0000000000362636

AUTHOR

Jose M. Framinan

0000-0003-0619-8508

showing 6 related works from this author

Closed-loop supply chains: What reverse logistics factors influence performance?

2016

This paper analyses the inventory and order flow dynamics in closed-loop supply chains (CLSCs). In this kind of supply chains the reverse flow of materials entering the system for recycling purposes complicates the way in which inventories should be managed and replenishment policies should be designed. Specifically, we analyse the relationships between some reverse logistics’ factors (remanufacturing lead-time, return rate of recycled products, reverse order policy, and number of supply chain tiers) on the order and inventory variance amplification. We firstly perform a systematic literature review of the related studies. Secondly, by adopting a difference equation math approach and design…

Supply chain dynamicsEconomics and EconometricEconomics and EconometricsBullwhip effectOperations researchSupply chainCeteris paribusSupply chain dynamic0211 other engineering and technologies02 engineering and technologyReverse logisticsManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringOrder (exchange)Bullwhip effect0502 economics and businessEconomicsBusiness Management and Accounting (all)Operations managementRemanufacturing021103 operations researchSupply chain managementSystematic literature review05 social sciencesVariance (accounting)Settore ING-IND/35 - Ingegneria Economico-GestionaleGeneral Business Management and AccountingRemanufacturing lead timeReverse logisticReverse logisticsSimulation050203 business & managementInternational Journal of Production Economics
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Insights on Partial Information Sharing in Supply Chain dynamics

2015

This paper provides an assessment of partial Information Sharing (IS) in Supply Chain (SC). We study the dynamics of collaborative multi-echelon structure, characterized by an increasing level of information visibility among partners. To do so, we mathematically model six four-echelon serial SCs via difference equations and conduct numerical simulations on the basis of a robust design of experiment. Results shows how (1) as the extent of IS increases, the performance of whole SC improves as well, and (2) the impact of IS depends not on which particular members are involved but on the number of collaborative members.

Information managementStructure (mathematical logic)demand amplificationANOVA; asymmetric information sharing; demand amplification; simulation; supply chain collaboration; supply chain dynamics; Strategy and Management1409 Tourism Leisure and Hospitality Management; Industrial and Manufacturing EngineeringMathematical optimizationsupply chain dynamicsKnowledge managementANOVAsupply chain dynamicComputer sciencebusiness.industryInformation sharingSupply chainStrategy and Management1409 TourismLeisure and Hospitality ManagementVisibility (geometry)supply chain collaborationNumerical modelsasymmetric information sharingsimulationSettore ING-IND/35 - Ingegneria Economico-GestionaleIndustrial and Manufacturing EngineeringRobust designDynamics (music)business
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Inventory policies and information sharing in multi-echelon supply chains

2011

The aim of this article is to show how to modify a replenishment rule in relation to the operational information shared by suppliers. More specifically, we present a model of an Automatic Pipeline Variable Inventory and Order-Based Production Control System rule for a multi-echelon supply chain characterised by different increasing levels of shared information. A numerical study is presented to underline the performance differences for three variants of the smoothing order rule in terms of bullwhip reduction, inventory stability and operational and customer responsiveness. Results show how the effectiveness of a smoothing replenishment rule depends on the level of information sharing.

Inventory controlOperations researchRelation (database)Computer scienceStrategy and ManagementInformation sharingSupply chainManagement Science and Operations ResearchPipeline (software)Industrial and Manufacturing EngineeringComputer Science ApplicationsMicroeconomicsVariable (computer science)BullwhipSmoothingProduction Planning & Control
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The effect of inventory record inaccuracy in information exchange supply chains

2015

Abstract The goal of this paper is to quantify the impact of Inventory Record Inaccuracy on the dynamics of collaborative supply chains, both in terms of operational performance (i.e. order and inventory stability), and customer service level. To do so, we model an Information Exchange Supply Chain under shrinkage errors in the inventory item recording activity of their nodes, present the mathematical formulation of such supply chain model, and conduct a numerical simulation assuming different levels of errors. Results clearly show that Inventory Record Inaccuracy strongly compromises supply chain stability, particularly when moving upwards in the supply chain. Important managerial insights…

Information sharingSupply chain managementBullwhip effectInformation Systems and ManagementGeneral Computer ScienceOperations researchInformation sharingSupply chainService managementSystem dynamicSystem dynamicsManagement Science and Operations ResearchSettore ING-IND/35 - Ingegneria Economico-GestionaleCollaborationIndustrial and Manufacturing EngineeringSystem dynamicsBullwhip effectModeling and SimulationEconomicsInventory theoryBullwhip effect; Collaboration; Information sharing; Supply chain management; System dynamics; Management Science and Operations Research; Modeling and Simulation; Information Systems and ManagementOperations managementSupply chain managementInformation exchange
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Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand …

Article SubjectGeneral Computer ScienceIMPACTComputer scienceSupply chain0211 other engineering and technologiesINFORMATION DISTORTIONINVENTORYDELAYS02 engineering and technologyERRORSlcsh:QA75.5-76.95Bullwhip effect0202 electrical engineering electronic engineering information engineeringEconometricsPERSPECTIVE021103 operations researchMultidisciplinaryInformation sharingContrast (statistics)BULLWHIPPOLICYSettore ING-IND/35 - Ingegneria Economico-GestionaleINCENTIVESLow demandMODEL020201 artificial intelligence & image processinglcsh:Electronic computers. Computer sciencePerformance indicatorComplexity
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On the Bullwhip Avoidance Phase: The Synchronised Supply Chain

2012

Abstract The aim of this paper is to analyse the operational response of a Synchronised Supply Chain (SSC). To do so, first a new mathematical model of a SSC is presented. An exhaustive Latin Square design of experiments is adopted in order to perform a boundary variation analysis of the main three parameters of the periodic review smoothing ( S ,  R ) order-up-to policy: i.e., lead time, demand smoothing forecasting factor, and proportional controller of the replenishment rule. The model is then evaluated under a variety of performance measures based on internal process benefits and customer benefits. The main results of the analysis are: (I) SSC responds to violent changes in demand by re…

Information Systems and ManagementSupply chain managementGeneral Computer ScienceOperations researchComputer scienceSupply chainService managementManagement Science and Operations ResearchSettore ING-IND/35 - Ingegneria Economico-GestionaleIndustrial and Manufacturing EngineeringModeling and SimulationBullwhip effectInventory Supply chain management Simulation Collaboration Information sharingBullwhipLead time
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