Behavioral DEA model and its application to the efficiency evaluation of manufacturing transformation and upgrading in the Yangtze River Delta

  • Xiaoqing Chen
  • Xinwang LiuEmail author
  • Weizhong Wang
  • Zaiwu Gong
Methodologies and Application


The Yangtze River Delta (YRD) is a Chinese region with the highest level of economic development, which has an important impact on the level of China’s modernization. The development of manufacturing is the driving and critical force for the industrialization of the YRD. Transformation and upgrading are considered as an effective measure to improve the development of manufacturing industry. The purpose of this study is to develop a behavioral DEA (BDEA) model-based efficiency evaluation method by integrating the traditional DEA model with prospect theory. In this BDEA model framework, prospect theory is combined with the traditional DEA model to evaluate the development efficiency of manufacturing transformation and upgrading in the YRD, which takes behavioral preference of the decision-makers (DMs) in decision-making problems into account. In addition, the technique for order of preference by similarity to ideal solution method is applied to identify the reference points, in which maximum input minimum output is regarded as a negative reference point and the minimum input maximum output is regarded as a positive reference point. Then, the gain value and the loss value are obtained on the basis of the value function with reference points of prospect theory, and the overall utility function is further constructed to depict the behavioral preference of DMs. Finally, a case study is employed to illustrate the applicability of the proposed BDEA method by evaluating the relative efficiency of manufacturing transformation and upgrading in the YRD, and the comparative analysis with the result of efficiency values also shows the feasibility of the proposed BDEA model.


Data envelopment analysis Behavioral DEA model Manufacturing transformation and upgrading Yangtze river delta 



The authors wish to thank the anonymous reviewers for the valuable suggestions and comments which improved the quality of this paper. The work was supported by the National Science Foundation of China (NSFC) (71771051 and 71971121) and the Key Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (2017ZDIXM014), and the 2019 Jiangsu Province Policy Guidance Program (Soft Science Research) (BR2019064).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Economics and ManagementSoutheast UniversityNanjingChina
  2. 2.School of Economics and ManagementNanjing University of Information Science and TechnologyNanjingChina

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