Big data analytics in logistics and supply chain management: Certain investigations for research and applications
TLDR
In this article, the authors classify the literature on the application of big data business analytics (BDBA) on logistics and supply chain management (LSCM) based on the nature of analytics (descriptive, predictive, prescriptive) and the focus of the LSCM (strategy and operations).About:
This article is published in International Journal of Production Economics.The article was published on 2016-06-01 and is currently open access. It has received 938 citations till now. The article focuses on the topics: Analytics & Business analytics.read more
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Critical analysis of Big Data challenges and analytical methods
TL;DR: In this article, the authors present a state-of-the-art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/employed by organizations to help others understand this landscape with the objective of making robust investment decisions.
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The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics
TL;DR: This paper analyses recent literature and case-studies seeking to bring the discussion further with the help of a conceptual framework for researching the relationships between digitalisation and SC disruptions risks and emerges with an SC risk analytics framework.
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The future of manufacturing industry: a strategic roadmap toward Industry 4.0
TL;DR: In this paper, the authors conduct a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0.
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“Industrie 4.0” and Smart Manufacturing - A Review of Research Issues and Application Examples
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Big data and predictive analytics for supply chain and organizational performance
Angappa Gunasekaran,Thanos Papadopoulos,Rameshwar Dubey,Samuel Fosso Wamba,Stephen J. Childe,Benjamin T. Hazen,Shahriar Akter +6 more
TL;DR: In this article, the authors investigated the impact of big data and predictive analytics (BDPA) assimilation on supply chain (SCP) and organizational performance (OP) and found that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance.
References
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TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
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A framework of sustainable supply chain management: moving toward new theory
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TL;DR: In this article, a large-scale literature review and use conceptual theory building to introduce the concept of sustainability to the field of supply chain management and demonstrate the relationships among environmental, social, and economic performance within a supply chain context.
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TL;DR: A literature review of the applications of Analytic Hierarchy Process, which aims to provide a ready reference on AHP, and act as an informative summary kit for the researchers and practitioners for their future work.
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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
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Multi-criteria decision making approaches for supplier evaluation and selection: A literature review
TL;DR: Evidence is provided that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.