Academic journal article Journal of Research Administration

Social Network Analysis to Evaluate an Interdisciplinary Research Center

Academic journal article Journal of Research Administration

Social Network Analysis to Evaluate an Interdisciplinary Research Center

Article excerpt

Abstract

We sought to examine the growth of an interdisciplinary center using social network analysis techniques. Specific aims were to examine the patterns of growth and interdisciplinary connectedness of the Center and to identify the social network characteristics of its productive members. The setting for this study was The Center for Interdisciplinary Research on Antimicrobial Resistance (CIRAR) at Columbia University. Periodic surveys and social network analysis comprised the study design. The data for this study included a relational survey taken by all members of the Center at three time points over one year. Respondents confirmed whether or not they had "heard of," "met," or "know the work of," or had "worked with" each of the other Center members. Data were analyzed using the social networking software program Organizational Risk Analyzer (ORA). Over time the social network increased in size, density, centralization, and complexity. The density of connections among and between different disciplines in the Center varied from Time 1 to 2 to 3; some increased, some decreased, while others stayed the same. Finally, the total degree centrality and the betweeness centrality of Center members were highly correlated to productivity. The study shows that a number of characteristics of an interdisciplinary research center can be quantified and described using social network techniques. Data from these analyses can be used to evaluate a center's progress, identify important indicators of leadership, identify areas of strength and need for improvement, and inform decisions on strategic direction.

Key Words: Interdisciplinary, Social Networking, Collaboration, Research, Growth

Introduction

Despite this nation's potential to deliver the finest health care in the world, the translational blocks from basic science to human studies and from clinical research to practice and policy clearly "impede efforts to apply science to better human health in a expeditious fashion. "(Sung et al., 2003) One way to expedite the translation of research to health care delivery is through interdisciplinary research, which crosses the traditional boundaries of profession, department, or institution. Indeed, much has been written in recent years about the value of interdisciplinary collaboration, to the extent that it has become one of the academic bandwagons of the day, and the National Institutes of Health (NIH) has identified interdisciplinarity as an explicit priority in its recent Roadmap, a strategic plan for future funding priorities http://nihroadmap.nih.gov/interdisciplinary/index.asp).

In a recent survey, more than 2,000 fulltime academic researchers ranked their collaborators above salary and job security as their highest priorities for job satisfaction (Grimwade & Park, 2003). Nevertheless, academic environments generally have established incentives for an entrepreneurial, independent approach to research. It has been suggested, in fact, that the academic culture hinders collaboration and, hence, slows translational research (Pober, Neuhauser, & Pober, 2001; Sung et al., 2003). Thus, data suggest that an interdisciplinary culture must be well planned and executed before success is possible. Despite this, there is little empirical evidence of a change in the traditional departmental academic systems and networks, with many initiatives identified as interdisciplinary actually being reconfigurations of traditional modes of multidisciplinary research (Rhoten & Parker, 2004).

The ultimate purpose of interdisciplinary research is to develop new knowledge or solve a relevant human problem by combining the skills and perspectives of multiple disciplines. This requires a realistic understanding of the nature of disciplinarity Although academic disciplines are often thought of as "bodies of teachable knowledge" (Woollcott, 1979) or as "conceptually specific structures" (Robertson, Martin, & Singer, 2003), these dehumanized descriptions do not capture the entire domain. …

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