Data analytics for supply chain networks / Niamat Ullah Ibne Hossain, editor.
Hossain, Niamat Ullah Ibne, 1987-
2023
HD38.5
Available Online

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Title Data analytics for supply chain networks / Niamat Ullah Ibne Hossain, editor.
ISBN 9783031298233 (electronic bk.)
3031298233 (electronic bk.)
3031298225
9783031298226
DOI https://doi.org/10.1007/978-3-031-29823-3
Imprint Cham, Switzerland : Springer, 2023.
Language English
Description 1 online resource.
Other Standard Identifiers 10.1007/978-3-031-29823-3 doi
Call Number HD38.5
Dewey Decimal Classification 658.5
Summary The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed June 28, 2023).
Added Author Hossain, Niamat Ullah Ibne, 1987-
Series Greening of industry networks studies ; v. 11.
Available in Other Form Print version: 9783031298226
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Chapter 1. The state of art of data analytics in resilience and sustainability management
Chapter 2. Enhancing the viability of green supply chain management initiatives leveraging data fusion technique
Chapter 3. Supply chain sustainability and supply chain resilience: A performance measurement framework with empirical validation
Chapter 4. An assessment of decision-making in resilient and sustainable project between literature and practice
Chapter 5. Barriers for Lean Supply Chain Management and their Overcoming Strategies in Context of the Indian Automobile Industry
Chapter 6. Prioritizing Sustainability Criteria of Green Supply Chains using Best Worst Method
Chapter 7. Economic performance analysis of resilient and sustainable supply chain: Adoption of electric vehicles as a sustainable logistics option
Chapter 8. Integrating circular economy and reverse logistics for achieving sustainable dairy operations
Chapter 9. The impact of big data analytics capabilities on the sustainability of maritime firms
Chapter 10. Smart transportation logistics: Achieving supply chain efficiency with green initiatives.

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