Field experiments in networks, innovation and entrepreneurship [electronic resource] : evidence from a startup bootcamp
Keywords: Business.

In this three-part dissertation, I explore how social networks shape the process of innovation, entrepreneurship, and organizational learning. In the first chapter, I investigate if networks plentiful in ideas provide early stage startups with performance advantages. On the one hand, network positions that provide access to a multitude of ideas are thought to increase team performance. On the other hand, research on network formation argues that such positional advantages should be fleeting as entrepreneurs both strategically compete for the most valuable network positions and form relationships with others who have similar characteristics and abilities. I embed a peer effects experiment in a three-week-long startup bootcamp to test if networks that are plentiful in ideas lead to performance advantages. Using detailed data from the bootcamp's custom-designed learning management platform, I find support for the first hypothesis. Teams with networks more plentiful in ideas receive better peer evaluations and more crowdfunding page views. I find little evidence that entrepreneurs actively build networks to others who could have provided a greater quantity of information and ideas. Instead, entrepreneurs seek feedback from those they have collaborated with in the past or who share similar ascriptive characteristics. These findings provide first-order evidence for the importance of knowledge spillovers within bootcamps, incubators, and accelerators. Furthermore, the findings provide a potential explanation for the durability of idea and information-based network advantages. In the second chapter, I delve deeper into the social mechanisms underlying peer effects. I illustrate how text data provides a fruitful way to explore the mechanisms that lead to peer influence and learning. By capturing the unstructured language that a focal actor generates, I test if peers causally shape how a focal actor describes their thoughts, activities, and ideas. Furthermore, through formal mediation analysis, I check if changes in the language induced by a randomized peer serve as a channel by which peer effects shape outcomes. To do so, I use two sources of text data: work journal entries and the text of ideas generated during a half-day-long brainstorming session. I find that randomized peers do affect the words people write and in turn the outcome of interest. This structure, of measuring text between the peer treatment and outcome, not only enriches studies of social networks by providing insight into the social mechanism underlying peer effects, but provides a template for future researchers who want to estimate causal effects and use text to capture socially complex constructs like culture, norms, and practices. In the third chapter, I connect the literature on organization learning and adaption to the peer effects and network-influence models explored in the first two chapters. To do so, I model inter-firm learning as a two-stage process of formation and influence. In the first stage, firms select from whom who they want to learn. Conditional on this first stage, influence either occurs or does not. This model helps explain when firms will naturally learn best practices, when policymakers need to filter inter-firm interactions to improve a business ecosystem, and when merely bringing companies together will result in improved ecosystem performance. To test this model, I use data from a unique three-day-long bootcamp that brought together 167 startup founders. The bootcamp allows me to check if founders prefer to get advice from other startups that have better management practices and if this advice changes the focal startup's strategy. I find evidence for the two-stage learning model. First, founders prefer to get advice from founders who are better managers. Second, being randomly paired with a better manager results in the development of strategies that involve both more delegation and have potentially greater payoffs. The findings imply that policymakers need not filter how firms interact with one another, but merely need to create opportunities for firms to interact.