Organizational Learning And Entry: Complexity Approach To Performance Differentials Between Diversifying Entrants And Entrepreneurial Start-Ups

Martin Ganco (and Rajshree Agarwal), Business Administration, UIUC

There is a well-developed empirical literature suggesting that the characteristics of firms at the time of entry have long-term consequences for the firm performance. But the consensus about the performance implications of each specific initial firm characteristic is considerably weaker. Modeling the industry dynamics as an extension of the co-evolutionary NKC model, we explore the performance differentials of entrants that vary in the degree of complexity of their organizational routines, time of entry and learning mechanism. Our results show that only some groups of late entrants can outperform the incumbents (depending on routine complexity and environmental turbulence) and the optimal late entry strategy involves significant random innovation combined with vicarious learning from incumbents. The level of environmental turbulence driven by inter-firm interactions also unequally affects the ability of firms to adapt depending on the level of their routine complexity, time of entry, and the stage of the industry. High levels of inter-firm interactions destroy learning of the less robust firms faster but an exceedingly high level destroys adaptation of all firms.

Key words: industry and firm evolution, diversifying and entrepreneurial entry organizational adaptation and learning, NK model.