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Performance measurement in the parallel interdependent processes systems under decentralized and centralized modes

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  • Beibei Xiong
  • Jie Wu

Abstract

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.

Suggested Citation

  • Beibei Xiong & Jie Wu, 2021. "Performance measurement in the parallel interdependent processes systems under decentralized and centralized modes," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(11), pages 2442-2459, November.
  • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:11:p:2442-2459
    DOI: 10.1080/01605682.2020.1796534
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    Cited by:

    1. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

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