A chance‐constrained data envelopment analysis approach for strategy selection

Purpose – To select the best strategies in the presence of both deterministic and non‐deterministic data in uncertain environments, without relying on weight assignment by decision makers, this paper aims to propose an innovative approach, which is based on mathematical programming called chance‐constrained data envelopment analysis (CCDEA). Design/methodology/approach – This paper proposes an innovative approach called CCDEA for strategy selection. Findings – In summary, the approach presented in this paper has some distinctive contributions: the proposed model does not demand weights from maker; DEA analysis obtains the optimal weights for all inputs and outputs of each decision‐making unit without relying on the subjective judgment of decision makers; the proposed model considers multiple criteria for strategy selection; the paper makes a sufficient contribution to the practice of operations research. This paper is the first study which applies CCDEA for evaluating the strategies in uncertain environments; and the paper introduces a method for strategy selection in the presence of stochastic data. Originality/value – To the best of the authors' knowledge, this paper is the first application of CCDEA to deal with strategy selection.