Using AHP, DEA and MPI for governmental research institution performance evaluation

Chun Liu (), Tse-Yu Wang and Guang-Zhuang Yu

Applied Economics, 2019, vol. 51, issue 10, 983-994

Abstract: Under situations of limited resources, soft powers such as technology development and innovation become critical capabilities for a nation’s continuous growth and sustainability. Therefore, we used analytical hierarchy process (AHP), data envelopment analysis (DEA), and Malmquist productivity index (MPI) to evaluate the performance of research projects in 6 main fields of study managed by the Ministry of Science and Technology (MOST) in Taiwan from 2002 to 2012. Among the 6 fields of study, Agriculture and Humanities were two research fields as efficiency; and the sequence of inefficiency 4 fields were sociology, medicine, science, and engineering. Although the field of sociology was inefficiency, it was the only field show continuous growth in result of MPI analysis. Taking the fields as a whole, the result of the analysis of total factor productivity showed recession. However, as seen from the growth in technical change and in scale efficiency change, the MOST was effective to a certain extent during the period. However, the recession in technical efficiency change showed that further improvement in the planning and distribution of manpower and funds is needed.

Date: 2019
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DOI: 10.1080/00036846.2018.1524131

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