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

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.

Keywords:

• Data envelopment analysis
• interdependent processes network
• parallel system
• decentralized and centralized modes
• waste

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research is supported bythe National Natural Science Funds of China (Nos. 71971203,71871223, 71571173, 71921001), the Four Batch Talent Programsof China, and the Fundamental Research Funds for the CentralUniversities (Grant No. WK2040160028).