Supply Chain Management in Manufacturing and Service Systems : Advanced Analytics for Smarter Decisions / edited by Sharan Srinivas, Suchithra Rajendran, Hans Ziegler
(International Series in Operations Research & Management Science. ISSN:22147934 ; 304)
| Publisher | (Cham : Springer International Publishing : Imprint: Springer) |
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| Year | 2021 |
| Edition | 1st ed. 2021. |
| Authors | Srinivas, Sharan editor Rajendran, Suchithra editor Ziegler, Hans editor SpringerLink (Online service) |
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| Links to the text | Location | Volume | Call No. | Barcode No. | Status | Comments | ISBN | Printed | Restriction | Reserve |
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| Links to the text | Library Off-campus access |
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OB00162428 | Springer Business and Management eBooks (電子ブック) | 9783030692650 |
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| Material Type | E-Book |
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| Media type | 機械可読データファイル |
| Size | XVIII, 278 p. 99 illus., 79 illus. in color : online resource |
| Notes | An 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 Management 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 HTTP:URL=https://doi.org/10.1007/978-3-030-69265-0 |
| Subjects | LCSH:Business logistics LCSH:Operations research LCSH:Management science LCSH:Quantitative research LCSH:Industrial engineering LCSH:Production engineering LCSH:Production management LCSH:Service industries FREE:Supply Chain Management FREE:Operations Research, Management Science FREE:Data Analysis and Big Data FREE:Industrial and Production Engineering FREE:Production FREE:Services |
| Classification | LCC:HD38.5 DC23:658.7 |
| ID | 8000076331 |
| ISBN | 9783030692650 |
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