Applied Evolutionary Economics and Economic Geography

Applied Evolutionary Economics and Economic Geography

Edited by Koen Frenken

Applied Evolutionary Economics and Economic Geography aims to further advance empirical methodologies in evolutionary economics, with a special emphasis on geography and firm location. It does so by bringing together a select group of leading scholars including economists, geographers and sociologists, all of whom share an interest in explaining the uneven distribution of economic activities in space and the historical processes that have produced these patterns.

Chapter 7: Informational Complexity and the Flow of Knowledge Across Social Boundaries

Olav Sorenson, Jan W. Rivkin and Lee Fleming

Subjects: economics and finance, economics of innovation, evolutionary economics, geography, economic geography, innovation and technology, economics of innovation

Extract

7. Informational complexity and the flow of knowledge across social boundaries Olav Sorenson, Jan W. Rivkin and Lee Fleming 1. INTRODUCTION Scholars from a variety of backgrounds – economists, sociologists, strategists and students of technology management – have sought a better understanding of why some knowledge disperses widely while other knowledge does not. In this quest, some researchers have focused on the characteristics of the knowledge itself (for example, Polanyi, 1966; Reed and DeFillippi, 1990; Zander and Kogut, 1995) while others have emphasized the social networks that constrain and enable the flow of knowledge (for example, Coleman et al., 1957; Davis and Greve, 1997). This chapter examines the interplay between these two factors. Specifically, we consider how the complexity of knowledge and the density of social relations jointly influence the movement of knowledge. Imagine a social network composed of patches of dense connections with sparse interstices between them. The dense patches might reflect firms, for instance, or geographic regions or technical communities. When does knowledge diffuse within these dense patches circumscribed by social boundaries but not beyond them? Synthesizing social network theory with a view of knowledge transfer as a search process, we argue that knowledge inequality across social boundaries should reach its peak when the underlying knowledge is of moderate complexity.1 To test this hypothesis, we analyse patent data and compare citation rates across three types of social boundaries: within versus outside the firm, geographically near to versus far from the inventor, and internal versus external to...

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