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Understanding the role of big data analytics for coordination of electronic retail service supply chain

Fatao Wang (Hebei University of Economics and Business, Shijiazhuang, China)
Di Wu (Shanghai University of Finance and Economics, Shanghai, China)
Hongxin Yu (Shanghai Business School, Shanghai, China)
Huaxia Shen (Shanghai Business School, Shanghai, China)
Yuanjun Zhao (Shanghai Lixin University of Accounting and Finance, Shanghai, China)

Journal of Enterprise Information Management

ISSN: 1741-0398

Article publication date: 29 April 2021




Based on the typical service supply chain (SSC) structure, the authors construct the model of e-tailing SSC to explore the coordination relationship in the supply chain, and big data analysis provides realistic possibilities for the creation of coordination mechanisms.


At the present stage, the e-commerce companies have not yet established a mature SSC system and have not achieved good synergy with other members of the supply chain, the shortage of goods and the greater pressure of express logistics companies coexist. In the case of uncertain online shopping market demand, the authors employ newsboy model, applied in the operations research, to analyze the synergistic mechanism of SSC model.


By analyzing the e-tailing SSC coordination mechanism and adjusting relevant parameters, the authors find that the synergy mechanism can be implemented and optimized. Through numerical example analysis, the authors confirmed the feasibility of the above analysis.


Big data analysis provides a kind of reality for the establishment of online SSC coordination mechanism. The establishment of an online supply chain coordination mechanism can effectively promote the efficient allocation of supplies and better meet consumers' needs.



This study was funded by National Social Science Fund of China (Grant No. 18CGL015).


Wang, F., Wu, D., Yu, H., Shen, H. and Zhao, Y. (2021), "Understanding the role of big data analytics for coordination of electronic retail service supply chain", Journal of Enterprise Information Management, Vol. ahead-of-print No. ahead-of-print.



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