Please use this form to submit your study for inclusion into our database. It will be checked by a member of the Innovation Growth Lab team, who may be in contact to ask for more information. Your email address * Your name * Title * The name of the study Short summary Identifying the most promising business ideas is key to the introduction of novel firms, but predicting their success can be difficult. It is argued that if entrepreneurs adopt a scientific approach by formulating problems clearly, developing theories about the implications of their actions, and testing these theories, they make better decisions. A brief description of the project's goals and its current state Abstract <p>Identifying the most promising business ideas is key to the introduction of novel firms, but predicting their success can be difficult. It is argued that if entrepreneurs adopt a scientific approach by formulating problems clearly, developing theories about the implications of their actions, and testing these theories, they make better decisions. In particular, this approach helps entrepreneurs to make more precise predictions of the value of their idea and to spot new ideas with higher expected returns. Precision implies that the distribution of value perceived by the entrepreneurs is more concentrated around its mean. While this cuts the right tail, it does not have important implications for the left tail because entrepreneurs will close the firm before making profits smaller than their opportunity cost. Thus, other things being equal, precision reduces expected returns, making it more likely that scientific entrepreneurs close their firm. At the same time, the scientific approach helps to see new ideas with higher probabilities at the right tail. Thus, when they do not close the firm, they perform better. Using a field experiment with 250 nascent entrepreneurs attending a pre-acceleration program, we provide evidence consistent with these mechanisms. The treated group is taught how to formulate the problem scientifically and to develop and test theories about their actions, while the control group follows a standard training approach. 18 data points are collected on the decision-making and performance of all entrepreneurs for 14 months. Results show that the narrower spread of the prediction of business value of treated entrepreneurs raises the probability that they close their startups. Scientific entrepreneurs are also more likely to see new opportunities with higher odds at the right tail which prompts them to pivot to these new ideas and perform better.</p> The full abstract of the study, if available Links Links to any published papers and related discussions Authors * Affiliations Academic and other institutes that the authors of the study are members of Delivery partner Organisations involved in delivering the trial, if appropriate Year Year Year199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026 Month MonthJanFebMarAprMayJunJulAugSepOctNovDec Day Day12345678910111213141516171819202122232425262728293031 Journal Journal publishing the study, if available Publication stage * Working Paper Published Ongoing Research Forthcoming Discussion Paper Research theme * Entrepreneurship Innovation Business Growth Country Country or countries where this study took place. Topics What sort of topics does the study cover? Sample attributes Hypotheses / research question How does the scientific approach affecting the prediction of the distribution of returns from a venture? Sample Trial population and sample selection Nascent startups with a business idea they want to develop further. They are yet to undertake significant steps to bring their product or service to the market. Participant startups operate in a wide range of sectors, with fashion, food, finance and software being the most common ones. The majority (76%) intend to use internet enabled technologies to bring their product or services to the market. Most participants are founding teams of two to three members. Participants’ average age is around 31 years, 78% are male and most hold a bachelor degree. Their expectation at the beginning of the programme is to start making revenue from their business idea within slightly less than a year. Participants are representative of the population of entrepreneurs in the country, on the basis of their demographic characteristics and of the sectors they operate in. Number of treatment groups Size of treatment groups Size of control group Unit of analysis Clustered? Yes No Cluster details Trial attributes Treatment description During the sessions, half of the participant startups are taught a “scientific approach” to decision making. That is, how to frame, identify, and validate the problem; formulate falsifiable hypotheses; and test them using reliable data and experiments. This includes defining valid metrics and establishing clear thresholds for concluding whether a given hypothesis is corroborated or not. Rounds of data collection Baseline data collection and method Baseline data included Startup potential, sector and start up experience , management and work experience, working hours, gender, age and team size. On these parameters the randomization was found to be balanced. Data collection method and data collected Evaluation Outcome variables Results <p>Being taught how to implement a scientific approach to decision making increases the probability that nascent entrepreneurs cease all activities related to their business idea (exit) by about 10%. The decision to exit is taken earlier for those trained on the scientific approach, compared to entrepreneurs who do not receive the training. This effect seems to be driven by the training on the scientific approach helping entrepreneurs be more precise in their predictions about the profitability of their ideas, and therefore to realise more often and earlier that very positive scenarios are unlikely to occur. Being trained on the scientific approach to decision making makes entrepreneurs more likely to pivot to a new business idea once, while reducing the probability of them pivoting more than twice. There is suggestive evidence that this effects are due to “scientific entrepreneurs” being more able to see new versions of their idea they can pivot to as well as better at envisioning profitable options they can pivot and stick to. Within the first and a half year, firms receiving the scientific approach training do not have higher odds of starting to make positive revenue, but average revenue is higher for them. There is suggestive evidence that this effect is due to the scientific approach allowing entrepreneurs to identify new factors that increase the value of their business idea, on the basis of improved understanding of the problem.</p> Intervention costs Not available. Cost benefit ratio Reference Camuffo, A., Gambardella, A., & Spina, C. , 2020. Small changes with big impact: Experimental evidence of a scientific approach to the decision-making of entrepreneurial firms. Citation for use in academic references
