned how the informal weekend get-togethers helped them bond. This led to fresh rounds of data collection on participation in informal social events and revisiting data on camp C’s weekly progress meetings. As we revisited the data on Camp C’s weekly progress meetings, we observed that the shared emotions became negative over time. Entrepreneurs displayed apathy and distrust towards each other in weekly progress meetings. When collective emotions generated in social events became an important theme, we turned to interaction ritual theory to help explain our findings.  We had all these insights from the qualitative data that we deductively tested using the quantitative data. The quantitative data also helped us construct network graphs that helped illustrate the contrasting interaction patterns. Overall, my advice is to go into the field with an abductive mindset and be open to surprising findings that deviate from your theoretical priors.

5. Can you tell us what it was like to collect extensive qualitative data in both positive and negative social situations?

Dr. Krishnan: When you’re in the field, you’re just an observer. I had fun! Being in an accelerator, everything about Silicon Valley sort of came alive. I was just a fly on the wall, observing entrepreneurs’ interaction dynamics and trying to make sense of it while staying emotionally distant from it. I carried these theoretical priors in the back of my head and when the interaction dynamics deviated from these theoretical priors, I began questioning what might account for these surprises.

There’s no denying that I was affected negative situations at times. I remember one incident that really touched me, and I have talked about it in the paper. There was an implicit understanding in Camp C that a certain client would be a good match for an entrepreneur. The mentor always reminded him to have a good demo ready for the client. However, when the big day arrived, this entrepreneur’s pitch didn’t go well. Other entrepreneurs didn’t seem to care. They didn’t let this entrepreneur explain his case to the client more clearly during round table sessions. Instead, they dominated roundtable discussions by pitching their own ideas. If I recall correctly, one of them got an invitation to pitch to other members in the client’s company. It was supposed to be his client, but when the pitch failed, others were more opportunistic than helpful.  I felt sorry for the entrepreneur who failed, but one has to step back.

In a sense, these negative events become part of your findings. It pushes you to go back to your data and understand this further. I started wondering why entrepreneurs in Camp C were so competitive and hostile to one another? Consider a PhD cohort. It’s bound to influence how they approach each other if you tell them early on, “use each other, we’ll rank you,” versus “have each other’s back and be nice to each other.” In our case, the mentor’s message during onboarding rituals, which were further reinforced in subsequent weekly meetings, played a big part in setting exchange expectations. These expectations shaped early exchange dynamics. Failed exchanges became shaming rituals, triggering a vicious cycle of shaming and avoidance, culminating in the dissolution of ties. Long story short, you kind of use these negative situations to figure out what contributed to them.