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Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments
16 references·16 citing·38 second hopsampled
Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments (2018)Applying machine learning to the dynamic …Ripple effect in the supply chain: an analysis and recent literature (2017)Ripple effect in the supply c…The bullwhip effect: Progress, trends and directions (2015)The bullwhip effect: Progress…Artificial intelligence in supply chain management: theory and applications (2009)Artificial intelligence in su…Mapping the future of supply chain management: a Delphi study (2008)Mapping the future of supply …Application of machine learning techniques for supply chain demand forecasting (2007)Application of machine learni…Managing Risk To Avoid Supply-Chain Breakdown (2004)Managing Risk To Avoid Supply…Measuring and avoiding the bullwhip effect: A control theoretic approach (2003)Measuring and avoiding the bu…Inventory management in supply chains: a reinforcement learning approach (2002)Inventory management in suppl…DEFINING SUPPLY CHAIN MANAGEMENT (2001)DEFINING SUPPLY CHAIN MANAGEM…Foundations of Inventory Management (2000)Foundations of Inventory Mana…The single-period (news-vendor) problem: literature review and suggestions for future research (1999)The single-period (news-vendo…The Bullwhip Effect In Supply Chains 1 (1997)The Bullwhip Effect In Supply…Quantifying the bullwhip effect in supply chains (1997)Quantifying the bullwhip effe…Inventories and the volatility of production (1986)Inventories and the volatilit…International Journal of Production Research (1962)International Journal of Prod…Dynamic Inventory Policy with Varying Stochastic Demands (1960)Dynamic Inventory Policy with…Industry 4.0 technologies and circular economy synergies: Enhancing corporate sustainability through sustainable supply chain integration and flexibility (2024)Industry 4.0 technologies and…Artificial intelligence and prescriptive analytics for supply chain resilience: a systematic literature review and research agenda (2024)Artificial intelligence and p…Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research (2023)Data science and big data ana…Artificial intelligence in supply chain and operations management: a multiple case study research (2023)Artificial intelligence in su…Supply chain risk management with machine learning technology: A literature review and future research directions (2022)Supply chain risk management …Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions (2022)Applying digital twins for in…Understanding the influential and mediating role of cultural enablers of AI integration to supply chain (2021)Understanding the influential…Product backorder prediction using deep neural network on imbalanced data (2021)Product backorder prediction …Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques (2021)Fusion-Based Supply Chain Col…Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas (2021)Application of Machine Learni…AI-enabled Enterprise Information Systems for Manufacturing (2021)AI-enabled Enterprise Informa…A systematic review of machine learning in logistics and supply chain management: current trends and future directions (2021)A systematic review of machin…Machine learning for demand forecasting in the physical internet: a case study of agricultural products in Thailand (2020)Machine learning for demand f…Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion (2020)Demand forecasting in supply …Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail (2020)Deep learning with long short…Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility (2019)Digital Supply Chain Twins: M…Supply Chain Management: Strategy, Planning and Operations (2000)The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities (2007)A Contingent Resource‐Based Perspective of Supply Chain Resilience and Robustness (2014)The bullwhip effect in supply chains (2015)The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018)Information Distortion in a Supply Chain: The Bullwhip Effect (1997)Information systems in supply chain integration and management (2003)Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities (2020)Artificial intelligence applications in supply chain management (2021)Inventory management and production planning and scheduling (1999)Designing and managing the supply chain : concepts, strategies, and case studies (2000)Exponential smoothing: The state of the art—Part II (2006)Literature review on disruption recovery in the supply chain (2017)Competitive Strategy: Techniques for Analyzing Industries and Competitors (1980)A Model of Distributor Firm and Manufacturer Firm Working Partnerships (1990)The Commitment-Trust Theory of Relationship Marketing (1994)A framework of sustainable supply chain management: moving toward new theory (2008)Understanding the concept of supply chain resilience (2009)Supply chain collaboration: Impact on collaborative advantage and firm performance (2010)Reducing the Cost of Demand Uncertainty Through Accurate Response to Early Sales (1996)Demand chain management in manufacturing and services: web‐based integration, drivers and performance (2002)From supply to demand chain management: efficiency and customer satisfaction (2002)The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains (2003)Analysis of Inventory Systems. (1964)Optimal Lot Sizing, Process Quality Improvement and Setup Cost Reduction (1986)A Newsvendor’s Procurement Problem when Suppliers Are Unreliable (2007)Strategic Customer Behavior, Commitment, and Supply Chain Performance (2008)The newsvendor problem: Review and directions for future research (2010)Perspectives in supply chain risk management (2006)Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future (2014)OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications (2020)Supply chain disruptions and resilience: a major review and future research agenda (2021)Two perspectives on supply chain resilience (2021)The Value of Information Sharing in a Two-Level Supply Chain (2000)Lectures on Stochastic Programming: Modeling and Theory (2009)Building the Resilient Supply Chain (2004)A systematic review on drivers, barriers, and practices towards circular economy: a supply chain perspective (2018)Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience (2019)
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References

  • 2001DEFINING SUPPLY CHAIN MANAGEMENT5,167 cited
  • 1962International Journal of Production Research2,111 cited
  • 1997The Bullwhip Effect In Supply Chains 12,102 cited
  • 2004Managing Risk To Avoid Supply-Chain Breakdown1,860 cited
  • 2000Foundations of Inventory Management1,856 cited
  • 1999The single-period (news-vendor) problem: literature review and suggestions for future research910 cited
  • 2017Ripple effect in the supply chain: an analysis and recent literature907 cited
  • 2003Measuring and avoiding the bullwhip effect: A control theoretic approach685 cited
  • 2007Application of machine learning techniques for supply chain demand forecasting669 cited
  • 1997Quantifying the bullwhip effect in supply chains593 cited
  • 2009Artificial intelligence in supply chain management: theory and applications574 cited
  • 1986Inventories and the volatility of production505 cited
  • 2015The bullwhip effect: Progress, trends and directions436 cited
  • 1960Dynamic Inventory Policy with Varying Stochastic Demands303 cited
  • 2008Mapping the future of supply chain management: a Delphi study223 cited
  • 2002

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Inventory management in supply chains: a reinforcement learning approach
220 cited

Cited by

  • 2021Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques278 cited
  • 2019Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility254 cited
  • 2023Artificial intelligence in supply chain and operations management: a multiple case study research242 cited
  • 2021Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas230 cited
  • 2020Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail206 cited
  • 2020Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion202 cited
  • 2021A systematic review of machine learning in logistics and supply chain management: current trends and future directions176 cited
  • 2022Supply chain risk management with machine learning technology: A literature review and future research directions163 cited
  • 2022Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions145 cited
  • 2023Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research141 cited
  • 2021AI-enabled Enterprise Information Systems for Manufacturing132 cited
  • 2020Machine learning for demand forecasting in the physical internet: a case study of agricultural products in Thailand115 cited
  • 2024Artificial intelligence and prescriptive analytics for supply chain resilience: a systematic literature review and research agenda108 cited
  • 2024Industry 4.0 technologies and circular economy synergies: Enhancing corporate sustainability through sustainable supply chain integration and flexibility100 cited
  • 2021Understanding the influential and mediating role of cultural enablers of AI integration to supply chain99 cited
  • 2021Product backorder prediction using deep neural network on imbalanced data89 cited