Author List: Dey, Debabrata;
Information Systems Research, 2013, Volume 24, Issue 4, Page 1087-1099.
We examine how network centrality and closure, two key aspects of network structure, affect technology adoption. In doing so, we consider the content of potential information flows within the network and argue that the impact of network structure on technology adoption can be better understood by separately examining its impact from two groups of alters—current and potential adopters. We contend that increased network centrality and closure among current adopters contribute positively to adoption, whereas the same among potential adopters has exactly the opposite impact. Accordingly, we propose a dynamic view where the fraction of current adopters in the network positively moderates the impact of network centrality and closure. We empirically test the theory by analyzing the adoption of software version control technology by open source software projects. Our results strongly support the theory.
Keywords: technology adoption;network structure;network centrality;network closure;dynamic view;software version control technology;open source software
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List of Topics

#249 0.239 network networks social analysis ties structure p2p exchange externalities individual impact peer-to-peer structural growth centrality participants sharing economic ownership embeddedness
#49 0.236 adoption diffusion technology adopters innovation adopt process information potential innovations influence new characteristics early adopting set compatibility time initial current
#273 0.127 source open software oss development developers projects developer proprietary community success openness impact paper project associated activity phenomenon peripheral variety
#58 0.082 internal external audit auditing results sources closure auditors study control bridging appears integrity manager effectiveness auditor controls facilitating boundaries potential
#262 0.082 impact data effect set propensity potential unique increase matching use selection score results self-selection heterogeneity evidence measure associated estimate leads
#235 0.076 diversity free impact trial market time consumer version strategy sales focal premium suggests freemium trials effect include extensions internet products