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While experimentation in entrepreneurial ventures has become a broadly accepted means to validate ideas and optimize business models, recent works have engaged in a critical debate about the potential limitations of scientific entrepreneurship and lean startup experiments. Our research looks at the practice of entrepreneurial experimentation in the context of a large engineering company that has built its corporate accelerator program around scientific entrepreneurship methods. We find that entrepreneurial experimentation comes in different forms and functions, which makes it important for entrepreneurs to select and execute experimental strategies appropriate for the respective business goals. They will need to develop, in particular, a strategic understanding of the commitment-generating function of experiments. Our findings contribute to the emerging interest in entrepreneurial experimentation and scientific entrepreneurship.
Lighting the Way: Knowledge Characteristics, Experimentation & Pivoting Amongst Entrepreneurial Ventures in a Nascent Industry
University of Illinois at Urbana-Champaign Sonali Shah,
University of Illinois at Urbana-Champaign
Firms in nascent industries engage in experimentation to reduce the manifold uncertainties they face. Although the importance of experimentation to entrepreneurial ventures has been well-documented, we understand little about how the experimentation process unfolds. Using an inductive, theory building approach, we find that firms engage in either an open or closed experimentation process; these processes involve strikingly different ways of gathering information and engender different entrepreneurial outcomes (pivots and financial performance). Three factors––prior entrepreneurial experience, prior industry knowledge, and an orientation towards technologies (rather than products)––work in concert to lead firms to pursue open (rather than closed) experimentation. This study is based on archival data and rich, first-hand interview data collected from founders in the global smart lighting industry.
A Simple Model of Experimentation and Learning in Early-Stage Ventures
This paper proposes a stylized model of experimentation in early-stage ventures combining elements of spatial differentiation and Bayesian learning. Given an initial product idea, a venture seeks to commercialize a product. It chooses one of two strategies: direct entry or experimental entry. Following direct entry, it develops the initial idea without new information and commercializes the product. Following experimental entry, it collects market feedback by experimenting, incorporates this information into the development process, and commercializes the product. Besides the upfront cost of experimenting, experimental entry implies learning biases, adaptation costs, and appropriability concerns. The model formalizes the notion that experimentation is optimal only when market uncertainty and learning capability are sufficiently high. Furthermore, experimentation is less valuable when adaptation is costly or appropriability is weak.
Venture Experimentation: Examining the Complementarity and Substitution Tension With Improved Measures of Entrepreneurial Activity
University of Oregon Lauren Lanahan,
University of Oregon
Public programs invest in early-stage activity to relieve entrepreneurs' resource constraints. Yet, it remains unclear whether public incentives truly spawn new activity or merely substitute other financial avenues of support. We seek to address this tension by offering insight when each mechanism – substitution or complementarity – predominates. We employ an improved measure of entrepreneurial activity considering failed and successful venturing initiatives. Empirical research on this subject has primarily focused on successful attempts, resulting in inaccurate interpretations. We find consistent evidence of a positive effect on the overall local entrepreneurial activity; this supports a complementarity argument. However, we also observe the effect is primarily driven by failed attempts. We explain the predominant effect of complementarity by considering the role of slack resources in venture experimentation.