Measuring the impact of (s, S) ordering policy on the bullwhip effect by means of simulation optimization

Derbel, Mouna; Chabchoub, Habib; Hachicha, Wafik; Masmoudi, Faouzi

doi:10.1109/icadlt.2013.6568506

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…The bullwhip effect, also known as demand information amplification or the Forrester effect [46], is a phenomenon in which small changes in customer demand lead to significant fluctuations in orders received by upstream suppliers in the supply chain system [47]. The bullwhip effect reflects the existence of various forms of uncertainty in the supply chain system [48], which is also one of the most studied phenomena in supply chain management [49]. Wang and Disney, 2016 defined the bullwhip effect as the amplification of order fluctuations throughout the supply chain [50].…”

Section: Literature Review 21 Bullwhip Effectmentioning

confidence: 99%

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

Hsu

Yang

Zhang

et al. 2021

JTAER

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With the development of economic globalization, the uncertainty of supply chains is also increasing, and alleviating the bullwhip effect has become an important issue. From previous discussions on alleviating the bullwhip effect, there was no research on alleviating it by enhancing supply chain agility through improving big data. Moreover, it has not been found that quality function deployment is used to analyze the interdependence between big data and supply chain agility, as well as between supply chain agility and the bullwhip effect. In particular, the interaction of bullwhip effect factors are not considered. In this study, the multicriteria decision-making integrated framework is proposed and the largest relay manufacturer in China is taken to identify key big data enablers to enhance supply chain agility and mitigate the bullwhip effect, thus providing an effective method for electronic equipment manufacturing enterprises to develop a supply chain that can quickly respond to changes and uncertainties. These big data enablers can enhance supply chain agility and reduce the bullwhip effect. This framework provides an effective method for electronic manufacturers to formulate supply chain agility indicators and big data enablers to mitigate the bullwhip effect and also provides a reference for other manufacturing enterprises in supply chain management.

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Section: Literature Review 21 Bullwhip Effectmentioning

confidence: 99%

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

Hsu

Yang

Zhang

et al. 2021

JTAER

View full text Add to dashboard Cite

show abstract

“…In each period, the price is independent and identically distributed (i.i.d.) from a normal distribution with average  and variance 2  . If the product price increases greatly, a large number of end customers will purchase the product from the retailer.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…In the supply chain system, there are various forms of uncertainty. The "bullwhip effect" is short-hand term for a dynamical uncertainly phenomenon in supply chains [2]. The bullwhip effect is one of the most studied phenomena in supply chain management [3].…”

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confidence: 99%

The analysis of bullwhip effect in supply chain based on hedging strategy compared with optimal order quantity strategy

et al. 2021

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The bullwhip effect is one of the most important problems in the supply chain management. It can cause large inefficiency in supply chain. Although there are many researches about bullwhip effect, few studies have investigated this phenomenon caused by product price fluctuation. In this paper we consider a two-period supply chain consisting of one supplier, one wholesaler and one retailer. The wholesale price may increase greatly in the beginning of second period. If this happens, a large number of end customers will go to purchase the product from retailer. For managing the end customers' demands in the second period, we consider two ordering strategies available to the retailer including optimal order quantity strategy and hedging strategy with call option. For each strategy, we calculate the bullwhip effect ratio for two periods and compare the results. We found that the lower exercise price in hedging strategy compared with the wholesale price in the optimal order quantity strategy must not contribute to extra product purchase. The research provides new insights into how hedging strategy can reduce bullwhip effect.

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Analysis of Traceability Systems for Reducing the Bullwhip Effect in the Perishable Food Supply Chain: A System Dynamics Approach

Otero-Diaz

Castro

Herrera

2021

Communications in Computer and Information Science

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Measuring the impact of (s, S) ordering policy on the bullwhip effect by means of simulation optimization

Cited by 3 publications

References 19 publications

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

The analysis of bullwhip effect in supply chain based on hedging strategy compared with optimal order quantity strategy

Analysis of Traceability Systems for Reducing the Bullwhip Effect in the Perishable Food Supply Chain: A System Dynamics Approach

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