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Global Supply Chain and Operations Management: A Decision-Oriented Introduction to the Creation of Value Second Edition 2019 [Minkštas viršelis]

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  • Formatas: Paperback / softback, 578 pages, aukštis x plotis: 235x155 mm, weight: 914 g, 258 Illustrations, black and white; XXVI, 578 p. 258 illus., 1 Paperback / softback
  • Serija: Springer Texts in Business and Economics
  • Išleidimo metai: 20-Dec-2018
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030068307
  • ISBN-13: 9783030068301
Kitos knygos pagal šią temą:
Global Supply Chain and Operations Management: A Decision-Oriented Introduction to the Creation of Value Second Edition 2019Didesnis paveikslėlis
  • Formatas: Paperback / softback, 578 pages, aukštis x plotis: 235x155 mm, weight: 914 g, 258 Illustrations, black and white; XXVI, 578 p. 258 illus., 1 Paperback / softback
  • Serija: Springer Texts in Business and Economics
  • Išleidimo metai: 20-Dec-2018
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030068307
  • ISBN-13: 9783030068301
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783030068301.html
The second edition of this textbook comprehensively discusses global supply-chain and operations management, combining value creation networks and interacting processes. It focuses on the operational roles in the networks and presents the quantitative and organizational methods needed to plan and control the material, information and financial flows in the supply chain. Each chapter starts with an introductory case study, and numerous examples from various industries and services help to illustrate the key concepts. The book explains how to design operations and supply networks and how to incorporate suppliers and customers. It also examines matching supply and demand, which is a core aspect of tactical planning, before turning to the allocation of resources for fulfilling customer demands.





This second edition features three new chapters: Supply Chain Risk Management and Resilience, Digital Supply Chain, Smart Operations, and Industry 4.0, and Pricing and Revenue-Oriented Capacity Allocation. These new chapters provide the structured knowledge on the principles, models, and technologies for managing the supply-chain risks and improving supply-chain and operations performance with the help of digital technologies such as Industry 4.0, additive manufacturing, Internet-of-Things, advanced optimization methods and predictive analytics. The existing chapters have been updated and new case studies have been included. In addition, the preface provides guidelines for instructors on how to use the material for different courses in supply-chain and operations management and at different educational levels, such as general undergraduate, specialized undergraduate, and graduate courses. The companion website www.global-supply-chain-management.de has also been updated accordingly. In addition, the book is now supported by e-manuals for supply-chain and operations simulation and optimization in AnyLogic and anyLogistix.





Providing readers with a working knowledge of global supply-chain and operations management, with a focus on bridging the gap between theory and practice, this textbook can be used in core, special and advanced classes. It is intended for broad range of students and professionals involved in supply-chain and operations management. 
Part I Introduction to Supply Chain and Operations Management
1 Basics of Supply Chain and Operations Management
3(14)
1.1 Introductory Case Study: The Magic Supply Chain and the Best Operations Manager
4(1)
1.2 Basic Definitions and Decisions
5(6)
1.2.1 The Transformation Process, Value Creation, and Operations Function
5(2)
1.2.2 Supply Chain Management
7(2)
1.2.3 Decisions in Supply Chain and Operations Management
9(2)
1.3 Careers and Future Challenges in Supply Chain and Operations Management
11(4)
1.4 Key Points
15(1)
Bibliography
16(1)
2 Examples from Different Industries, Services, and Continents
17(28)
2.1 Examples of Operations and Supply Chains in Manufacturing
17(7)
2.1.1 Nike: Sourcing Strategy in the Integrated Supply Chain
17(2)
2.1.2 Dangote Cement: Establishing Sophisticated Supply Chain Management in Africa
19(3)
2.1.3 Toyota: Supply Chain Disruption Management
22(1)
2.1.4 Tesla Gigafactory
23(1)
2.2 Examples of Operations and Supply Chains in Services
24(9)
2.2.1 SCOM in Restaurants: Case Study Starbucks Corporation
24(2)
2.2.2 Operations Management at Airport Madrid/Barajas
26(2)
2.2.3 Time-Critical Supply Chains: Disaster Management and Humanitarian Logistics
28(3)
2.2.4 Operations Issues in Car Sharing
31(1)
2.2.5 REWE: Expanding the Logistics Network
32(1)
2.3 Examples of e-Operations and Supply Chains
33(5)
2.3.1 Fab.com
33(4)
2.3.2 Homeplus: The Store Comes to Your Home
37(1)
2.4 Examples of Digital Supply Chains and Smart Operations
38(3)
2.4.1 Amazon Robots
38(1)
2.4.2 Adidas "Speedfactory": 3D Printing and Industry 4.0 in Supply Chain and Operations Management
39(1)
2.4.3 Predictive Analytics and Machine Learning: RueLaLa and Pharmapacks
40(1)
Bibliography
41(4)
3 Processes, Systems, and Models
45(36)
3.1 Introductory Case-Study: AirSupply
45(4)
3.1.1 E-procurement
46(1)
3.1.2 Vendor-Managed Inventory
47(1)
3.1.3 Implementation
48(1)
3.2 Business Process Management
49(4)
3.2.1 Process Optimization and Re-engineering
49(2)
3.2.2 Business Process Modelling
51(2)
3.3 Management Information Systems
53(10)
3.3.1 Role of Information Technology in Supply Chain and Operations Management
53(1)
3.3.2 Types of Management Information Systems
53(1)
3.3.3 Management Information Systems and Organization
54(2)
3.3.4 ERP Systems
56(1)
3.3.5 APS Systems
57(1)
3.3.6 SCEM and RFID
58(2)
3.3.7 Business Analytics and E-Business
60(3)
3.4 Problem Solving Methods and Research Methodologies
63(11)
3.4.1 Problems, Systems, and Decision-Making
63(3)
3.4.2 Models and Modeling
66(1)
3.4.3 Model-Based Decision Making
67(3)
3.4.4 Quantitative Models and Operations Research
70(1)
3.4.5 Integrated Decision Making Support
70(2)
3.4.6 Research Methodologies
72(2)
3.5 Integration of Business Analytics, Simulation, and Optimization
74(2)
3.6 Key Points
76(1)
Bibliography
77(4)
Part II Designing Operations and Supply Network: Strategic Perspective
4 Operations and Supply Chain Strategy
81(30)
4.1 Introductory Case-Study "Quick and Affordable": Zara, UNIQLO & Primark
81(4)
4.1.1 Zara's Three Success Factors: Speed, Speed, and Speed
81(2)
4.1.2 UNIQLO: Basic, Casual Wear at Top Quality
83(1)
4.1.3 Primark: It's All About Money
84(1)
4.2 Operations and Supply Chain Strategies
85(6)
4.2.1 Value Added and Costs
85(1)
4.2.2 Operations Strategies
86(1)
4.2.3 Supply Chain Strategies and "Strategic Fit"
87(4)
4.3 Supply Chain Coordination
91(9)
4.3.1 Bullwhip Effect
91(4)
4.3.2 Vendor-Managed Inventory
95(3)
4.3.3 Collaborative Planning, Forecasting and Replenishment
98(1)
4.3.4 Supply Chain Contracting
99(1)
4.4 Supply Chain Resilience and Sustainability
100(7)
4.4.1 Supply Chain Sustainability: Examples of Coca-Cola and Mercadona
101(3)
4.4.2 Supply Chain Resilience and Ripple Effect
104(3)
4.5 Key Points
107(1)
Bibliography
108(3)
5 Sourcing Strategy
111(24)
5.1 Introductory Case Study "New Logistics Concept (NLK: Das Neue Logistik Konzept) at Volkswagen"
111(3)
5.2 Sourcing Process and Principles
114(6)
5.2.1 Procurement, Purchasing and Sourcing
114(1)
5.2.2 Sourcing Process
115(2)
5.2.3 Make-or-Buy and Outsourcing
117(3)
5.2.4 Organization of Sourcing Processes
120(1)
5.3 Sourcing Strategies
120(6)
5.3.1 Single vs. Dual and Multiple Sourcing
120(2)
5.3.2 Local vs. Global Sourcing
122(3)
5.3.3 Just-in-Time
125(1)
5.4 Supplier Relationship Management
126(7)
5.4.1 Strategic Supplier Analysis
127(2)
5.4.2 Supplier Selection
129(2)
5.4.3 Supplier Integration and Development
131(2)
5.5 Key Points
133(1)
Bibliography
133(2)
6 Production Strategy
135(20)
6.1 Introductory Case-Study DELL vs. Lenovo
135(5)
6.2 Postponement and Modularization
140(4)
6.2.1 Problem: Mass Production or Product Customization
140(1)
6.2.2 Principles: Postponement and Modularization
140(1)
6.2.3 Examples of Postponement Strategies
141(3)
6.3 Push--Pull Views and Order Penetration Point
144(1)
6.4 Selection of a Production Strategy
145(8)
6.4.1 Types of Production Strategies
145(5)
6.4.2 Method: Lost-Sales Analysis
150(3)
6.5 Key Points
153(1)
Bibliography
153(2)
7 Facility Location Planning and Network Design
155(48)
7.1 Introductory Case Study Power Pong Sports, China
155(3)
7.2 Supply Chain Design Framework
158(1)
7.3 Global Supply Chain Design
159(21)
7.3.1 Warehouse Location Problem and Its Formalization
160(3)
7.3.2 A Spreadsheet Approach to the WLP
163(5)
7.3.3 Branch-&-Bound: How the Solver Add-In Works
168(5)
7.3.4 Capacitated WLP
173(7)
7.4 Regional Facility Location
180(9)
7.4.1 Management Problem Description
181(1)
7.4.2 A Mathematical Model of the Decision Situation
181(1)
7.4.3 Solving the Mathematical Model: Centre-of-Gravity Approach
182(7)
7.5 Factor-Ranking Analysis
189(9)
7.5.1 Case-Study OTLG Germany
189(1)
7.5.2 Factor-Rating Method
189(5)
7.5.3 Utility Value Analysis
194(4)
7.6 Combining Optimization and Simulation in Supply Chain Design
198(2)
7.7 Key Points
200(1)
Bibliography
201(2)
8 Distribution and Transportation Network Design
203(44)
8.1 Introductory Case Study: Bavarian Wood
203(3)
8.2 Generic Transport Network Structures
206(2)
8.3 Realizing Economies of Scale in Transportation
208(10)
8.3.1 Consolidation of Shipments
208(2)
8.3.2 Postponement
210(1)
8.3.3 Milk-Runs
211(2)
8.3.4 Transshipment
213(5)
8.4 Trade-Off-Based Transportation Network Design
218(3)
8.5 Capacity Allocation in a Many-to-Many Network
221(13)
8.5.1 The Transportation Problem
222(1)
8.5.2 Decision Model
223(1)
8.5.3 Finding the First Feasible Model Solution
224(4)
8.5.4 Optimality Check
228(2)
8.5.5 Solution Improvement
230(4)
8.6 Distribution Network Design
234(9)
8.6.1 Case Study: ALDI vs. Homeplus
234(2)
8.6.2 Types of Distribution Networks
236(2)
8.6.3 Case Study: Seven-Eleven Japan
238(2)
8.6.4 Transportation Modes
240(3)
8.7 Key Points
243(1)
Bibliography
244(3)
9 Factory Planning and Process Design
247(46)
9.1 Introductory Case-Study "Factory Planning at Tesla"
247(2)
9.2 Factory Planning
249(5)
9.2.1 Role of Factory Planning in SCOM
249(1)
9.2.2 Processes of Factory Planning
250(4)
9.3 Capacity Planning
254(18)
9.3.1 Queuing Theory
256(4)
9.3.2 Little's Law
260(4)
9.3.3 Bottleneck Analysis/Theory of Constraints
264(1)
9.3.4 Drum, Buffer, Rope
265(1)
9.3.5 Break-Even Analysis
266(3)
9.3.6 Decision Trees
269(1)
9.3.7 Simulation: Case Study AnyLogic
270(2)
9.4 Process Flow Structures
272(7)
9.4.1 Job Shop
272(1)
9.4.2 Batch Shop
273(1)
9.4.3 Assembly Line
273(5)
9.4.4 Continuous Flow
278(1)
9.4.5 Product-Process Matrix
278(1)
9.5 Lean Production Systems
279(9)
9.5.1 Lean Thinking
279(2)
9.5.2 Lean Production Principles
281(5)
9.5.3 Lean Supply Chain
286(2)
9.6 Key Points and Discussion Questions
288(2)
Bibliography
290(3)
10 Layout Planning
293(26)
10.1 Introductory Case-Study "OTLG Ludwigsfelde"
293(1)
10.2 Layout Planning in Manufacturing
294(11)
10.2.1 Fixed Position Layout
295(1)
10.2.2 Process Flow Layout
296(3)
10.2.3 Product Flow Layout
299(3)
10.2.4 Cell-Based Layout
302(3)
10.3 Layout Planning in Warehouses
305(3)
10.3.1 Incoming Area
305(1)
10.3.2 Storage Area
306(1)
10.3.3 Put-Away and Order Pick-Up
306(1)
10.3.4 Layout Concepts
307(1)
10.4 Methods of Layout Planning
308(5)
10.4.1 REL-Charts
308(2)
10.4.2 Quadratic Assignment Problem
310(2)
10.4.3 Simulation: Modeling Operations at Pharmaceutical Distribution Warehouses with AnyLogic
312(1)
10.5 Key Points
313(1)
10.6 Discussion
314(1)
Bibliography
315(4)
Part III Matching Demand and Supply: Tactical and Operative Planning
11 Demand Forecasting
319(16)
11.1 Introductory Case Study
319(2)
11.2 Forecasting Process and Methods
321(5)
11.2.1 The Forecasting Process and Time Horizons
322(1)
11.2.2 Forecasting Methods
323(2)
11.2.3 Forecasting Quality
325(1)
11.3 Statistical Methods
326(6)
11.3.1 Linear Regression
326(2)
11.3.2 Moving Average
328(1)
11.3.3 Simple Exponential Smoothing
329(2)
11.3.4 Double Exponential Smoothing
331(1)
11.4 Key Points and Outlook
332(1)
Bibliography
333(2)
12 Production and Material Requirements Planning
335(26)
12.1 Introductory Case-Study SIBUR: Integrated Operations and Supply Chain Planning
335(3)
12.2 Planning Horizons/MRP-II
338(1)
12.3 Sales and Operations Planning
339(6)
12.3.1 Role of Sales and Operations Planning
339(2)
12.3.2 Options for Aggregate Planning
341(1)
12.3.3 Methods for Aggregate Planning
342(3)
12.4 Sales and Production Planning with Linear Programing
345(4)
12.4.1 Problem Description
345(1)
12.4.2 Method: Linear Programming
346(2)
12.4.3 Graphical Solution
348(1)
12.5 Master Production Schedule and Rolling Planning
349(2)
12.5.1 Master Production Schedule
349(2)
12.5.2 Rolling Planning
351(1)
12.6 Material Requirements Planning
351(7)
12.6.1 Bill-of-Materials
353(1)
12.6.2 MRP Calculation
354(4)
12.7 Key Points
358(2)
Bibliography
360(1)
13 Inventory Management
361(46)
13.1 Introductory Case-Study: Amazon, Volkswagen, and DELL
361(2)
13.2 Role, Functions, and Types of Inventory
363(2)
13.3 Material Analysis
365(5)
13.3.1 ABC Analysis
365(2)
13.3.2 XYZ Analysis
367(3)
13.4 Deterministic Models
370(8)
13.4.1 EOQ Model
371(3)
13.4.2 EOQ Model with Discounts
374(2)
13.4.3 EPQ Model
376(2)
13.4.4 Re-order Point
378(1)
13.5 Stochastic Models
378(10)
13.5.1 Service Level and Safety Stock
379(5)
13.5.2 Single Period Systems ("Newsvendor Problem")
384(2)
13.5.3 Safety Stock and Transportation Strategy: Case DailyMaersk
386(2)
13.6 Inventory Control Policies
388(5)
13.6.1 Fixed Parameters
389(4)
13.6.2 Dynamic View
393(1)
13.7 Dynamic Lot-Sizing Models
393(6)
13.7.1 Least Unit Cost Heuristic
394(2)
13.7.2 Silver-Meal Heuristic
396(1)
13.7.3 Wagner--Whitin Model
397(2)
13.8 Aggregating Inventory
399(3)
13.9 ATP/CTP
402(1)
13.10 Key Points and Outlook
403(2)
Bibliography
405(2)
14 Routing and Scheduling
407(48)
14.1 Introductory Case Study RED SEA BUS TRAVEL
408(1)
14.2 Shortest Paths in a Network
409(6)
14.2.1 Outline of the Shortest Path Problem (SPP) in a Network
409(2)
14.2.2 Mathematical Graphs
411(1)
14.2.3 The SPP as Graph-Based Optimization Model
411(1)
14.2.4 Dijkstra's Algorithm for the Identification of a Shortest S-T-Path
412(3)
14.3 Round Trip Planning/Travelling Salesman Problem
415(12)
14.3.1 Travelling Salesman Problem
416(2)
14.3.2 A Mixed-Integer Linear Program for TSP-Modelling
418(3)
14.3.3 Heuristic Search for High Quality Round Trips
421(6)
14.4 Vehicle Routing
427(12)
14.4.1 Case Study ORION: Vehicle Routing at UPS
427(2)
14.4.2 Decision Situation Outline
429(1)
14.4.3 Current Approach for the Route Compilation
430(2)
14.4.4 Capacitated Vehicle Routing Problem
432(3)
14.4.5 The Sweep Algorithm
435(4)
14.5 Machine Scheduling
439(9)
14.5.1 The Problem of Scheduling a Machine
439(2)
14.5.2 Priority Rule-Based Scheduling
441(3)
14.5.3 Scheduling Algorithm of Moore
444(1)
14.5.4 Scheduling Two Machines in a Flow Shop
445(2)
14.5.5 Further Challenges in Machine Scheduling
447(1)
14.6 Key Points
448(2)
Bibliography
450(5)
Part IV Advanced Topics in Supply Chain and Operations Management
15 Supply Chain Risk Management and Resilience
455(26)
15.1 Introductory Case-Study: Capacity Disruption at BASF
455(1)
15.2 Uncertainty and Risks
456(2)
15.3 Risk Management in the Supply Chain
458(4)
15.3.1 Risk Classification
458(2)
15.3.2 General Framework of Risk Management in the Supply Chain
460(2)
15.4 Operational and Disruption Risks
462(2)
15.5 Ripple Effect in the Supply Chain
464(2)
15.6 Supply Chain Resilience
466(7)
15.6.1 Resilience Framework
466(3)
15.6.2 Costs of Resilience
469(4)
15.7 KPI for Supply Chain Risk
473(2)
15.7.1 Operational Risks
473(1)
15.7.2 Disruption Risks
474(1)
15.8 Key Points and Discussion Questions
475(1)
Bibliography
476(5)
16 Digital Supply Chain, Smart Operations and Industry 4.0
481(46)
16.1 Introductory Case-Study: SupplyOn
481(2)
16.2 SCOM Excellence and Digitalization
483(4)
16.2.1 Operational Excellence
483(1)
16.2.2 From Operational Excellence to SCOM Excellence
484(1)
16.2.3 Digitalization as New Driver in SCOM Excellence
484(3)
16.3 Development of Technology in SCOM
487(6)
16.3.1 Three Industrial Revolutions
487(1)
16.3.2 Fourth Industrial Revolution: Industry 4.0
488(2)
16.3.3 Internet of Things
490(1)
16.3.4 Cyber Physical Systems
490(1)
16.3.5 Smart, Connected Products
491(1)
16.3.6 Smart Supply Chains and Smart Value Adding Networks
492(1)
16.4 Digital SCOM Framework
493(1)
16.5 Digital Technology in the "Plan" Processes
494(3)
16.5.1 Big Data Analytics
494(1)
16.5.2 The Digital Twin
495(2)
16.6 Digital Technology in "Source" Processes
497(5)
16.6.1 eProcurement
497(1)
16.6.2 Supplier Collaboration Portals
498(1)
16.6.3 Digital Trends for Excellence in Sourcing
499(1)
16.6.4 Blockchain
499(2)
16.6.5 Robotic Process Automation and Artificial Intelligence in Procurement
501(1)
16.7 Digital Technology in "Make" Processes
502(5)
16.7.1 3D Printing and Additive Manufacturing
502(2)
16.7.2 Virtual Reality and Augmented Reality
504(1)
16.7.3 Robotics
505(2)
16.8 Digital Technology in the "Delivery" Processes
507(4)
16.8.1 Drones or Unmanned Aerial Vehicles
508(1)
16.8.2 Smart Driverless Transportation Systems
508(1)
16.8.3 Smart Forklifts, Pallet Movers, and Cranes
509(2)
16.9 Qualitative and Quantitative Potential of Digital Technology in SCOM
511(5)
16.9.1 Qualitative Improvements of Digital SCOM
512(1)
16.9.2 Quantitative Potential Assessments of Digital SCOM
512(2)
16.9.3 Possible Obstacles and Limitations of Digital SCOM
514(2)
16.10 Key Points and Discussion Questions
516(2)
16.11 Case-Study "Smart Usage of Big Data Along the Supply Chain: Big Data Analytics Between Companies, Value-Added and the Impact of Risk and Complexity Management"
518(4)
Bibliography
522(5)
17 Pricing and Revenue-Oriented Capacity Allocation
527(40)
17.1 Case Study: FRISIA COASTAL SHIPPING: The Story of Jordis and Tjark
529(3)
17.2 Non-competitive Pricing
532(4)
17.3 Pricing with Scarce Capacities
536(6)
17.4 Setting Optimal Prices in Resource Networks
542(4)
17.5 Dynamic Pricing: Pricing in Reaction to Observed Market Developments
546(19)
17.5.1 Business Extension by Coastal Tours
547(5)
17.5.2 Decision Situation Modelling
552(2)
17.5.3 Pricing and Capacity Distribution over the Sales Period
554(10)
17.5.4 Summary of Dynamic Pricing
564(1)
17.6 Pricing Lessons Learned and Open Issues
565(1)
Bibliography
566(1)
Appendix Case-Study "Re-designing the Material Flow in a Global Manufacturing Network" 567(6)
Index 573
Prof. Dr. habil. Dmitry Ivanov is professor of Supply Chain Management at Berlin School of Economics and Law. He has been teaching classes for more than fifteen years in supply chain and operations management. He published extensively in international journals and is author of the books Structural Dynamics and Resilience in Supply Chain Risk Management and "Adaptive Supply Chain Management" published by Springer in 2018 and 2010, respectively.

Prof. Dr. Alexander Tsipoulanidis, MBA, is professor for Supply Chain and Operations Management at Berlin School of Economics and Law. He has more than twenty years of practical experience in factory planning and operations management. His teaching and research interest focuses on lean production and operational excellence at the time of the digital transformation.





Prof. Dr. habil. Jörn Schönberger is professor and chair for transport services and logistics at Technische Universität Dresden, "Friedrich List" faculty of transportation and traffic sciences. He has published several papers in international journals and is author of the book "Model-Based Control of Logistics Processes in Volatile Environments" published by Springer in 2011.