Hybrid Kano-DEMATEL-TOPSIS model based benefit distribution of multiple logistics service providers considering consumer service evaluation of segmented task

Abstract

Assessment of the contribution rates of third-party logistics (3PL) providers according to service quality is a highly uncertain and complex problem. The literature mainly focuses on a single multi-criteria decision making (MCDM) method based overall performance evaluations of 3PL service providers, whereas distinct operational performance measurements and the association of this service quality have not received enough attention. To efficiently solve the evaluation problem, we develop the Kano-DEMATEL-TOPSIS method and apply it in logistics service supply chain (LSSC) management. We incorporate Kano analysis and service blueprint to obtain the weight of service quality elements capturing customer feedback on the performance of segmented task. Considering the dependence of the segmented task, we put forward the DEMATE method, which gives the importance of segmented tasks in the service process. Due to the different risk preferences of logistics service providers, the entropy-based TOPSIS with adjustable contribution rates is proposed to resolve individual risk compensation. The hybrid method can better solve the problem of benefit distribution comprising segmentedtasks evaluation and individual risk compensation in LSSC.