Strategic Management Theories in Startups Assessment: A Multicriteria Fuzzy Decision-making Approach

Abstract

Evaluating start-up companies is an important management process for technology business incubators and it is also a typical multi-criteria decision‐making (MCDM) problem. Venture capitalists consider a MCDM problem before investing in a new venture, and the order preference of these criteria helps them make effective and efficient decisions. In this paper, we use fuzzy logic with the analytic hierarchy process (FAHP) technique to measure the relative importance of the strategic theory variables in assessment of a startup. The results of the study show that venture capitalist investors consider internal resources to be the most important criteria in evaluation, followed by industry resources and network-based. Entrepreneurs' track record also has a strong significant influence on startup assessment. The suggested tools confirm that it is possible to diversify the risks of an investor through the allocation of resources between several projects, in accordance with the received vector of global priorities, and such information is of high value for the process of decision-making. Therefore, the proposed approach outranks the required strategic inputs and provides a foundation to incorporate other statistical techniques, such as ANP, machine learning, and deep learning, in evaluation and to validate the results for future research.