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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…
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.
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.
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.
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.
This paper aims to assess the links among these supply chain constructs by conducting a full-scale systematic review of all supply chain management (SCM) literature…
This paper aims to assess the links among these supply chain constructs by conducting a full-scale systematic review of all supply chain management (SCM) literature reviews published in ten leading logistics, SCM and operations management journals from 1989 to 2012. Collaboration and integration are as central to SCM as risk and performance management.
The authors apply content analysis to execute the systematic literature review on the sample of 103 articles, supplemented by contingency analysis. These approaches guarantee a replicable, rigorous and transparent research process and minimize researcher bias. The analytical categories required for the content analysis are defined along the constructs of collaboration/integration and risk/performance.
As can be expected, the review highlights the key role of the two constructs in SCM. In this light, the research claims to provide statistical evidence of a link between the constructs of collaboration/integration and risk/performance, most notably between collaboration and performance, information sharing and rewards sharing, as well as integration and supply chain performance.
The study assesses the link between the constructs of collaboration/integration and risk/performance through research embedded in literature reviews, pinpointing research gaps and potential future research directions in the field. Contributing to SCM theory building, a thorough review provides statistical proof of the link between collaboration/integration and risk/performance.
Although numerous literature reviews have been conducted in the past on the SCM constructs of collaboration/integration and risk/performance, no full review of literature reviews aiming to test a theoretical link in the here presented form has yet been undertaken to the authors’ knowledge.