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Owing to the rapidly changing customer preferences and demands, the e-commerce industry encounters various uncertainties and risks to enhance competitiveness. Quality function deployment (QFD) is a commonly used model, which can translate customer requirements (CRs) into products or service design requirements (DRs), to improve competitiveness by launching a new business. To measure the uncertainties and behavioral risk factors in e-commerce service design, we propose a new QFD model based on the Kano model and TOPSIS method by considering the behavior of experts with prospect theory under interval type-2 fuzzy linguistic environment. The categories of CRs are identified using the Kano model and the weights of CRs are determined dynamically according to the development stages of enterprises. The priorities of DRs are ranked using the extended TOPSIS method with prospect theory. A case study of China's e-commerce service design is used to show the application of the proposed QFD model. The prioritizing results show the flexibility of the proposed model on determining the weights of CRs and the priorities of DRs for enterprises at different development stages. • A quality function deployment model is proposed under linguistic environment. • Identify the attribute category of CRs using the interval type-2 fuzzy Kano model. • Determine the weights of CRs based on the development stage of enterprises. • Rank DRs by an extended TOPSIS method considering the behavioral factors. [ABSTRACT FROM AUTHOR]

Large-scale group decision making (LSGDM) or complex group decision making (GDM) problems are very commonly encountered in actual life, especially in the era of data. At present, double hierarchy hesitant fuzzy linguistic term set is a reasonable linguistic expression when describing some complex linguistic preference information. In this paper, we develop a consensus reaching process for LSGDM with double hierarchy hesitant fuzzy linguistic preference relations. To ensure the implementation of consensus reaching process, we also propose the similarity degree-based clustering method, the double hierarchy information entropy-based weights-determining method and the consensus measures. Finally, we apply our model to deal with a practical problem that is to evaluate Sichuan water resource management and make some comparisons with the existing approaches. [ABSTRACT FROM AUTHOR]