Indiana University SPEA Edward J. Bloustein School of Planning and Public Policy University of Pennsylvania AIR American University

Panel Paper: Linking Network Structures with Dyad Relations: Examination of the CTSA Program and Knowledge Transfer in Scholarly Collaboration Networks

Saturday, November 14, 2015 : 10:55 AM
Grenada (Hyatt Regency Miami)

*Names in bold indicate Presenter

MengHao Li, George Mason University
In 2006, the National Institutes of Health launched the Clinical and Translational Science Awards (CTSA) program aiming to bridge the gap between basic science and clinical research. The University of Illinois at Chicago (UIC) is one of awarded medical research institutions that received the CTSA funding in July, 2008 and established the Center for Clinical and Translational Science (CCTS) to facilitate translational process. This article thus aims to explore how the CCTS intervention affects knowledge transfer among scientists at UIC.

The article frames two levels of analysis to understand how the CCTS intervention (individual level), network properties (individual level; i.e. degree centrality and network heterogeneity), and the nature of ties (dyad level; i.e. strength of tie, spatial proximity, and homophily of disciplines) affect knowledge transfer between two scientists (dyad level). The knowledge transfer among the scientists is defined as three variables, “providing clinical expertise,” “providing methodological or theoretical expertise” and “providing diverse methods or approaches.”

The data that employed in this article come from the UIC CCTS evaluation project. The project successfully interviewed 406 respondents (CCTS users=208; non-CCTS users=198) by conducting web survey and ego-centric network methods in 2010. Students and staff were removed from the analysis because the non-CCTS users only include faculty. Moreover, one of the research questions in this article is to understand the effect of spatial proximity on knowledge transfer.  In order to identify respondents and their collaborators’ locations, the respondents must be faculty members at UIC as a reference group for the comparison purpose. Non-UIC respondents thus were removed from the analysis (N=308). In addition, this research attempts to know how network factors influence knowledge transfer between two scientists. The respondents who did not have collaborators were removed from the sample (N=230). Because of some missing values in other analytic variables, the final sample in the analysis is 169 respondents with 1056 ties. Since the data include two levels of analysis, the hierarchical linear model (HLM) is used to estimate the model.

The results show that the factors that influence three types of knowledge transfer perform differently. First, the CCTS users are more likely to obtain clinical expertise from their collaborators in comparison with the non-CCTS users. The respondents’ strong ties are more likely to embed clinical expertise. Comparing to collaborators at UIC, the respondents who have collaborators in external academic locations are more likely to provide clinical expertise. Second, the respondents who have higher level of degree centrality are more likely to obtain methodological or theoretical expertise from collaborators. Comparing to non-academic collaborators, UIC collaborators are more likely to provide methodological or theoretical expertise. Finally, the results did not discover appropriate predictors to explain the variance of providing scientists with diverse methods or approaches.