The advent of e-commerce has led to a rapid acceleration of rural logistics development in China. To enhance green and sustainable development of rural logistics, it is necessary to improve the service quality of the rural last mile delivery and analyze service quality evaluation indexes. An integrated methodology combing fuzzy comprehensive evaluation (FCE) and the interpretative structural model (ISM) is presented in the current paper to reveal the relationship between the service quality evaluation indexes of the rural last mile delivery. A total of 18 logistics service quality evaluation indexes in five dimensions are selected. The FCE is used to measure the service quality of rural delivery in an empirical research area, and the weight of each evaluation index is assigned by regression analysis. The ISM is adopted to judge the hierarchical structure of indexes, and a five-layer hierarchy is obtained. The results show that it is necessary to first focus on improving the evaluation indexes of accuracy of goods arrival and timely customer service response. In the case of Shunfeng Express, the company needs to additionally improve the timeliness and rationality of damaged or lost processing goods. Some countermeasures and suggestions are put forward. The proposed integrated method helps to reveal the key service quality evaluation indexes and the areas needing improvement. The use of regression analysis within the FCE method allows the estimation of weights in a relatively objective way. This research provides theoretical support for improving the service quality and customers' satisfaction of the rural last mile delivery, and enhancing the green and sustainable development of rural logistics.

The development of rural e-commerce has rapidly driven the development of rural logistics in China. Improving the service quality of the last mile delivery is an important measure to promote the sustainable development of rural e-commerce logistics. However, such work is challenging because the current rural last mile delivery is inefficient and unsustainable and is influenced by a set of interacting factors. It is necessary to explore the relationships among the sustainability influencing factors of rural last mile delivery. A total of 15 sustainability influencing factors are selected. The improved fuzzy analytic hierarchy process (FAHP) is used to assign the weights of the factors and then the interpretative structural model (ISM) is used to determine the hierarchical structure of each factor. The driving force-dependency quadrant graph is constructed by cross-impact matrix multiplication (MICMAC). The research results show that four factors, including convenience of returning goods, integrity of goods, advance reservation of goods pickup, and delivery costs, are the most basic factors affecting the sustainability of rural last mile delivery and are the deepest and most indispensable factors. This research provides valuable information for decision makers to develop proactive strategies and reinforcement policies to improve the service quality of rural last mile delivery, which could promote the sustainable development of rural logistics.