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001 978-3-031-51241-4
003 DE-He213
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008 240527s2024 sz | s |||| 0|eng d
020 _a9783031512414
_9978-3-031-51241-4
024 7 _a10.1007/978-3-031-51241-4
_2doi
050 4 _aHD38.5
072 7 _aKJMV8
_2bicssc
072 7 _aBUS087000
_2bisacsh
072 7 _aKJMV8
_2thema
100 1 _aIvanov, Dmitry.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_977486
245 1 0 _aIntroduction to Supply Chain Analytics
_h[electronic resource] :
_bWith Examples in AnyLogic and anyLogistix Software /
_cby Dmitry Ivanov.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 167 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aClassroom Companion: Business,
_x2662-2874
505 0 _aAnalytics and model-based decision-making support -- Demand Forecasting, Production Planning and Inventory Control -- Discrete-Event Simulation of manufacturing processes and inventory control -- Facility location planning and network optimization -- Supply chain risk and resilience analytics.
520 _aThe book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook “Global Supply Chain and Operations Management”, it addresses the topics of supply chain analytics in more depth. The book describes descriptive, predictive, and prescriptive supply chain analytics explaining methodologies, illustrating method applications with the use of training exercises, and providing numerous examples in AnyLogic and anyLogistix software. Throughout the book, numerous practical examples and short case studies are given to illustrate theoretical concepts. Along with AnyLogic and anyLogistix model development guidelines and examples, the book has two other distinct features. First, it reviews and explains novel frameworks and concepts related to data-driven decision-making and digital twins. Second, it shows how to use analytics to improve supply chain resilience. Without relying heavily on mathematical derivations, the book offers a structured presentation and explanation of major supply chain analytics techniques and principles in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering backgrounds. Graduate/Ph.D. students and supply chain professionals alike would benefit from a structured and didactically-oriented concise presentation of the concepts, principles, and methods of supply chain analytics. Providing graduate students and supply chain managers with working knowledge of basic and advanced supply chain analytics, this book contributes to improving knowledge-awareness of decision-making in increasingly data-driven and digital environments. The book is supplemented by a companion website offering interactive exercises with the use of AnyLogic and anyLogistix software as well as Spreadsheet Modeling.
650 0 _aBusiness logistics.
_961225
650 0 _aQuantitative research.
650 0 _aProduction management.
_967141
650 0 _aOperations research.
_957943
650 1 4 _aSupply Chain Management.
_966371
650 2 4 _aData Analysis and Big Data.
650 2 4 _aLogistics.
_968350
650 2 4 _aProduction.
_967142
650 2 4 _aOperations Management.
_967304
650 2 4 _aOperations Research and Decision Theory.
_967143
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031512407
776 0 8 _iPrinted edition:
_z9783031512421
830 0 _aClassroom Companion: Business,
_x2662-2874
_976652
856 4 0 _uhttps://doi.org/10.1007/978-3-031-51241-4
912 _aZDB-2-BUM
912 _aZDB-2-SXBM
999 _c60148
_d60148