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010   $z9783031298226
010   $z3031298225
010   $a9783031298233$b(electronic bk.)
010   $a3031298233$b(electronic bk.)
024 7 $a10.1007/978-3-031-29823-3
035   $a(MiAaPQ)EBC30605742
035   $a(Au-PeEL)EBL30605742
035   $a(DE-He213)978-3-031-29823-3
035   $a(PPN)272263826
035   $a(CKB)27169562400041
035   $a(OCoLC)1385451467
035   $a(EXLCZ)9927169562400041
100   $a20230622d2023      u|         0
101 0 $aeng
135   $aurcz#---auuuu
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData Analytics for Supply Chain Networks /$fedited by Niamat Ullah Ibne Hossain
205   $a1st ed. 2023.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023.
215   $a1 online resource (264 pages)
225 1 $aGreening of Industry Networks Studies,$x2543-0254 ;$v11
311 08$aPrint version: Ibne Hossain, Niamat Ullah Data Analytics for Supply Chain Networks Cham : Springer International Publishing AG,c2023 9783031298226 
320   $aIncludes bibliographical references and index.
327   $aChapter 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 capabilitieson the sustainability of maritime firms -- Chapter 10. Smart transportation logistics: Achieving supply chain efficiency with green initiatives.
330   $aThe objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
410  0$aGreening of Industry Networks Studies,$x2543-0254 ;$v11
606   $aEnvironmental economics
606   $aBusiness logistics
606   $aQuantitative research
606   $aSustainability
606   $aEnvironmental Economics
606   $aSupply Chain Management
606   $aData Analysis and Big Data
606   $aSustainability
615  0$aEnvironmental economics.
615  0$aBusiness logistics.
615  0$aQuantitative research.
615  0$aSustainability.
615 14$aEnvironmental Economics.
615 24$aSupply Chain Management.
615 24$aData Analysis and Big Data.
615 24$aSustainability.
676   $a658.50285
702   $aHossain$b Niamat Ullah Ibne$f1987-
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910734838603321
996   $aData Analytics for Supply Chain Networks$93873132
997   $aUNINA