基于供应链管理视角大数据分析的挑战与机遇研究

Challenges and Opportunities of Big Data Analytics Based on Supply Chain Management

摘要: 目前对于供应链管理(SCM)的研究虽多种多样，但很少有人关注到利用大数据分析来提高供应链信息利用率，本文将通过调查大数据分析对企业和供应链环境中信息使用的潜在影响，为SCM的理论发展做出贡献。供应链中的企业有必要获得最新的、准确的和有意义的信息，本文的探索性研究将分析对SCM采用大数据分析所带来的机遇和挑战。虽然大数据分析在管理中越来越受关注，但仍然缺乏大量实证研究。由于大数据分析与SCM交叉研究的可对比材料有限，本文运用德尔菲研究方法，从数字化商业环境探讨新兴的转型趋势。德尔菲的研究发现有助于进一步了解现有知识，从企业和供应链角度确定与大数据分析相关的43个机会和挑战的影响因素，这些相关影响因素为此问题的研究搭建了第一个层面的集合，为大数据分析和SCM关系的进一步研究提供了基础。

Abstract: Despite the variety of supply chain management (SCM) research, little attention has been given to the use of Big Data Analytics for increased information exploitation in a supply chain. The purpose of this paper is to contribute to theory development in SCM by investigating the potential impacts of Big Data Analytics on information usage in a corporate and supply chain context. As it is imperative for companies in the supply chain to have access to up-to-date, accurate, and meaningful information, the exploratory research will provide insights into the opportunities and challenges emerging from the adoption of Big Data Analytics in SCM. Although Big Data Analytics is gaining increasing attention in management, empirical research on the topic is still scarce. Due to the limited availability of comparable material at the intersection of Big Data Analytics and SCM, the authors apply the Delphi research technique to portray the emerging transition trend from a digital business environment. The presented Delphi study findings contribute to extant knowledge by identifying 43 opportunities and challenges linked to the emergence of Big Data Analytics from a corporate and supply chain perspective. These constructs equip the research community with a first collection of aspects, which could provide the basis to tailor further research at the nexus of Big Data Analytics and SCM.