Abstract
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.
Highlights
With the continuous support of government policies, e-commerce growth in China’s rural areas has led to the rapid acceleration of rural logistics development
18 service quality evaluation indexes in five dimensions were selected, and a questionnaire of last mile delivery service quality in a rural area was used as an example
Based on the weight of the evaluation indexes assigned by regression analysis in this case, AEIOU was used to classify the importance of the weight value
Summary
With the continuous support of government policies, e-commerce growth in China’s rural areas has led to the rapid acceleration of rural logistics development. From January to November 2019, China’s rural online retail sales reached 1522.9 billion yuan, up 19% year-on-year. China’s online retail sales of agricultural products reached 230.5 billion yuan, up 33.8 percent year on year. In 2018, there were over 9.8 million rural e-commerce businesses in China. By May 2019, more than 99.83% of villages had a direct postal service, and 95% of towns and townships had express delivery outlets. A three-level logistics distribution system covering counties, townships, and villages has been formed. Problems still exist, such as limited coverage of the distribution network, high logistics cost, low level of logistics
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