Multiple approaches to entrepreneurial decision-making: A field study in India

Our ongoing research aims to understand and improve entrepreneurial decision-making in India. While much attention goes to startups that fail after implementation, many early-phase ideas never get off the ground. We are interested in how these nascent ideas can be transformed into successful companies. To study this question, we encouraged budding entrepreneurs with early ideas to join a pre-accelerator programme launched at ISB in collaboration with other business schools. The programme was designed and delivered by a mix of entrepreneurship faculty and industry experts trained to provide uniform instruction to the entrepreneurs. Participating start-ups also received support and follow-ups from trained research affiliates.

The pre-accelerator curriculum includes three main training approaches - scientific thinking, heuristics, and effectuation. Each approach aims to improve decision-making under uncertainty. The scientific approach teaches entrepreneurs to frame problems, derive hypotheses, test them, and evaluate results. Heuristics focuses on intuition, rapid testing, and iteration. Effectuation emphasises building on existing resources. By conducting this large-scale standardised training across different methods, we can evaluate the overall efficacy of such programmes. More specifically, we want to determine if certain types of training benefit specific entrepreneur profiles based on factors like education, work experience, and previous roles.

A key goal is identifying what works and if any type of training hinders particular entrepreneurs. This ambitious research initiative leverages a preaccelerator programme to study entrepreneurial decision-making at the earliest stages. By training a large number of early-stage entrepreneurs using different but standardised methods, we aim to elucidate the transformational process from ideas to successful companies. Our goal is to evaluate the impact of training on decision-making empirically and to provide data-driven recommendations on how best to support different types of entrepreneurs in India.