Journal
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
Volume 72, Issue 11, Pages 2442-2459Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/01605682.2020.1796534
Keywords
Data envelopment analysis; interdependent processes network; parallel system; decentralized and centralized modes; waste
Funding
- National Natural Science Funds of China [71971203, 71871223, 71571173, 71921001]
- Four Batch Talent Programsof China
- Fundamental Research Funds for the CentralUniversities [WK2040160028]
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Data envelopment analysis (DEA) is a technique used to evaluate the performance of decision-making units, and the interdependent relationship between system components is crucial in performance evaluation. With complex competition, interdependent systems have become increasingly common in production systems.
Data envelopment analysis (DEA) is a non-parametric technique that is widely used in measuring the performance (efficiency) of decision-making units (DMUs). Many network DEA models have been built to investigate the internal structure of a system, which was considered a black box in traditional DEA models. However, the interdependent relationship between system components is rarely considered in performance evaluation. Interdependent processes system has become common in production systems because of complex competition. In this study, we build a novel DEA model to investigate the efficiency of a parallel system with two interdependent components. Furthermore, decentralized and centralized models are built to respectively measure the efficiency of DMUs in decentralized and centralized organization modes. The analysis shows that fewer inputs can produce more outputs but fewer wastes among the components under the centralized mode. Finally, our approach is verified through a numerical example and an application to Chinese high-level universities.
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