Supply chain analytics: an uncertainty modeling approach
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2023]
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| Schriftenreihe: | Springer texts in business and economics
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xiv, 314 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031303463 |
| ISSN: | 2192-4341 |
Internformat
MARC
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| 650 | 4 | |a Operations Management | |
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| 650 | 4 | |a Business Analytics | |
| 650 | 4 | |a Risk Management | |
| 650 | 4 | |a Business logistics | |
| 650 | 4 | |a Production management | |
| 650 | 4 | |a Business information services | |
| 650 | 4 | |a Business—Data processing | |
| 650 | 4 | |a Financial risk management | |
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Datensatz im Suchindex
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| adam_text |
Contents 1 Introduction and Risk Analysis in Supply Chains. Internet Era and Shift in Supply Chains. Three Challenges of Modern Supply Chains. Supply Chain Management Framework. Supply Chain Integration. Supply Chain Analytics at the Interface of Supply Chain Management and Data Analytics. 1.6 Case Study: Kordsa Inc. 1.7 Chapter Summary. 1.8 Practice Examples. 1.9 Exercises. References. 1.1 1.2 1.3 1.4 1.5 2 15 18 21 22 23 24 Predictive Analytics. 2.1.1 Bias-Variance Trade-Off. 2.1.2 Linear Models. 2.1.3 Matrix Formation . 2.1.4 Generalized Least Squares (GLS). 2.1.5 Dealing with
Endogeneity Problems. 2.1.6 Regularization Methods. 2.1.7 Classification Methods. 2.1.8 Time Series Analysis. 2.2 Prescriptive Analytics. 2.2.1 Taylor’s Expansion. 2.2.2 Convexity. 2.2.3 Newton’s Method. 2.2.4 Gradient Descent Method. 2.2.5 Lagrange Optimization . 2.3 Chapter Summary. 2.4 Practice Examples. 2.5 Exercises. References. 27 28 29 30 32 35 36 41 43 49 58 59 61 62 63 64 66 67 73 73 Inventory Management Under Demand Uncertainty. 75 Analytical Foundations: Predictive and Prescriptive Analytics . 2.1 3 1 2 4 6 12 xi
Contents xii 4 3.1 Inventory Productivity and Financial Performance. 3.2 Single-Period Models. 3.2.1 Single-Period Example . 3.3 Multi-period Models . 3.3.1 Multi-period Example. 3.4 Reorder Model with Continuous Review. 3.4.1 Reorder Model Example. 3.5 Monte Carlo Simulation for Inventory Models . 3.6 Chapter Summary. 3.7 Practice Examples. 3.8 Exercises. 3.9 Appendix to Chap. 3. 3.9.1 Analytical Solution to the Newsvendor Problem. 3.9.2 Analytical Solution to՜ the Base Stock Problem . References. 77 80 86 89 91 93 98 100 104 106 115 116 116 118 119 Uncertainty Modelling. 121 124 128 129 132 134 4.1 Uncertainty Modelling Versus Demand
Forecasting . 4.2 Evolutionary Dynamics of Uncertainty . 4.2.1 Additive Demand Models. 4.2.2 Multiplicative Demand Models. 4.3 Integration of Uncertain Elements in a Unified Model. 4.3.1 Inventory Management with the Additive Integration of Uncertain Elements. 136 4.3.2 Inventory Management with the Multiplicative Integration of UncertainElements . 139 4.3.3 A Commonly Used Multiplicative Model: Jump Diffusion Process . 142 4.3.4 Example. 4.4 Demand Regularization. 4.5 Chapter Summary. 4.6 Practice Examples. 4.7 Exercises. References. 5 Supply Chain Responsiveness. 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 Lead Time Reduction .
Multiple Sourcing. Quantity Flexibility Contracts. Multiple and Sequential Ordering Problems. Multiple Ordering in a Multi-echelonModel. Chapter Summary. Practice Examples. Exercises. Appendix to Chap. 5. 144 146 150 151 157 157 159 162 167 173 176 182 187 187 194 194
Contents xiii 5.9.1 Derivation of ß*and К*. References. 194 195 6 Managing Product Variety. 197 199 203 205 209 214 220 221 226 226 226 227 230 Mean-Variance Analysis for Product Selection. Resource Allocation and Capacity Management. Multiple Ordering Model with Multiple Products. Product Proliferation Model. Operational Excellence. Chapter Summary. Practice Examples. Exercises. Appendix to Chap. 6. 6.9.1 Mean-Variance Analysis Derivations . 6.9.2 Multi-product Newsvendor Model. References. 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 7 Managing the Supply
Risk. 7.1 Type-1 Disruption Risk. 7.2 Type-2 Disruption Risk. 7.3 Implications of the Shipment Ownership for Global Trade. 7.4 Type-3 Risk: Delivery Shortfalls . 7.5 Chapter Summary. 7.6 Practice Examples. 7.7 Exercises. References. 8 Supply Chain Finance. Early Payment Scheme. Reverse Factoring . Letter of Credit. Dynamic Discounting. 8.4.1 Market Mechanism of Dynamic Discounting. 8.5 Chapter Summary. 8.6 Practice
Examples. 8.7 Exercises. References. 8.1 8.2 8.3 8.4 9 Future Trends: AI and Beyond. 9.1 Artificial Neural Networks. 9.2 Activation Functions. 9.3 Model Training. 9.4 ANNs in Inventory Management. 9.5 Chapter Summary. References. 231 232 240 244 245 251 251 254 254 257 259 261 264 268 271 275 276 279 279 281 283 285 287 288 291 292 A Introduction to Python Programming for Supply Chain Analytics . 293
xiv Contents A.l NumPy. A.2 SciPy. A.3 Pandas. A.4 Matplotlib. A.5 General Programming Concepts. Reference. 298 300 302 306 307 311 Index. 313 |
| adam_txt |
Contents 1 Introduction and Risk Analysis in Supply Chains. Internet Era and Shift in Supply Chains. Three Challenges of Modern Supply Chains. Supply Chain Management Framework. Supply Chain Integration. Supply Chain Analytics at the Interface of Supply Chain Management and Data Analytics. 1.6 Case Study: Kordsa Inc. 1.7 Chapter Summary. 1.8 Practice Examples. 1.9 Exercises. References. 1.1 1.2 1.3 1.4 1.5 2 15 18 21 22 23 24 Predictive Analytics. 2.1.1 Bias-Variance Trade-Off. 2.1.2 Linear Models. 2.1.3 Matrix Formation . 2.1.4 Generalized Least Squares (GLS). 2.1.5 Dealing with
Endogeneity Problems. 2.1.6 Regularization Methods. 2.1.7 Classification Methods. 2.1.8 Time Series Analysis. 2.2 Prescriptive Analytics. 2.2.1 Taylor’s Expansion. 2.2.2 Convexity. 2.2.3 Newton’s Method. 2.2.4 Gradient Descent Method. 2.2.5 Lagrange Optimization . 2.3 Chapter Summary. 2.4 Practice Examples. 2.5 Exercises. References. 27 28 29 30 32 35 36 41 43 49 58 59 61 62 63 64 66 67 73 73 Inventory Management Under Demand Uncertainty. 75 Analytical Foundations: Predictive and Prescriptive Analytics . 2.1 3 1 2 4 6 12 xi
Contents xii 4 3.1 Inventory Productivity and Financial Performance. 3.2 Single-Period Models. 3.2.1 Single-Period Example . 3.3 Multi-period Models . 3.3.1 Multi-period Example. 3.4 Reorder Model with Continuous Review. 3.4.1 Reorder Model Example. 3.5 Monte Carlo Simulation for Inventory Models . 3.6 Chapter Summary. 3.7 Practice Examples. 3.8 Exercises. 3.9 Appendix to Chap. 3. 3.9.1 Analytical Solution to the Newsvendor Problem. 3.9.2 Analytical Solution to՜ the Base Stock Problem . References. 77 80 86 89 91 93 98 100 104 106 115 116 116 118 119 Uncertainty Modelling. 121 124 128 129 132 134 4.1 Uncertainty Modelling Versus Demand
Forecasting . 4.2 Evolutionary Dynamics of Uncertainty . 4.2.1 Additive Demand Models. 4.2.2 Multiplicative Demand Models. 4.3 Integration of Uncertain Elements in a Unified Model. 4.3.1 Inventory Management with the Additive Integration of Uncertain Elements. 136 4.3.2 Inventory Management with the Multiplicative Integration of UncertainElements . 139 4.3.3 A Commonly Used Multiplicative Model: Jump Diffusion Process . 142 4.3.4 Example. 4.4 Demand Regularization. 4.5 Chapter Summary. 4.6 Practice Examples. 4.7 Exercises. References. 5 Supply Chain Responsiveness. 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 Lead Time Reduction .
Multiple Sourcing. Quantity Flexibility Contracts. Multiple and Sequential Ordering Problems. Multiple Ordering in a Multi-echelonModel. Chapter Summary. Practice Examples. Exercises. Appendix to Chap. 5. 144 146 150 151 157 157 159 162 167 173 176 182 187 187 194 194
Contents xiii 5.9.1 Derivation of ß*and К*. References. 194 195 6 Managing Product Variety. 197 199 203 205 209 214 220 221 226 226 226 227 230 Mean-Variance Analysis for Product Selection. Resource Allocation and Capacity Management. Multiple Ordering Model with Multiple Products. Product Proliferation Model. Operational Excellence. Chapter Summary. Practice Examples. Exercises. Appendix to Chap. 6. 6.9.1 Mean-Variance Analysis Derivations . 6.9.2 Multi-product Newsvendor Model. References. 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 7 Managing the Supply
Risk. 7.1 Type-1 Disruption Risk. 7.2 Type-2 Disruption Risk. 7.3 Implications of the Shipment Ownership for Global Trade. 7.4 Type-3 Risk: Delivery Shortfalls . 7.5 Chapter Summary. 7.6 Practice Examples. 7.7 Exercises. References. 8 Supply Chain Finance. Early Payment Scheme. Reverse Factoring . Letter of Credit. Dynamic Discounting. 8.4.1 Market Mechanism of Dynamic Discounting. 8.5 Chapter Summary. 8.6 Practice
Examples. 8.7 Exercises. References. 8.1 8.2 8.3 8.4 9 Future Trends: AI and Beyond. 9.1 Artificial Neural Networks. 9.2 Activation Functions. 9.3 Model Training. 9.4 ANNs in Inventory Management. 9.5 Chapter Summary. References. 231 232 240 244 245 251 251 254 254 257 259 261 264 268 271 275 276 279 279 281 283 285 287 288 291 292 A Introduction to Python Programming for Supply Chain Analytics . 293
xiv Contents A.l NumPy. A.2 SciPy. A.3 Pandas. A.4 Matplotlib. A.5 General Programming Concepts. Reference. 298 300 302 306 307 311 Index. 313 |
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| index_date | 2024-07-03T22:29:10Z |
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| issn | 2192-4341 |
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| spelling | Biçer, Işık Verfasser aut Supply chain analytics an uncertainty modeling approach Işık Biçer Cham Springer [2023] xiv, 314 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Springer texts in business and economics 2192-4341 Supply Chain Management Operations Management IT in Business Business Analytics Risk Management Business logistics Production management Business information services Business—Data processing Financial risk management Supply Chain Management (DE-588)4684051-5 gnd rswk-swf Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd rswk-swf Entscheidung bei Unsicherheit (DE-588)4070864-0 s Supply Chain Management (DE-588)4684051-5 s DE-604 Erscheint auch als Online-Ausgabe 978-3-031-30347-0 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034349846&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Biçer, Işık Supply chain analytics an uncertainty modeling approach Supply Chain Management Operations Management IT in Business Business Analytics Risk Management Business logistics Production management Business information services Business—Data processing Financial risk management Supply Chain Management (DE-588)4684051-5 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd |
| subject_GND | (DE-588)4684051-5 (DE-588)4070864-0 |
| title | Supply chain analytics an uncertainty modeling approach |
| title_auth | Supply chain analytics an uncertainty modeling approach |
| title_exact_search | Supply chain analytics an uncertainty modeling approach |
| title_exact_search_txtP | Supply Chain Analytics An Uncertainty Modeling Approach |
| title_full | Supply chain analytics an uncertainty modeling approach Işık Biçer |
| title_fullStr | Supply chain analytics an uncertainty modeling approach Işık Biçer |
| title_full_unstemmed | Supply chain analytics an uncertainty modeling approach Işık Biçer |
| title_short | Supply chain analytics |
| title_sort | supply chain analytics an uncertainty modeling approach |
| title_sub | an uncertainty modeling approach |
| topic | Supply Chain Management Operations Management IT in Business Business Analytics Risk Management Business logistics Production management Business information services Business—Data processing Financial risk management Supply Chain Management (DE-588)4684051-5 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd |
| topic_facet | Supply Chain Management Operations Management IT in Business Business Analytics Risk Management Business logistics Production management Business information services Business—Data processing Financial risk management Entscheidung bei Unsicherheit |
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