When and how do innovation ecosystems outperform integrated organizations? on technological interdependencies and ecosystem performance

Huanren Zhang, Yimei Hu, Xianwei Shi, Yuchen Gao*

*Kontaktforfatter

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Abstract

Purpose: Studies have documented the distinctive advantage of innovation ecosystems in integrating and recombining heterogeneous knowledge resources across firms' boundaries. However, hierarchical governance in the form of vertical integration is still preferred in many industries for organizing innovation, and the current literature touches little on the relative performance of different organizational structures (integrated firms vs innovation ecosystem) and the factors that lead firms to choose one over the other. The authors conjecture that structure of technological interdependence is one of such important factors. Using a computational experiment, the authors compare the innovation performance of ecosystems with integrated firms under different interdependency structures. Design/methodology/approach: Using the NKC model, the authors incorporate non-generic complementarities and modularity into the technological interdependence between different components. The authors compare four different types of technological interdependence (modular, hierarchical, nearly modular, and random). Findings: The results show that integrated firms with centralized search demonstrate stable and consistent performance that is robust to the structure of technological interdependencies, but an ecosystem significantly outperforms integrated firms with centralized or decentralized when the products exhibit modular or nearly-modular structures. Originality/value: This study sheds light on why an ecosystem often exhibits modular structures while vertical integration is prevalent in industries with complex technological interdependence. In addition, it shows the evolutionary nature of ecosystems and indicates how the cooperation and competition between actors shape the interdependence structure of ecosystems.

OriginalsprogEngelsk
TidsskriftIndustrial Management and Data Systems
Vol/bind122
Udgave nummer9
Sider (fra-til)2091-2120
ISSN0263-5577
DOI
StatusUdgivet - okt. 2022

Bibliografisk note

Funding Information:
Funding: The authors acknowledge the funding support by National Social Science Fund of China (20&ZD075), National Natural Science Foundation of China (72102144 and 72104121), Humanities and Social Sciences Project of the Ministry of Education of China (21YJC630114), Shanghai Pujiang Program (2020PJC074) and Shanghai Chenguang Program (20CG17).

Publisher Copyright:
© 2022, Emerald Publishing Limited.

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