Cross-efficiency aggregation method considering bounded rationality: An application to healthcare service
Year: 2025
Type: article
Abstract: • This study develops a cross-efficiency evaluation method considering bounded rationality in decision makers. • It introduces inequality aversion and overconfidence into the cross-efficiency weight aggregation process, proposing an equity-minded approach. • A consensus compromise algorithm is developed to address consensus issues within evaluation groups based on the equity-minded cross-efficiency method. • The model is applied to assess healthcare service efficiency in China, highlighting the role of fairness preferences and overconfidence. • Tobit regression is used to analyze the factors influencing healthcare service efficiency in real-world scenarios. The cross-efficiency evaluation method is a powerful tool for assessing efficiency. However, previous research has often overlooked the bounded rationality of decision makers (DMs), thereby neglecting key factors. To address this gap, we investigate the cross-efficiency weight aggregation method under bounded rationality. Firstly, we develop a utility function incorporating inequality aversion and overconfidence, integrating them into the cross-efficiency weight aggregation process to formulate the equity-minded cross-efficiency method. Secondly, building upon this method, we address consensus issues within evaluation groups by introducing a consensus compromise algorithm. This algorithm aims to reconcile group opinions based on the principles of the equity-minded cross-efficiency approach. Furthermore, we apply our model to evaluate healthcare service efficiency in China. Our analysis explores the impact of overconfidence and fairness preferences, using a Tobit regression model to examine factors influencing healthcare service efficiency.
Authors: Hao Pan, Guoliang Yang, Yuanyu Lou, Zhongcheng Guan
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4409500428