An extended VIKOR method using stochastic data and subjective judgments

•Decision makers face several uncertainty levels through the decision making process.•We extend the VIKOR method to solve multi-criteria decision making problems with stochastic data.•We use the fuzzy analytic hierarchy process to define the weights of the decision criteria.•Our method is used to rank several bank branches based on their stochastic efficiency.•We compare our ranking with a stochastic super-efficiency data envelopment analysis model.

Decision makers (DMs) face different levels of uncertainty throughout the decision making process. In particular, natural language is generally subjective or ambiguous when used to express perceptions and judgments. The aim of this paper is to extend the VIKOR method and develop a methodology for solving multi-criteria decision making (MCDM) problems with stochastic data. The weights of the stochastic decision criteria considered in our extended VIKOR model have been determined using the fuzzy analytic hierarchy process (AHP) method. We present a case study in the banking industry to demonstrate the applicability of the proposed method. We also compare our results with the results obtained from a stochastic version of the super-efficiency data envelopment analysis (DEA) model to exhibit the efficacy of the procedures and algorithms.