Measuring entrepreneurship: Expert-based vs. data-based methodologies

The concept of entrepreneurial orientation (EO) has become essential in research into the degree of entrepreneurial behavior at firm level. It is relevant to managers to be able to assess explicitly the level of entrepreneurship of a firm. Incubators, venture capitalists, corporate venturing units, angel investors, investment banks and governments need solid measures that go beyond expert intuition to assess the entrepreneurial nature of firms before they invest in them. Researchers have examined EO and consider innovativeness, risk taking, and proactiveness are important dimensions of this concept. Although the concept is seen as a multidimensional construct, there has been a great deal of debate among scholars on how to analyse it. The traditional statistical methodology has a number of drawbacks. In this article, we extend the debate and assess the construct of EO using four different methodologies: the traditional statistical methodology, a fuzzy-logic methodology, a DEA-like methodology and a naive methodology. As an expert-based methodology, fuzzy logic compensates some of the limitations of the statistical methodology. Drawing on a sample of 59 start-ups in a self-administered questionnaire, we measure innovativeness, risk taking and proactiveness and subsequently compare the resulting EO scores using the four methodologies. We found several differences, the most prominent of which are discussed in greater detail. The EO score from a naive methodology yields a value that lies between the other results, while the entrepreneurial score from a fuzzy logic methodology is most different from the other results.