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External heterogeneity and its impact on open innovation performance
Authors:Shufang Huang  Jin Chen  Lutao Ning  Dylan Sutherland  Zengjun Zhou
Affiliation:1. School of Public Administration, Zhejiang University, Zheda Road 38, Hangzhou 310007, People's Republic of China;2. School of Economics and Management, Tsinghua University, Qinghuayuan 1, Beijing 100084, People's Republic of China;3. School of Business and Management, Queen Mary, University of London, Mile End Road, London E1 4NS, UK;4. Durham University Business School, Mill Hill Lane, Durham DH1 3LB, UK
Abstract:While current research commonly finds there may be an optimum overall level of search depth commitment at the apex of an inverted U relationship, it says comparatively little about the optimal allocation of search depth between competing search channels. Neither does it explore in depth the qualitative differences in the breadth of different external search channels. Here we conceptually and empirically explore the idea of the intra-search channel allocation problem using the concept of heterogeneity in search depth and breadth. We explore how variations in the distribution of open innovation search depth and breadth influnence innovation performance and in doing so contribute to a more fine grained conceptual understanding of external innovation. We do so an emerging market context, namely China. Our contributions are therefore twofold, involving both conceptual and empirical elements.
Keywords:open innovation  external innovation factors  heterogeneity  innovation performance
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