Logistics provider selection for omni-channel environment with fuzzy axiomatic design and extended regret theory

As e-commerce marketplaces proliferate, omni-channels will become the new engine of growth. Omni-channel retailers need to optimally determine how to select suitable logistics providers (LSPs) to help maintain their competitive advantage. Although there are many methods to solve the problem of LSP selection, most of them overlook the decision maker's psychology. Most importantly, previous studies paid little attention to the probability of success for each candidate under each criterion. To compensate for these shortcomings, this study proposes a new method of logistics provider selection in an omni-channel environment. We present the model in three phases. The first phase involves computing the probability of success of each LSP with respect to each criterion through axiomatic design method. The second phase uses the perspective of the extended regret aversion/rejoice preference to develop a bounded rational decision making model for determining the criteria weights. In this phase, the regret/rejoice levels are treated as continuous parameters, whereby decision makers can regret and rejoice simultaneously. The final phase computes the expected perceived utility values to select the best LSP. To validate the capability of the proposed model, LSPs of six from a case study are ranked based on the proposed model, and the results are compared with the traditional regret and TOPSIS. The findings suggest that the proposed method provides more reasonable and reliable results, which are in line with the psychological behavior of human beings. (C) 2018 Elsevier B.V. All rights reserved.