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Input–output analysis of international research collaborations: a case study of five U.S. universities

Abstract

International collaboration in research is increasingly recognized as an important component of both research and internationalization priorities by higher education institutions. This study analyzed the input–output trends of international research collaboration at five U.S. public universities using quantitative research metrics. We also tested these set of metrics to understand its individual direct relationship with international research collaboration using binary logistic regression. Results showed that international faculty, research funding, research influence, and academic impact were statistically significant (P < 0.05) and can serve as single predictors of international research collaboration for the five universities. Findings should provide international officers and research managers with clear sample data and metrics, and their association to make judgments and decisions on the value and impact of international research collaborations as they relate to overall research progress, productivity and research quality of U.S. universities.

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Acknowledgements

The authors are grateful to collaborators at Colorado State University (Dr. James Cooney, Dr. Alan Rudolph and Doug Leavell); Michigan State University (Dr. Steve Hanson and Dr. John Whims); Kansas State University (Dr. Mary Lou Marino and Dr. Marcellus Caldus); and University of North Texas-Denton (Dr. Richard Nader, Dr. Thomas McCoy, Amanda White and Jaya Vaidyanathan) for their support in study design and data collection at their respective institutions. The authors also thank data providers from the five universities.

Funding

This work was supported by the National Science Foundation Award Number NCSE-1324474 “International Research Evaluation Metrics”.

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Correspondence to Jane Payumo.

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Payumo, J., Sutton, T., Brown, D. et al. Input–output analysis of international research collaborations: a case study of five U.S. universities. Scientometrics 111, 1657–1671 (2017). https://doi.org/10.1007/s11192-017-2313-2

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Keywords

  • International collaboration
  • University
  • Quantitative metrics
  • International research metrics