Data envelopment analysis models based on decentralized decision making. (August 2022)

• Record Type: Journal Article
• Authors: Zhou, Zhixiang; Ma, Yuanfei; Pan, Yinghao; Zhu, Yangguang
• Is Part Of: Computers & industrial engineering. Volume 170(2022)
• Publication Date: 2022-08
• Subjects: Data envelopment analysis -- Decentralized decision-making -- Decentralized DEA -- Voting majority; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108318
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We discuss efficiency measurement based on decentralized making organizations. This paper describes DEA approach under decentralized decision making mode. We construct a set of decentralized DEA models based on "voting majority". Decentralized DEA models are constructed under different information availability. Abstract: Information technologies, such as blockchain, have promoted the development of decentralized decision-making in complex systems and generated many decentralized autonomous organizations. We construct a set of decentralized Data Envelopment Analysis (DEA) models based on the basic decentralized decision mode of "voting majority", and we consider the assumptions that DMUs have no prior information about other DMUs' decisions, and that they do. Then, the process of decision-making for each decision making unit (DMU) can be viewed as a social behavior over multiple time periods. Using a numerical example, we demonstrate that the new DEA models can provide acceptable efficiency results with specific weights for each DMU and can describe the details of the consensus relationship among DMUs. Similar to the market mechanism in reality, the efficiency scores of DMUs within an alliance containing more than half of the participants are overestimated, at the expense of nonallied DMUs. The models in this paper provide a possible path for efficiency measurement based on decentralized decision-making principles in complex systems.