Simulating Entrepreneurial Strategies In A Global Knowledge Economy

In seeking to better understand strategic entrepreneurship in the 21 st Century, this paper develops an agent-based simulation model that allows researchers to study different opportunity recognition strategies in a globalized knowledge economy. The simulation takes account of international knowledge spillovers and shows the comparative payoffs of each entrepreneurial strategy, with distinctive knowledge progression and financial performance profiles. In addition, the societal level effects that arise from competitive agent behavior can be analyzed. INTRODUCTION Looking at the literature on opportunity recognition, one can easily get the impression that we are dealing with only one player: that classical hero of entrepreneurship – the innovator that single-handedly conceives and develops an entrepreneurial enterprise. However, Ihrig (2010) argues that there are also other valuable strategies for recognizing and realizing opportunities, especially those that involve imitative behavior. He introduces a framework that distinguishes between four distinct entrepreneurial strategies: innovating, inventing, imitating, and copying. He goes on to describe an agent-based simulation that models those strategies, enabling researchers to study their associated financial payoffs and their knowledge creation potentials under different environmental conditions. As Ihrig and zu Knyphausen-Aufseß (2009) point out, it is important to analyze the opportunity recognition process in an international context. Therefore, the goal of this paper is to extend Ihrig " s (2010) simulation model, which places its entrepreneurs in a single " national " economy, and to develop a model that takes account of the global knowledge economy and international knowledge spillovers. For this, we first briefly review Ihrig " s (2010) framework and describe his original simulation model. We then present the model extensions that help implement the international dimension and show results of virtual experiments that highlight the distinct modeling capabilities of the simulation.