A DEA-ANN-based analytical framework to assess and predict the efficiency of Canadian universities in a service supply chain context
Benchmarking: An International Journal
ISSN: 1463-5771
Article publication date: 11 July 2022
Issue publication date: 22 November 2023
Abstract
Purpose
This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.
Design/methodology/approach
The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.
Findings
The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.
Research limitations/implications
This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.
Practical implications
The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.
Originality/value
This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.
Keywords
Acknowledgements
The authors would like to thank the editor and the anonymous reviewers for their constructive comments, which improved the quality of this paper significantly. This work was supported by Discovery Grants from the Natural Sciences and Engineering Research Council of Canada (grant numbers: RGPIN-2017-04434 and RGPIN-2017-04481) and the Dean's postdoctoral research awards from the Ted Rogers School of Management, Toronto Metropolitan University.
Citation
Jauhar, S.K., Zolfagharinia, H. and Amin, S.H. (2023), "A DEA-ANN-based analytical framework to assess and predict the efficiency of Canadian universities in a service supply chain context", Benchmarking: An International Journal, Vol. 30 No. 8, pp. 2734-2782. https://doi.org/10.1108/BIJ-08-2021-0458
Publisher
:Emerald Publishing Limited
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