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.