Understanding knowledge sharing: From the perspectives of knowledge complexity, media selection, social capital, exploration and exploitation capabilities
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Increased interest in knowledge sharing phenomena has developed in the IS field during the last 20 years. The difficulty of successful knowledge sharing lies in the fact that knowledge sharing is a complicated process involving knowledge, media, sender and receiver. My dissertation is composed of three essays to study the successful knowledge sharing from the perspectives of knowledge complexity, media selection, social capital, and learning strategy of exploration and exploitation. In the first essay, the research question is: what specific knowledge transfer complexity dimensions are associated with what particular media capabilities in the context of knowledge transfer at the individual level, based on the notion of fit between knowledge complexity and media capabilities? Various knowledge characteristics are synthesized into four complexity dimensions (tacitness, depth, diversity, and obsolescence of knowledge transfer) after a comprehensive literature review is made. Through meta-analytical techniques employed on 80 studies published since 2000, I test the proposed model to show the relationship between each complexity dimension's fit and particular media synchronicity capabilities (transmission velocity, parallelism, symbol sets, and reprocessability) from effective dyadic knowledge transfer. In the second essay, I address about the role of different social capital in individual knowledge seeking. I consider the influence of two types of social capital (cognitive and relational capital) on knowledge seeking in the context of IS academic field, operationalized as research citations in top-tier IS journals. Using information about articles published in 10 leading IS journals during 2006-2011, social network analysis is first applied to develop measures for the considered social capital from citation and co-author relationships on each pair of authors. This is followed by a multiple regression quadratic assignment procedure due to the matrix format of the network data to investigate the effects of cognitive and relational capital on the knowledge seeking behaviors of IS researchers. In the third essay, I examine how two dimensions of knowledge creation capabilities (diversity and depth) proposed in essay 1 are likely to influence knowledge creation by IS researchers. A longitudinal author co-citation analysis is applied to develop measures for the two complexity constructs using the same data set as that used in essay 2. Both knowledge exploration and exploitation capabilities can be articulated as an individual-level knowledge-cluster-related construct showing diversity and depth. Then, I test each dimension's influence on knowledge creation, operationalized as 2011 publication of each individual author. In summary, I develop theoretical frameworks and test the proposed models with two data sets to address the success of knowledge sharing (including knowledge transfer, knowledge seeking, and knowledge creation) at the individual level from the standpoints of knowledge complexity (essay 1 and 3), media selection (essay 1) and social capital (essay 2).