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

Author

Listed:
  • William B. Rouse

    (Center for Complex Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ 07030)

  • John V. Lombardi

    (Center for Measuring University Performance, University of Massachusetts, Amherst, and University of Florida, Amherst, MA 01004)

  • Diane D. Craig

    (Center for Measuring University Performance, University of Massachusetts, Amherst, and University of Florida, Gainesville, FL 32611)

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.

Suggested Citation

  • William B. Rouse & John V. Lombardi & Diane D. Craig, 2018. "Modeling research universities: Predicting probable futures of public vs. private and large vs. small research universities," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12582-12589, December.
  • Handle: RePEc:nas:journl:v:115:y:2018:p:12582-12589
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    Cited by:

    1. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.

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