Literature DB >> 30530668

Modeling research universities: Predicting probable futures of public vs. private and large vs. small research universities.

William B Rouse1, John V Lombardi2, Diane D Craig3.   

Abstract

The future of the American academic research enterprise is considered. Data are presented that characterize the resources available for the 160 best-resourced research universities, a small subset of the 2,285 4-year, nonprofit, higher education institutions. A computational model of research universities was extended and used to simulate three strategic scenarios: status quo, steady decline in foreign graduate student enrollments, and downward tuition pressures from high-quality, online professional master's programs. Four specific universities are modeled: large public and private, and small public and private. The former are at the top of the 160 in terms of resources, while the latter are at the bottom of the 160. The model's projections suggest how universities might address these competitive forces. In some situations, it would be in the economic interests of these universities to restrict research activities to avoid the inherent subsidies these activities require. The computational projections portend the need for fundamental change of approaches to business for universities without large institutional resources.

Keywords:  computational model; research universities; strategic scenarios

Year:  2018        PMID: 30530668      PMCID: PMC6294910          DOI: 10.1073/pnas.1807174115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

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Authors:  Staša Milojević; Filippo Radicchi; John P Walsh
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

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Authors:  Katy Börner; William B Rouse; Paul Trunfio; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

2.  Vision for a systems architecture to integrate and transform population health.

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Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

  2 in total

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