S-Space College of Business Administration/Business School (경영대학/대학원) Dept. of Business Administration (경영학과) Journal Papers (저널논문_경영학과)
Coauthorship Dynamics and Knowledge Capital: The Patterns of Cross-Disciplinary Collaboration in Information Systems Research.
- OH, WONSEOK; CHOI, JIN NAM; KIM, KIMIN
- Issue Date
- M e Sharpe Inc
- Journal of Management Information Systems, 22, 3 (2005-6), 265-292
- coauthorship patterns; knowledge capital; ontology of IS research; research impact; social networks; SSIC index; structural holes
- From the social network perspective, this study explores the ontological structure of knowledge sharing activities engaged in by researchers in the field of information systems (IS) over the past three decades. We construct a knowledge network based on coauthorship patterns extracted from four major journals in the IS field in order to analyze the distinctive characteristics of each subfield and to assess the amount of internal and external knowledge exchange that has taken place among IS researchers. This study also tests the role of different types of social capital that influence the academic impact of researchers. Our results indicate that the proportion of coauthored IS articles in the four journals has doubled over the past 25 years, from merely 40 percent in 1978 to over 80 percent in 2002. However, a significant variation exists in terms of the shape, density, and centralization of knowledge exchange networks across the four subfields of IS--namely, behavioral science, organizational science, computer science, and economic science. For example, the behavioral science subgroup, in terms of internal cohesion among researchers, tends to develop the most dense collaborative relationships, whereas the computer science subgroup is the most fragmented. Moreover, external collaboration across these subfields appears to be limited and severely unbalanced. Across the four subfields, on average, less than 20 percent of the research collaboration ties involved researchers from different subdisciplines. Finally, the regression analysis reveals that knowledge capital derived from a network rich in structural holes has a positive influence on an individual researcher's academic performance.
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