Abstract
Consequent to increasing higher education attainment and the expansion of higher education institutions, many countries have embarked on assessing discipline efficiency to track performance, promote competition, and ensure reasonable resource allocation. Therefore, measuring scientific-research efficiency is a crucial part of evaluating a discipline's development. This paper proposes the three-stage multi-criteria decision-making (MCDM) non-radial super-efficiency data envelopment analysis (NRSDEA) method with bootstrapping to study a discipline's scientific research efficiency from the university-level perspective. To ensure robust analysis, the proposed model incorporates the contextual variables describing the external environment and the random error. The data envelopment analysis (DEA) model is a non-oriented one. The three-stage DEA approach is applied, including contextual variables such as economic growth, innovation, infrastructure, and the natural environment. In addition, the bootstrap method is applied to correct for measurement errors. Finally, the research efficiency measurement of the statistics discipline at Chinese universities is taken as an example to verify the method's validity.
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