Preferential Linkage and Network Evolution: A Conceptual Model and Empirical Test in the U.S. Video Game Sector

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Citation: N. Venkatraman, Chi-Hyon Lee (2004) Preferential Linkage and Network Evolution: A Conceptual Model and Empirical Test in the U.S. Video Game Sector. Academy of Management Journal (RSS)
Internet Archive Scholar (search for fulltext): Preferential Linkage and Network Evolution: A Conceptual Model and Empirical Test in the U.S. Video Game Sector
Tagged: Business (RSS) preferential linkage (RSS), network analysis (RSS), network evolution (RSS), interorganizational network (RSS)

Summary

This study investigates how network structure (density overlap and embeddedness) and technology characteristics of a platform (dominance and newness) affect network evolution in the case of U.S. video game industry. Since video game industry encompasses two main players of platform (game console) manufacturers and game developers which are highly dependent to be successful in the market, it is a rich environment for analysis of network evolution in a complementary context.

The empirical study demonstrates that structural embeddedness is the strongest predictor of linkage between game developers and platform manufacturers. Respectively, platform dominance in the network, its newness, and its overlap density are the other factors significantly explaining the linkage between the two parties.

Comments

The study provides valuable insights into inter-organizational network complexities of a context in which actor values complement each other. In this context, actors (developers) cooperate with a group of actors (console manufacturers) while compete with another group (other developers). However, the study lacks an agency view looking into how actor decisions to develop games for specific platforms would constrain their future decisions.

In terms of the effect size, the two factors of platform overlap density and age are marginally affecting preferential linkages with beta values of less than 0.05, while their significance could be due to the large sample size (over 2000).


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