Technology Adoption in Online Social Networks

With the advances of information technology, online social networks are becoming increasingly important venues for technology adoption. However, although the dynamics of technology adoption in real world social networks have been well documented, technology adoption in online social networks remains relatively under-explored. This study identifies the differences between online and offline social networks and proposes a framework to investigate the dynamics of technology adoption in online social networks. To illustrate the proposed research framework, this study employs behavior-link panel data obtained from an open source software (OSS) development network to examine how online social networks affect the adoption of Subversion, the latest OSS version control technology. Based on social network theory, co-membership is used to construct online social networks within the OSS development network. Methodologically, this study takes advantage of the panel dataset and addresses the issues of simultaneity and individual heterogeneity that frequently confound the relationship between network structure and adoption decision, and as a result it demonstrates a more compelling relationship between social networks and technology adoption. The results of this study reveal that social networks are major conduits for technology adoption in an online social network in terms of imitation, leadership, lock-in, similarity, recency, and team size effects. In online social networks, one's decision to adopt a new technology is strongly influenced by the actions of the connected others. Project leaders have a stronger influence over other members in technology adoption decision making, even in informal virtual teams where traditional governance structures do not apply. Older projects exhibit stronger inertia and thus lack innovativeness. Similarities among projects facilitate faster adoption, and the effect of leadership attenuates in the networks with increasing project dissimilarity. Recent adoptions of technology within the networks, rather than more distant ones, have a stronger impact on subsequent adoption, implying the salience of memory over usage confidence, and increased size of a project team accelerates the rate of adoption. These results help in understanding the dynamics of technology adoption in online social networks, and provide useful guidelines for firms to promote technology and product innovation.