• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.203-217
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• 1998

Supply chain management is defined as "an integrative philosophy to manage the total flow of a distribution channel from the supplier to the ultimate user". There are many differences between traditional systems and supply chain management systems, There are so many advantages applying SCM concept in inventory management field from the viewpoint of information sharing. While each firm try to optimize the inventory individually in traditional systems, SCM focus on optimizing the channel-wide-inventory making effort to reduce the inventory interrelatedly, The more complex your network of suppliers, manufacturers, and distributors, the more you are likely to gain operational efficiencies by attending on inventory management. The inventory stockpiles at the various sites, including both incoming materials and finished products, have complex interrelationships. Efficient and effective management of inventory throughout the supply chain significantly improves the ultimate service provided to the customer. The purpose of this thesis is to develop the integrated inventory management system for the control of channel-wide inventory on the intranet by applying SCM concept.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.349-357
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using houristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.

• Journal of Digital Convergence
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• v.5 no.1
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• pp.47-53
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using heuristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.

• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.77-88
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• 2021

The development history of China's big data is relatively short, and it has only been ten years so far. Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model. Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.

• Korean Management Science Review
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• v.25 no.1
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• pp.107-121
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• 2008

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.141-152
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• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where JIT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying JIT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.191-201
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• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where ]IT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying ]IT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.115-123
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• 2006

The main focus of this study is to investigate the performance of a clark-scarf type multi-echelon serial supply chain operating with a base-stock policy and to optimize the inventory levels in the supply chains so as to minimize the systemwide total inventory cost, comprising holding and backorder costs as all the nodes in the supply chain. The source of supply of raw materials to the most upstream node, namely supplier, is assumed to have an infinite raw material availability. Retailer faces random customer demand, which is assumed to be stationary and normally distributed. If the demand exceeds on-hand inventory, the excess demand is backlogged. Using the echelon stock and demand quantile concepts and an efficient simulation technique, we derive near optimal inventory policy. Additionally we discuss the derived results through the extensive experiments for different supply chain settings.

• Journal of Distribution Science
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• v.19 no.11
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• pp.59-68
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• 2021

Purpose: The Covid-19 pandemic has had excessively severe impacts on all the nodes and edges of any supply chain due to changes in consumer behaviours and lockdown restrictions from governments among countries. This article aims to provide a simulating experiment on how a supply chain deals with supply disruption risks by flexibility in the inventory level of each sector as a buffer considering the overall cost to fulfil demand in the market. Research design, data and methodology: Agent-based simulation techniques are used to determine the cost-efficiency and customer waiting time related to varying inventory levels of each member in the supply chain when using inventory buffers. Findings: This study has shown that any sudden changes in the inventory level of each sector are likely to impact the rest of the supply chain. Among all sectors, the wholesaler will be impacted more severely than others. Also, the manufacturing sector is the most suitable node to adjust inventory depending on its manufacturing ability. Conclusion: The findings of the study provide insightful implications for decision-makers to adjust inventory levels and policymakers to maintain manufacturing activities in the context of the pandemic restrictions to deal with the excessive demand and potential supply disruption risks.