Person:

Koning, Rembrand

Recent scholarship argues that experimentation should be the organizing principle for entrepreneurial strategy. Experimentation leads to organizational learning, which drives improvements in firm performance. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of testing business ideas. Our results provide the first evidence on how digital experimentation affects a large sample of high-technology start-ups using data that tracks their growth, technology use, and products. We find that, although relatively few firms adopt A/B testing, among those that do, performance improves by 30%–100% after a year of use. We then argue that this substantial effect and relatively low adoption rate arises because start-ups do not only test one-off incremental changes, but also use A/B testing as part of a broader strategy of experimentation. Qualitative insights and additional quantitative analyses show that experimentation improves organizational learning, which helps start-ups develop more new products, identify and scale promising ideas, and fail faster when they receive negative signals. These findings inform the literatures on entrepreneurial strategy, organizational learning, and data-driven decision making.

Can managers influence the formation of organizational networks? In this article, we evaluate the effect of joint tasks on the creation of network ties with data from a novel field experiment with 112 aspiring entrepreneurs. During the study, we randomized individuals to a set of 15 joint tasks varying in duration (week-long teams to 20-min conversations). We then evaluated the impact of these interactions on the formation and structure of individuals’ social networks. We find strong evidence that these designed interactions led to the systematic creation of new friendship and advice relations as well as changes to the participants’ network centrality. Overall, network ties formed after a randomized interaction account for about one-third the individuals a participant knows, of their friendships, and their advice relations. Nevertheless, roughly 90% of randomized interactions never become social ties of friendship or advice. A key result from our research is that while joint tasks may serve to structure the social consideration set of possible connections, individual preferences strongly shape the structure of networks. As a consequence, there will likely remain a considerable unpredictability in the presence of specific ties even when they are designed.

Recent field experiments demonstrate that advice, mentorship, and feedback from randomly assigned peers improve entrepreneurial performance. These results raise a natural question: what is preventing entrepreneurs and managers from forming these peer connections themselves? We argue that entrepreneurs may be under-networked because they lack the necessary social skills—the ability to communicate effectively and interact collaboratively with new acquaintances—that allow them to match efficiently with knowledgeable peers. We use a field experiment in the context of a business training program in Togo to test if a short social skills training module increases the number and complementarity of peers that participants choose to learn from. We find that social skills training led entrepreneurs to match with 50% more peers and that more of those matches were based on complementary managerial skill. Finally, the training also increased entrepreneurs’ monthly profits by approximately 20%. Further analyses point to improvements in networking and advice as the drivers of performance improvements. Our findings suggest that social skills help entrepreneurs build relationships that create value for both themselves and their peers. The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4334 .

We analyze firm-driven labor market search, where firms “hunt” for talent rather than rely on workers to apply for vacancies. We leverage three approaches. We develop a model of firm-driven search and derive equilibrium conditions under which firms use this channel. We test our model's predictions using two data sources. Data from a nationally representative survey of 10,000 workers shows that the percentage hired through recruiting has increased from 4.9% in 1991 to 14.3% in 2022. This share is larger for higher-skilled workers and those with online profiles on LinkedIn. We complement this analysis with data on the near universe of online job postings from 2010 through 2020. Consistent with our model and worker survey evidence, we find firms that demand higher-skilled workers or operate in labor markets with heavy LinkedIn use are more likely to “hunt for talent.”