RESEARCH

A classical approach to collecting and elaborating information to make entrepreneurial decisions combines search heuristics such as trial and error, effectuation, and confirmatory search. This paper develops a framework for exploring the implications of a more scientific approach to entrepreneurial decision making. The panel sample of our randomized control trial includes 116 Italian startups and 16 data points over a period of about one year. Both the treatment and control groups receive 10 sessions of general training on how to obtain feedback from the market and to gauge the feasibility of their idea. We teach the treated startups to develop frameworks for predicting the performance of their idea and to conduct rigorous tests of their hypotheses, very much as scientists do in their research. We let the firms in the control group, instead, follow their intuitions about how to assess their idea, which has typically produced fairly standard search heuristics. We find that entrepreneurs who behave like scientists perform better, pivot to a greater extent to a different idea, and do not drop out less than the control group in the early stages of the startup. These results are consistent with the main prediction of our theory: a scientific approach improves precision – it reduces the odds of pursuing projects with false positive returns, and increases the odds of pursuing projects with false negative returns.

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Forthcoming, Management Science

In early-stage entrepreneurship, we argue that descriptions of activities conducted by entrepreneurs to create a new venture – both planning and especially experimentation-based activities – will be valued by resource providers as a signal of the quality and the feasibility of new ventures. We evaluate 54,337 project descriptions of entrepreneurs seeking funds on Kickstarter to provide initial evidence of the impact of planning and experimentation activities described by entrepreneurs on resource providers. Our results show that resource providers value both the description of planning and experimentation, with the latter increasing the likelihood of funding, especially for inexperienced entrepreneurs. These patterns are replicated in online experiments, suggesting that they represent true causal relationships in the observational data.

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Under review, Strategic Management Journal

Identifying the most promising business ideas is key to the introduction of novel firms and the creation of new value for societies, but predicting the success of novel business ideas can be difficult. To select the best business ideas, we argue that entrepreneurs must excel at formulating problem clearly, developing theories about the implications of their actions, and test these theories. Using a field experiment with 251 nascent entrepreneurs attending a pre-accelerator programme, we examine the conditions that aid the assessment and development of business ideas, focusing on the effect of a scientific approach to decision making. In the field experiment, both treated and control entrepreneurs undergo a training course that teaches them market validation techniques. The treatment group is also thought to formulate the problem scientifically, and to develop and test theories about their actions. We collect 18 data points on the decision-making and performance of all entrepreneurs for 14 months. Results show that treated entrepreneurs are more likely to select and develop profitable ideas. This difference in performance derives from the fact that treated entrepreneurs are more likely to abandon seemingly unprofitable ideas and pivot to more promising ones. Crucially, treated entrepreneurs pivot fewer times than control entrepreneurs, suggesting that they are better equipped to pivot to more valuable ideas. This study highlights that a scientific approach to decision making is a critical bridge linking decision making and performance of nascent entrepreneurs, sheds light on the importance of prediction in uncertain contexts and advances theory on why many entrepreneurs fail to create novel firms. 

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Nominated for  the Best Conference Paper Award, SMS Minneapolis

Preparing for submission, target: Organization Science

While previous research has shown that entrepreneurial teams can benefit from diversity, research in this area has consistently shown that most founding teams are highly homogenous. As a result, the initial homogeneity within an entrepreneurial team can potentially limit access to heterogeneous information sources and constrain the range of viewpoints that can be generated. This is likely to hurt creative performance, which is typically observed in the initial stages of new venture foundation, when entrepreneurial teams are attempting to identify a viable business idea. In bringing together insights from literature on creativity and early-stage entrepreneurship, we are looking to gain a better understanding of what helps entrepreneurs generating and selecting viable business ideas. In order to gather causal evidence in a realistic setting, we are planning to conduct a field experiment embedded within a hackathon in September 2019.

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Design stage, field study to be conducted in October 2019

This is an ongoing study with 140 start-ups in the tech sector in Italy. The data collection is ongoing and will end in February 2020.

This is an ongoing study with 290 later-stage entrepreneurial firms with less than 10 employees. The data collection will end in December 2019.