Abstract
At present, with the continuous development of the intelligent system, it is used in many industries. In e-commerce industry, the intelligent system has also been used, especially in supplier management. Based on the machine learning theory, this paper studies the optimization of the supplier management intelligent system of cross-border e-commerce platforms. Based on the wisdom algorithm and machine learning perspective, the optimization of cross-border e-commerce platform supplier credit system is studied in this paper. Firstly, the calculation of the traditional supplier credit evaluation is optimized by introducing the decision matrix algorithm of the difference matrix and the cloud model evaluation method. Then a multi-objective joint decision model of supplier selection and order allocation is established, and the multi-objective evolutionary algorithm combined with actual examples is applied to verify the effectiveness and feasibility of the algorithm and model. Finally, the decision makers’ preferences are integrated into the intelligent decision-making, and the cloud model evaluation method is adopted. The rough set and gray relational analysis mathematical tools are used to construct the procurement supply evaluation system. The research results show that the comparison of the three general indicators of the procurement supply chain can be obtained through the cloud model evaluation calculation, which indirectly reflects the preference decision weights of the three objective functions of the cross-border e-commerce supplier selection and order allocation multi-objective optimization model. This indicates that the procurement supply evaluation system constructed in this paper has achieved the purpose of scientific evaluation and selection of suppliers, and has played a theoretical reference role for supplier management of cross-border e-commerce platform.
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14 November 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s10257-022-00588-x
References
Ahmed RR (2015) Supply chain management: milk collection & distribution system in Pakistan. Eur J Sci Res 39(4):130–142
Feng X, Liu Y, Gao Y (2015) Food safety system construction based on supply chain management. Bus Econ 10(9):78–85
Gan ST (2017) Optimization and establishment of sustainable supply chain performance evaluation model for cross-border e-commerce. Value Eng 64(32):369–372
Ghose A (2009) Internet exchanges for used goods: an empirical analysis of trade patterns and adverse selection. MIS Q 33(2):263–291
Kim DJ (2012) An investigation of the effect of online consumer trust on expectation, satisfaction, and post-expectation. IseB 10(2):219–240
Lamba K, Singh SP (2017) Big data in operations and supply chain management: current trends and future perspectives. Prod Plan Control 28(11–12):877–890
Lin F-T, Wu H-Y, Tran TNN (2015) Internet banking adoption in a developing country: an empirical study in Vietnam. IseB 13(2):267–287
Luo B, Lin Z (2013) A decision tree model for herd behavior and empirical evidence from the online P2P lending market. IseB 11(1):141–160
Pappas IO, Mikalef P, Giannakos MN et al (2018) Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. IseB 16(3):479–491
Rong DI, Zhao YJ, Hong-Xin YU et al (2017) Research on the supply chain management optimization in pharmaceutical circulation enterprises. Technoeconomics Manag Res 7(3):14–18
Sanderson J, Lonsdale C, Mannion R et al (2015) Towards a framework for enhancing procurement and supply chain management practice in the NHS: lessons for managers and clinicians from a synthesis of the theoretical and empirical literature. Health Technol Assess 3(18):12–16
Shan SN (2017) Research on the personnel training mode on cross-border e-commerce based on structural reform of the supply front. J Hubei Corresp Univ 36(7):230–256
Vaidya K, Campbell J (2016) Multidisciplinary approach to defining public e-procurement and evaluating its impact on procurement efficiency. Inf Syst Front 18(2):1–16
Wang YY (2018) Research on the training mode of innovative talents in cross-border e-commerce from the perspective of “supply-side structural reform”. J Heilongjiang Vocat Inst Ecol Eng 10(4):21–25
Yang LJ (2016) The supply-side reform of circulation enterprises based on supply chain optimization. China Bus Mark 5(1):42–46
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Yang, Y. RETRACTED ARTICLE: Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning. Inf Syst E-Bus Manage 18, 851–870 (2020). https://doi.org/10.1007/s10257-019-00402-1
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DOI: https://doi.org/10.1007/s10257-019-00402-1