• Journal of Distribution Research
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• v.7 no.1
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• pp.87-103
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• 2002

This study shows the effect of individual decision style on the Bullwhip effect of supply chain. There are four individual decision styles developed by Rowe and Boulgarides(1992). The analysis of the relationship between individual decision style and supply chain dynamics is focused on overshot against final consumer order rate. Multi methodologies are used to meet the goal of this study, which are survey, game and simulation. As a result of this study, the Bullwhip effect of supply chain isn't influenced by individual decision style. This study shows different result in comparision with the prior research results that individual fact affected the Bullwhip effect of supply chain, Therfore, it is important to improve supply chain infrastructure and system than the individual fact for decreasing the Bullwhip effect of supply chain.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.41-51
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• 2013

Tendency for small changes in end-consumer demand to be amplified as one moves further up the supply chain is known as bullwhip effect (BE). BE is usually defined as variance(order)/variance(demand). Since such distorted information throughout the supply chain can lead to inefficiencies, many studies to reduce variance(order) have been performed. However, in this study, we show that minimization of BE may increase inefficiencies of the supply chain. We introduce a new objective function to increase system efficiency using smoothed ordering policies. Simulation optimization is utilized to find optimal smoothed ordering policies.

• 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.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.65-75
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• 2016

Unused spare parts of military equipments which have been kept in the warehouse for a long term have been recognized as wasting of defense budget which also decreased people's confidence in the field of national defence. It is known that overstock is caused by information distortion and bullwhip effect from downstream to upstream in the logistic support as is like business cases. After upgrading the logistic information system, it is possible for Army Logistics Command(ALC) to know demand information of end-user which is the key factor to reduce bullwhip effect. However, inventory is still overstocked and stock-out at the same time. Previous studies have not accounted for these phenomenons and have mainly focused on forecasting inventory level instead of budgetary process(budget period, PROLT, ASL/N-ASL). Thus, this study focuses on the information distortion, overstock and stock-out which caused by budgetary process in the logistic support with system dynamics and simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.155-156
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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.

• IE interfaces
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• v.21 no.2
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• pp.161-169
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• 2008

Normally, suppliers have to decide on what, how much, and when to replenish stocks of goods based on a data flow generated by a vendor managed inventory(VMI) system. But information from supply chain is often misleading. It is common for such data to be distorted by a lack of coordination and synchronization across several business entities managing different supply chain operations. This phenomenon is called the 'bullwhip effect(BwE)'. Many researchers, working over many years, have studied the reasons for the BwE. They have proposed various remedies, but this phenomenon persists. Though overlooked in previous research, this paper reveals that the 'lot size' of a supply chain of distribution is indeed the main cause of the BwE. In addition, some problems in the existing methods of measuring the BwE are identified and a revised much improved method of measurement is suggested.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.3
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• pp.203-212
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• 2009

The bullwhip effect refers to the phenomenon where demand variability is amplified when one moves upward a supply chain. In this paper, we exactly quantify the bullwhip effect for cases of seasonal demand processes in a two-echelon supply chain with a single retailer and a single supplier. In most of the previous research, some measures of performance for the bullwhip effect are developed for cases of non-seasonal demand processes. The retailer performs demand forecast with a multiplicative seasonal mixed model by using the minimum mean square error forecasting technique and employs a base stock policy. With the developed bullwhip effect measure, we investigate the impact of seasonal factor on the bullwhip effect. Then, we prove that seasonal factor plays an important role on the occurrence of the bullwhip effect.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.91-112
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• 2009

The bullwhip effect means the phenomenon of increasing demand variation as moving UP to the upstream in the supply chain. Therefore, it is recognized that the bullwhip effect is problematic for effective supply chain operations. In this paper, we exactly quantifies the bullwhip effect for the case of stochastic lead time and seasonal demand in two-echelon supply chain where retailer employs a base-stock policy considering SARMA demand processes and stochastic lead time. We also investigate the behavior of the proposed measurement for the bullwhip effect with autoregressive and moving average coefficient, stochastic lead time, and seasonal factor.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.169-179
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• 2017

The size of the market for SCM information systems have globally and steadily increased. And there are businesses that obtained innovative business performance by introducing SCM information systems. However, many businesses have still undergone trial and error in the process to introduce and operate SCM. As external factors including suppliers, customers, etc. and internal factors of businesses have been analyzed to be failure factors of executing SCM information systems, the businesses that try to introduce SCM information systems need to understand possible failure factors and establish the solutions. Therefore, this study tries to verify the diffusion of SCM information systems and effects on bullwhip effects. The study is expected to suggest empirical data that people will refer to the establishment of next counterstrategies according to the lapse of the period that systems are introduced based on theoretical bases related to the diffusion of SCM information systems.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1298-1304
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• 2006

공급체인관리(Supply Chain Management)는 단순히 물질의 흐름관리뿐만 아니라 제품의 생산, 공급, 유통 등 다양하고 복잡한 활동들의 물질 및 정보 흐름의 통합이라고 할 수 있다. 그러므로 각 구성원간의 긴밀한 협력과 공동작업을 위해서는 원활한 정보 수집 및 응답이 요구된다. 하지만 기존 시스템은 비이동성 에이전트 개념으로 네트워크의 오버헤드나 혹은 접속 단절 상황에서 작업 수행이 불가능하여 구성원간의 정보 수집과 응답이 실제 업무 처리에 지연이 발생되므로 생산에서 판매까지의 리드타임이 길어지게 되고 채찍효과(Bullwhip Effect)가 더욱 크게 나타난다. 따라서 본 논문에서는 구성원간 협력과 공동작업을 위해 효율적으로 처리되어야 할 정보 수집 및 응답을 대상으로 하는 효율적 다중 응답을 위한 이동 에이전트 시스템을 설계한다. 제안시스템은 기존 시스템의 문제 해결을 위해 이동 에이전트와 객체 복제 메커니즘을 제시하며, 또한 각 구성원 시스템의 투명성을 위해 네이밍 서비스의 구성 방법과 등록된 구성원 시스템 객체의 객체 참조자 정보에 따라 복제된 이동 에이전트가 각 구성원 시스템으로 이주하는 이주 방식과 이주 후, 개별적인 작업 수행 결과를 해당 각 구성원 시스템에 제공하는 다중 응답 시나리오를 제시한다.