A DEA Game Cross-Efficiency Model with Loss Aversion for Contractor Selection

Author:

Huang Huixia12,Zhou Chi3ORCID,Deng Hepu4ORCID

Affiliation:

1. Business School, Foshan University, Foshan 528225, China

2. Research Centre for Innovation & Economic Transformation, Research Institute of Social Sciences in Guangdong Province, Foshan 528225, China

3. School of Management, Tianjin University of Technology, Tianjin 300384, China

4. School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, VIC 3000, Australia

Abstract

Evaluating and selecting appropriate contractors is critical to the success of specific construction projects in the building industry. Existing approaches for addressing this problem are unsatisfactory due to the ignorance of the multi-dimensional nature of the evaluation process and inappropriate consideration of existent risks. This study presents a DEA game cross-efficiency model with loss aversion for evaluating and selecting specific contractors. The competitiveness of the evaluation process is modeled using game theory with respect to the adoption of the cross-efficiency model. The attitude of the decision maker toward risks is tackled with the use of loss aversion, which is a phenomenon formalized in prospect theory. As a result, the proposed approach can adequately screen available contractors through prequalification and adequately consider the attitude of the decision maker toward risks, leading to effective decisions being made. An example is presented to demonstrate the applicability of the proposed model in evaluating and selecting appropriate contractors for specific construction projects. The results show that the proposed model is effective and efficient in producing a unique solution for contractor selection through appropriate modeling of the multi-dimensional contractor selection process and adequate consideration of the competition between the contractors and the attitude of the decision maker toward risks in practical situations.

Funder

Guangdong Provincial Philosophy and Social Sciences Plan 2022 Project

Publisher

MDPI AG

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