标题:Exploring an Interactive Value-Adding Data-Driven Model of Consumer Electronics Supply Chain Based on Least Squares Support Vector Machine
作者:Wan, Xiao-le; Zhang, Zhen; Rong, Xiao-xia; Meng, Qing-chun
作者机构:[Wan, Xiao-le; Meng, Qing-chun] Shandong Univ, Sch Management, Jinan 250100, Peoples R China.; [Wan, Xiao-le; Meng, Qing-chun] Shandong Univ, Res Ct 更多
通讯作者:Meng, QingChun
通讯作者地址:[Meng, QC]Shandong Univ, Sch Management, Jinan 250100, Peoples R China;[Meng, QC]Shandong Univ, Res Ctr Value Cocreat Network, Jinan 250100, Peoples R 更多
来源:SCIENTIFIC PROGRAMMING
出版年:2016
卷:2016
DOI:10.1155/2016/3717650
摘要:The differences in supply chains and their competitiveness depend on the differences in supply chain value creation systems. On the basis of the theory of value cocreation, this study investigates the interactive value creation of consumer electronics supply chains from the perspective of the interaction and added value created by the main value creation bodies in supply chains. Least squares support vector machine (LS-SVM) is innovatively introduced into the study on consumer electronics supply chains. A data-driven model is also established, the parameters of the method and kernel functions are optimized and selected, and an LS-SVM algorithm of consumer electronics supply chains is proposed to deal with the limited number of samples. Then, an empirical analysis of the top 10 smartphone supply chains in the Chinese market is conducted, and the LS-SVM model and other forecasting methods are compared. Results suggest that the LS-SVM model achieves a good predictive accuracy. This study also analyzes the value-adding structure of supply chains from the perspective of interaction and enriches the theory of value creation among supply chains. This study is conducive to helping consumer electronics enterprises to conduct market analyses and determine value growth points accurately.
收录类别:EI;SCOPUS;SCIE;SSCI
WOS核心被引频次:1
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994323914&doi=10.1155%2f2016%2f3717650&partnerID=40&md5=7bc62ac21937ce38dc43d9f6f1384fb8
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