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001			239337
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007			cr nn 008mamaa
008			210625s2021 sz | o |||| 0|eng d
020			_a9783030692650
024	7		_a10.1007/978-3-030-69265-0 _2doi
040			_aES-VaU _bspa _cES-VaU _dES-VaU
050		4	_aHD38.5 _b2021 EB
245	0	0	_aSupply Chain Management in Manufacturing and Service Systems : _bAdvanced Analytics for Smarter Decisions _cedited by Sharan Srinivas, Suchithra Rajendran, Hans Ziegler
250			_a1st ed. 2021.
264		1	_aCham _c2021 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aInternational Series in Operations Research & Management Science _x2214-7934 _v304
505	0		_aAn Overview of Decisions, Performance and Analytics in Supply Chain Management -- Intelligent Digital Supply Chains -- Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design -- Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach -- Improving Service Supply Chain of Internet Services by Analyzing Online Customer Reviews -- An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration -- A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service -- Pro-Active Strategies in Online Routing -- Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces.
520			_aManagement of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization. In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-69265-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Business_2021
999			_c239337 _d239337