Model for evaluating the E-commerce logistics service quality with hesitant fuzzy uncertain linguistic information

Abstract

In recent years, the electronic information and network technology has developed rapidly, meanwhile, E-commerce has been widely applied in society. Especially the online shopping, relying on its rich products, low price, no time and geographical restrictions and several other distinctive characteristics, which has absorbed attentions of many consumers. In recent years, China’s online retail market has seen a big growth. The market share of e-commerce has gradually increased and become a mainstay of China’s e-commerce development. However, with the fast growth of e-commerce, consumers’ requirements for enterprise service quality is also getting higher and higher. Logistics services is considered to be one of the three main inhibitions of e-commerce and improve logistics service quality has gradually become an important way of e-commerce enterprises to obtain competitive advantage. At present, the research on how to evaluate the quality of e-commerce logistics services has not yet formed a complete and scientific theoretical system and method. In this paper, we have proposed the induced hesitant fuzzy uncertain linguistic Einstein correlated average (IHFULECA) operator. Then, we used the IHFULECA operator to design the multiple attribute decision making problems to estimate the E-commerce logistics service quality. At last, an example is given to shown the effectiveness of the proposed method.