Cohen, Bingham, and Hallen (2019). The Role of Accelerator Designs in Mitigating Bounded Rationality in New Ventures

Authors:

Susan Cohen – Terry College of Business, University of Georgia

Christopher B. Bingham – Kenan-Flagler School of Business, University of North Carolina at Chapel Hill

Benjamin L. Hallen – Foster School of Business, University of Washington

Interviewers:

Elisabeth Yang – Yale School of Management

Melody Chang – Yale School of Management

Article link: https://journals.sagepub.com/doi/full/10.1177/0001839218782131

The responses are written from Susan’s perspective, as the project has evolved out of her dissertation. All authors have collaborated on the interview.

1. Research Question and Framing. The paper introduced accelerators as a new type of organizational sponsor and has set forth an exciting avenue for future research. (a) For inductive studies in new, under-examined contexts, there seem to be so many factors one could consider exploring. What other accelerator characteristics did you consider and how did you decide to focus on the design aspects?  (b) You provide a rich, consistent story of how the design of accelerators plays a crucial role in shaping the learning of early-stage entrepreneurs mitigating the bounded rationality. In the paper, you mention that the authors “jointly considered many perspectives,” including “how accelerators accelerated learning of entrepreneurs.” Could you share with us how the story or the key takeaway changed over time as the paper evolved? 

When I first set out to study accelerator programs in 2011, I considered many different theoretical lenses, and many different aspects of accelerators. I went back to my archives to review some of the ideas that I had proposed to my dissertation committee (this paper started out as my dissertation). Some of my initial ideas explored accelerators as an emerging industry. The industry was expanding exponentially. New entrants seemed to be imitating the early pioneers – Y Combinator and Techstars – based on well-documented “industry recipes,” and yet results varied drastically. I was curious about why. But, when I entered the field, I realized that there were many differences between accelerators lying beneath the seemingly similar recipes. My advisor, Chris Bingham and I started to dig deeper into these differences. Over time we, along with Ben Hallen who joined the project later, realized that many of these differences had to do with accelerator’s designs. My dissertation also examined how the entrepreneurial teams divided their work, and how managing directors interacted with the ventures.

We focused on learning as a broad theoretical frame fairly early in the process. We noticed that some (but not all) accelerators helped ventures learn extremely quickly. The progress of these ventures was astounding. Yet, according to foundational theory, startups should have experienced time compression diseconomies when trying to accelerate. We tried framing the paper around time compression diseconomies, but alternative explanations were hard to rule out. For example, was it that some accelerators created richer learning environments than others? In order to prove time compression economies, inputs had to remain constant across programs and this was simply out of our control. On the other hand, even if the inputs varied, the simple fact that ventures in some accelerators learned so quickly was still vexing. We wondered, how were some ventures able to process such extraordinary amounts of information in such short periods of time?

2. Theory. Your paper furthers our understanding of early-stage entrepreneurship by applying theories about established organizations. How do you see research on early-stage entrepreneurship moving forward empirically and conceptually? Where do you think are some opportunities for theoretical advancement?

One area we started to explore was absorptive capacity. Absorptive capacity is one of the most highly cited theories in strategic management. However, its role in nascent organizations seems to be unclear. New organizations lack experience relative to established organizations. I think this could be an interesting avenue for future research. Another important area is the culture. When interviewing entrepreneurs, they often tell me about how they overlooked the critical importance of deliberately developing a positive organizational culture. Changing culture after the firm scales can be challenging. I think this is an area where theory lags practice, and where scholars could make an important contribution.

3. Method. Can you tell us more about how your research questions informed the multiple-case study design of the paper? Were there any challenges to conducting and analyzing multiple cases that may be different from doing inductive research at a single site? 

We began with a multi-case approach and never really considered a single case approach. Because accelerators were such a new phenomenon at the time, with no academic research, we felt that a multi-case study would afford us the opportunity to understand differences amongst programs. This was critical for our results to be more generalizable. Further, it would have been nearly impossible to know which single program to choose! There were only a handful of programs at the time and it was really hard to know which ones were going to survive. Some seemingly top-performing programs shut down during our study period.

Later, when we had a sense of our research question – a “how” question that also explores variance, a multi-case study was clearly the best fit. If we had a process question, then a single case may have been more of a contender.

4. Findings. You encountered surprising findings from the study that ventures in accelerator programs fostering privacy and with customized activities and spaced out consultations had lower performance, opposite from what the extant literature would suggest. Can you talk about the process of how you connected your emerging findings with the literature?

This was one of the most exciting parts of conducting the research. Chris was teaching me how to conduct qualitative research as we were conducting the research. He really highlighted the need to contrast our findings with extant research. If we simply confirmed that extant theory also applies in the accelerator context, then we would not be extending theory. As a PhD student, though, this was also really challenging, because it requires that you know the literature extremely well. Chris and I collaborated closely during this phase of the research. I made a lot of diagrams, both of the extant literature and what we saw in the field. I also read a lot of literature, and tried quite a few angles that did not work as well as the published version. Finding the contrasts – the places where the data and the literature are at odds is key to a strong contribution.

5. Empirical Setting. We are fascinated that you had an opportunity to work with 8 accelerators for the project. For PhD students interested in conducting research in the field, do you have any tips in getting buy-ins to conduct research in (for qualitative studies) or to access data from (for quantitative studies) organizations? How did you persuade these organizations to participate in the research study? How did you form and maintain relationships with different actors in the field?

Since I was usually the first researcher to contact accelerators about conducting research, many seemed flattered by the idea. The startup ethos values learning and experimentation, and most accelerator directors were deeply committed to learning, which helped. But, what likely helped even more was my personal network. I was an entrepreneur prior to getting my PhD and got my MBA from Kellogg. I knew someone affiliated with nearly all of the accelerators in my study – usually a mentor but sometimes an entrepreneur.

As far as recommendations, perhaps volunteering in the local community would help build relationships before you need them. As academics, we move frequently which can make connecting to the local community challenging. But try to do so.  Also, find institutions that value research and learning and that have not been approached before. Finally, many of our universities have active accelerator programs, such as iCorps, which can be ideal settings for research.

6. Collaboration. How did the collaboration come about, and how does this paper fit into each of your broader research streams? How did this paper affect your research trajectory and future plans?

As mentioned above, this paper grew out of my dissertation, and Chris is my advisor. Ben joined the team after I graduated and helped us sharpen the theory. After working on the project for several years it was extremely helpful to have a fresh pair of eyes to help us see more clearly and push the paper to the finish line.  The three of us have a companion paper that is forthcoming at Organization Science that uses mixed methods to explore whether or not accelerators improve outcomes for participating ventures, and if so, how.

While I was working in the field, accelerator directors introduced me to Yael Hochberg, who was running the Seed Accelerator Rankings Project at the time. The two of us now run it together, along with Dan Fehder. We collect confidential data from accelerator directors and participating ventures and provide an annual ranking of programs as a service to entrepreneurs deciding which programs to apply or attend. We published some initial findings in a recent article in Research Policy (along with Fiona Murray).

Susan and Ben have a handful of ongoing projects related to accelerators, investment syndicates and entrepreneurial careers. Chris is currently working on founding teams and coworking spaces with another PhD student.  We all work in the broad areas of entrepreneurship and organizational learning.

7. Any final comments?

Can we thank reviewer 2 again? Seriously, our reviewers and editor, Dev Jennings, were outstanding. We are grateful for their advice and support. 

Elisabeth’s Bio:

Elisabeth is a Ph.D student in Organizations and Management at Yale University’s School of Management. She is interested in the processes of organizing for collaboration and innovation, as well as how such processes are influenced by technological change. 

Melody’s Bio:

Melody is a Ph.D. student in Organizations and Management at Yale University School of Management. Her research interests focus on careers and organizations in entrepreneurial and innovation-driven environments. In particular, she explores the role of human capital and resource attraction in entrepreneurship.

Reflections on the Interview:

Interviewing with Susan, Chris, and Ben was a rewarding learning experience for both of us. When we first reached out to them for an interview, they were very enthusiastic about sharing their perspectives and behind-the-scenes stories. While we had many insightful takeaways from the interview, two lessons particularly stood out to us. First, we learned the value of deriving research questions from your personal experience and engaging with your existing network to conduct research that has relevance for both academics and practitioners. Their suggestions were particularly valuable to us as we are both working closely with organizations in our current projects and striving to develop both theoretical and managerial implications. Second, we gained insights on how to approach new phenomena and craft a novel theoretical contribution. Their advice on contrasting the findings with the existing theories is a helpful pointer for theory development, particularly when we are studying an emerging phenomenon.

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