Growing artificial entrepreneurs : advancing entrepreneurship research using agent-based simulation approach

Abstract

Purpose – The aim of this paper is to offer agent?based modelling (ABM) as an alternative approach to advance research in entrepreneurship. It argues that ABM allows entrepreneurship researchers (i.e. the designers) to find better ways in generating entrepreneurial outcomes by understanding alternative histories and examining a plausible future.

Design/methodology/approach – This paper begins with an overview of ABM, and discusses the shared conceptual foundations of entrepreneurship and ABM as the motives for the adoption of ABM as an appropriate methodology to study entrepreneurship. It offers a roadmap in using ABM approach for entrepreneurship research and illustrates this using a contemporary research question in entrepreneurship: the study of success/failure in business venturing.

Findings – This paper suggests the shared foundations between ABM and entrepreneurship as the basis for bringing the methodology and research domain closer. It offers a roadmap for advancing entrepreneurship research using agent?based simulation approach and explains the contribution of ABM to further advance entrepreneurship research.

Originality/value – This paper addresses the methodological gap in entrepreneurship research and develops the argument for a wider adoption of ABM simulation approach to study entrepreneurship. It bridges the gap by examining the possibility of formalizing entrepreneurship processes by grounding an agent?based model on empirical facts and generally?accepted foundations of entrepreneurship. It offers a contribution to the literature by showing that ABM is a useful and appropriate methodological approach for entrepreneurship research in addition to the conventional variance and process approach.

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