Undue concentration of research and education: multi-criteria decision approach to assess jurisdiction eligibility for NSF funding

Jeffrey M. Keisler (), Christy M. Foran, Maija M. Kuklja and Igor Linkov
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Jeffrey M. Keisler: University of Massachusetts Boston
Christy M. Foran: U.S. Army Engineer Research and Development Center
Maija M. Kuklja: University of Maryland
Igor Linkov: U.S. Army Engineer Research and Development Center

Environment Systems and Decisions, 2017, vol. 37, issue 3, 367-378

Abstract: Abstract Research and education tend to concentrate in specific geographical areas, while many jurisdictions receive limited federal research funding. This has resulted in reduced opportunity for students as well as limited ability of science to influence solving problems at the jurisdiction level. The National Science Foundation’s Experimental Program to Stimulate Competitive Research (EPSCoR) was intended to address the “undue concentration of research and education” by providing direct funding to improve research infrastructure, hire researchers, develop outreach, and to enhance local research capacity. Despite many successful outcomes attributed to EPSCoR, the aim and the execution of the program have generated controversy. Decision analytic tools can provide a systematic approach to EPSCoR prioritization that improves transparency and addresses the program’s intent. The wording of NSF’s mission and EPSCoR legislation suggest the intent of maximizing NSF’s benefit to the nation by directly supporting scientific research product across all jurisdictions and by supporting development of competitive scientific capabilities within particular jurisdictions. These components may be quantified via data-driven metrics producing indicators of ultimate benefit. Using illustrative scenarios within a multi-criteria decision model, we explore how such decision models may generate insights and how their guidance compares with current eligibility determinations.

Keywords: Research policy; Funding allocation; Transparency; Multi-criteria decision analysis (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10669-017-9650-9

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