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Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management

大数据 供应链 数据科学 分析 供应链管理 知识管理 德尔菲法 背景(考古学) 计算机科学 多样性(控制论) 实证研究 业务 营销 数据挖掘 认识论 哲学 古生物学 人工智能 生物
作者
Florian Kache,Stefan Seuring
出处
期刊:International Journal of Operations & Production Management [Emerald (MCB UP)]
卷期号:37 (1): 10-36 被引量:694
标识
DOI:10.1108/ijopm-02-2015-0078
摘要

Purpose 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. Design/methodology/approach 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. Findings Portraying 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. Research limitations/implications 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. Originality/value The research adds to the existing knowledge base as no empirical research has been presented so far specifically assessing opportunities and challenges on corporate and supply chain level with a special focus on the implications imposed through Big Data Analytics.
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