期刊文献+

大数据技术在粤港澳电商企业供应链成本控制中的应用研究 被引量:4

Research on the Application of Big Data Technology in the Supply Chain Cost Control of the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)
在线阅读 下载PDF
导出
摘要 随着互联网的运用,越来越多的电商企业发展起来,粤港澳大湾区得天独厚的地理和环境优势,加快了电商企业的发展。然而,随着国际贸易环境的恶化,国内电商企业的竞争加剧,电商企业的物流成本无疑压缩了企业的利润空间。在此背景下,如何运用大数据技术对电商企业的供应链成本进行控制,是本次研究的主要内容。文章基于粤港澳大湾区电子商务企业发展面临的问题,构建大数据背景下粤港澳大湾区电子商务企业供应链成本控制模式,阐述基于大数据的粤港澳大湾区电子商务企业供应链成本控制途径,最后提出相关建议,为运用大数据提升供应链成本控制能力提供理论依据。 With the use of the Internet, more and more E-commerce companies have developed. The unique geographical and environmental advantages of the Guangdong-Hong Kong-Macao GBA have accelerated the development of E-commerce companies. However, with the deterioration of the international trade environment, competition among domestic e-commerce companies has intensified, and the logistics costs of e-commerce companies have undoubtedly compressed their profit margins. How to use big data technology to control the supply chain costs of E-commerce companies is the main content of this research.Based on the above problems, this article constructs a supply chain cost control model for E-commerce enterprises and elaborates the supply chain costs of E-commerce enterprises in the Guangdong-Hong Kong-Macao GBA based on big data. Finally it puts forward relevant suggestions to provide a theoretical basis for using big data to improve the cost control ability of the supply chain.
作者 刘琦 LIU Qi(Guangdong University of Science and Technology,523083,Dongguan,Guangdong,China)
机构地区 广东科技学院
出处 《特区经济》 2022年第6期76-79,共4页 Special Zone Economy
基金 大数据技术在粤港澳大湾区电商企业供应链成本控制中的应用研究,中国物流学会(项目编号:2020CSLKT3-219) 东莞市跨境电子商务综合试验区的政策效应研究,广东科技学院(项目编号:GKY-2021KYYBW-14) 基于大数据技术的东莞市跨境电商产业链培育研究,广东科技学院(项目编号:GKY-2021KYYBW-13)。
关键词 大数据 粤港澳电商企业 供应链 成本控制 Big data E-Commerce Enterprises in Guangdong Hong Kong and Macao GBA Supply Chain Cost Control
  • 相关文献

参考文献3

二级参考文献20

  • 1Nada R Sanders.Big Data Driven Supply Chain Management: A Framework for Implementing Analytics and Turning Information Into Intelligence [M]. London:Pearson FF Press, 2014.
  • 2Viktor Mayer-Schonberger,Kenneth Cukler.Big Data: A Revolution That Will Transform How We Live, Work and Think[M].London:Kodder Export, 2013.
  • 3Chopra S, Meindl P. Supply Chain Management Strategy, Planning, and Op-eration[M].北京:清华大学出版社,2008.
  • 4Sezen B. Relative effects of design, integration and information sharing on supply chain performance [J]. Supply Chain Management: An International Journal, 2008,13(3):233-240.
  • 5Lee H L.Creating value through supply chain integration [J].Supply Chain Management Review, 2000, 4(4):30-36.
  • 6Suhan N. Knowledge management in the age of cloud computing and web 2.0: experiencing the power of disruptive innovations [J].International Jour- nal of Inforrnation Management, 2013, 33(1): 160-165.
  • 7Fomell C, Larcher F E. Valuating structural equation models with unob- servable variables and measurement error [J]. Journal of Marketing Research, 1981,18(1):29-50.
  • 8罗琼.电子商务与快递行业供应链协同发展研究[D].重庆交通大学,2012.
  • 9张以彬,陈俊芳.供应链的风险识别框架及其柔性控制策略[J].工业工程与管理,2008,13(1):47-52. 被引量:27
  • 10叶飞,薛运普.供应链伙伴间信息共享对运营绩效的间接作用机理研究——以关系资本为中间变量[J].中国管理科学,2011,19(6):112-125. 被引量:50

共引文献26

引证文献4

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部