Metrics for bullwhip effect analysis

Cannella, Salvatore; Barbosa‐Póvoa, Ana Paula; Framiñán, José M.; Relvas, Susana

doi:10.1057/jors.2011.139

Cited by 72 publications

(65 citation statements)

References 65 publications

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“…A reduction in all three metrics reflects improved cost effectiveness of members' operations. Table 5 provides more details on the performance metrics adopted [56].…”

Section: Design Of Experimentsmentioning

confidence: 99%

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

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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 error has a negative impact on SC performance, which is exacerbated by the magnitude of the error and by low demand variability scenarios. In contrast, demand delay produces a nonlinear behavior in the supply chain response (i.e., a short delay may have a negative impact and a long delay may have a positive impact), being influenced by the supply chain configuration.

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“…A reduction in all three metrics reflects improved cost effectiveness of members' operations. Table 5 provides more details on the performance metrics adopted [56].…”

Section: Design Of Experimentsmentioning

confidence: 99%

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

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“…We adopt a recent framework for the analysis of the bullwhip effect (see Cannella et al (2013)). It is based on a two-criterion assessment-'internal process efficiency' and 'customer service level' -is developed along this article.…”

Section: Performance Metricsmentioning

confidence: 99%

“…On the contrary, according to Cagnazzo et al (2010), performance metrics should not only assess internal processes efficiency but also their effectiveness in terms of the impact on the customers (Cannella et al 2013). Nevertheless, there are studies that analyse the impact of the smoothing replenishment rule not only in terms of the bullwhip effect, but also in terms of customer service level (see, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…In order to isolate the effect of the smoothing replenishment rule of the supply chain performance, for the aforementioned market condition, we simulate a classical traditional supply chain without information sharing and we test five settings of demand and inventory smoothing. The adopted measurement system assesses the operational performance or 'internal process benefits' in terms of bullwhip reduction, inventory stability and operational responsiveness and in terms of customer service level (Cannella et al 2013). …”

Section: Introductionmentioning

confidence: 99%

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Current economic downturn and supply chain: the significance of demand and inventory smoothing

Cannella

Ashayeri

Miranda

et al. 2013

International Journal of Computer Integrated Manufacturing

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The aim of this article is to analyse and quantify the effects of demand and inventory smoothing into supply-chain performance, facing the extreme volatility and impetuous alteration of the market produced by the current economic recession. To do so, we model a traditional serial three-stage supply chain and we test five settings of order smoothing under two shocks in the market demand, and we measure effects in terms of internal process benefits and customer service level of all supply chain partners. Results show that the implementation of this inventory strategy should be based on reward schemes; in fact a higher level of smoothing can generally improve the performance of the upstream stages. On the contrary, this approach cannot be always beneficial for the retailer as the decrease in service level can outweigh the decrease in bullwhip.

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“…Cannella et al [10][11][12][13][14] investigated the inventory policies in multi-echelon supply chains by simulation, and the case with collaboration in supply chains is also discussed. Furthermore, they conducted research of the bullwhip effect in closed-loop supply chains.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Complexity Entropy and Chaos Control of the Bullwhip Effect Considering Price of Evolutionary Game between Two Retailers

Lou

2016

Entropy

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Abstract:In this research, a model is established to represent a supply chain, which consists of one manufacturer and two retailers. The price-sensitive demand model is considered and the price game system is built according to the rule of bounded rationality as well as the entropy theory. With the increase of the price adjustment speed, the game system may go into chaos from the stable and periodic state. The bullwhip effect and inventory variance ratio of different stages that the system falls in are compared in real time. We also employ the delayed feedback control method to control the system and succeed in mitigating the bullwhip effect of the system. On the whole, the bullwhip effect and inventory variance ratio in the stable state are smaller than those in period-doubling and chaos. In the stable state, there is an optimal price adjustment speed to obtain both the lowest bullwhip effect and inventory variance ratio.

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Metrics for bullwhip effect analysis

Cited by 72 publications

References 65 publications

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Current economic downturn and supply chain: the significance of demand and inventory smoothing

Analysis of the Complexity Entropy and Chaos Control of the Bullwhip Effect Considering Price of Evolutionary Game between Two Retailers

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