Volume List  / Volume 11 (1)



DOI: 10.7708/ijtte.2021.11(1).04

11 / 1 / 75 - 93 Pages


Qingmin Zhang - School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, 3 Wenyuan Road, Qixia District, Nanjing City, Jiangsu Province, China -

Yisu Li - School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, 3 Wenyuan Road, Qixia District, Nanjing City, Jiangsu Province, China -

Qianxiao Cai - School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, 3 Wenyuan Road, Qixia District, Nanjing City, Jiangsu Province, China -


Recently, the last-mile delivery problem of rural e-commerce has emerged and became a bottleneck issue, due to the booming development of rural e-commerce which drives the vigorous growth of upstream agricultural products and downstream industrial products. This paper takes rural areas of China as a case study to discuss the last-mile delivery cost under crowdsourcing logistics. Owing to the absence of theoretical guidance on rural crowdsourcing logistics, the paper firstly intends to explore the theoretical framework of rural crowdsourcing logistics in terms of multi-level perspective (MLP). Then, the couriers’ willingness coefficient is introduced to develop a mathematical optimization model containing time windows and vehicle capacity constraints, and the heuristic algorithm is applied to solve the model. The final results indicate that the transportation cost and Vehicle Miles Traveled (VMT) can be saved 23.85% and 37.38% respectively, compared with conventional rural logistics. Besides, analysis indicates that under certain conditions the approach of crowdsourcing delivery can be economically competitive and has valuable implication for unchoking the last-mile delivery problem of other similar rural regions.

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The paper was done within the research project (20BGL182): Mechanism, path, and effect of sustainable development of rural e-commerce clusters in China under digital rural strategy, which was funded by The National Social Science Fund of China (NSSFC). Also, the authors are grateful for the support and help of the Courier station manager.


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