Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 2, 2023


Pages


DOI

Article

A Green Supply Chain Management Strategy for E-Commerce Based on Multiple Blockchain Technology

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Authors

Min Qu Affiliation:
College of Digital Commerce, Department of Electronic Commerce, Jiangsu Vocational Institute of Commerce, Nanjing, Jiangsu, 211168, China.
, Tianpei Xu Affiliation:
College of Communication, Department of Educational Technology, Hulunbuir University, Hulunbuir, Inner Mongolia, 021008, China.
and Changzhi Ju Affiliation:
College of Digital Commerce, Jiangsu Vocational Institute of Commerce, Nanjing, Jiangsu, 211168, China.


Abstract

In this paper, firstly, the e-commerce green supply chain management strategy of multivariate blockchain is explored, and digital assets are traded on the e-commerce supply chain platform through the information anchoring model. Secondly, the Diffie-Hellman algorithm is used to generate the key, the AES algorithm is used to encrypt the information, and the account data, transaction data and IoT data, are stored in three independent chains. Finally, the selection strategies of different e-commerce sales models and the green supply chain management strategies of e-commerce platforms are visually analyzed through numerical arithmetic examples. The results show that when E0 = 10, it is optimized by the ecological R&D efforts of supply chain members. When E0 = 50, the greenness of the product is decreasing. When it finally tends to the steady state, E∞C > E∞BR > E∞MR. The three green supply chain management models proposed in this study are conducive to enhancing consumer utility and in line with the sustainable development strategy.


Keywords

Multivariate blockchain, E-commerce, Green supply chain, Information anchoring model, AES algorithm, 78-02


Citation

Qu, M., Xu, T., & Ju, C. (2023). A green supply chain management strategy for e-commerce based on multiple blockchain technology. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00450

Published by: Engineering Journals

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