The implications of information sharing on bullwhip effects in a toy supply chain

Wong, Chee Yew; El-Beheiry, Mohammed M.; Johansen, John; Hvolby, Hans‐Henrik

doi:10.1504/ijram.2007.011407

Cited by 28 publications

(16 citation statements)

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“…Demand signal processing refers to the magnification in variance that occurs through the interaction between forecasting procedures and inventory rules at each stage of the supply chain (see also Chen et al, 2000a, b;Wong et al, 2007; for a review of studies in this area please refer to Syntetos et al, 2009a). Lee et al (1997b) argued that rationing and shortage gaming is a major cause of the Bullwhip Effect and occurs in situations where the demand exceeds the production capacity.…”

Section: Factors Influencing the Bullwhip Effectmentioning

confidence: 99%

Judgement and Supply Chain Dynamics

Syntetos¹,

Boylan²,

Dangerfield³

2017

System Dynamics

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Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and 'laboratory' studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper.

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Section: Factors Influencing the Bullwhip Effectmentioning

confidence: 99%

Judgement and Supply Chain Dynamics

Syntetos¹,

Boylan²,

Dangerfield³

2017

System Dynamics

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“…Cash et al (1992) argue that in firms where the concept of IS integration plays a strategic role, massive transformation of operational and marketing aspects of the value chain is enabled. Through IS integration, companies can identify, combine, and coordinate appropriate internal resources to improve capabilities across several domains, such as product quality (Iansiti and Clark, 1994;Grant, 1996;Griffin, 1997;Flynn et al, 1999;Verona, 1999;Hsu and Chen, 2004;Yusuf et al, 2004;Swink et al, 2006;Jacobs et al, 2007;Wong et al, 2007). Case-based evidence also suggests that internal integration leads to greater cost reduction (Burt and Doyle, 1993;Ellram and Pearson, 1993;Wong et al, 2011).…”

Section: Internal Is Integration In Relation To Cost and Quality Perfmentioning

confidence: 99%

Relationships between internal and external information systems integration, cost and quality performance, and firm profitability

Maiga

Nilsson

2015

International Journal of Production Economics

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a b s t r a c tThis paper proposes that the impact of information systems (IS) integration on manufacturing firm profitability is underestimated as a result of inadequate attention to indirect effects. The study uses structural equation modeling to investigate the associations among internal and external information system integration, quality and cost performance, and firm profitability. Overall, the results from a mail survey of 263 member firms of the Institute for Supply Management support the theoretical model. Results indicate that (a) internal IS integration has a significant positive association with external IS integration, (b) both internal IS integration and external IS integration are significantly positively associated with cost and quality performance, (c) quality performance is significantly positively associated with cost performance, and (d) both quality and cost performance have significant positive associations with firm profitability. However, the direct effects of internal and external IS integration on firm profitability are not significant. Rather, the association is through cost and quality performance, suggesting that both cost and quality performance act as intervening variables. This study extends the literature on IS integration by providing insights into a set of interrelationships that matters for the attainment of firm profitability from IS integration.

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“…Lead l signals correspond to demands between l and l + 1 quarters hence, and lead signals to quarterly seasonal means. We proxy COGS for demand and production for orders (see Cachon et al 2007, Lai 2005, Wong et al 2007, Dong et al 2011). (Recall, in our model sales equals demand and production equals orders.)…”

Section: Bullwhip Effectmentioning

confidence: 99%

“…A number of case studies illustrate the bullwhip: Hammond (1994), Lee et al (1997), Fransoo and Wouters (2000), Lai (2005), and Wong et al (2007), respectively, find it in pasta, soup, frozen dinner, toy, and grocery supply chains. However, two factors make drawing conclusions from single-firm studies difficult: First, a publication bias may favor positive results-after all, bullwhip case studies will feature companies that bullwhip.…”

Section: Introductionmentioning

confidence: 99%

Information Transmission and the Bullwhip Effect: An Empirical Investigation

Bray,

Mendelson

2012

Management Science

219

145

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T he bullwhip effect is the amplification of demand variability along a supply chain: a company bullwhips if it purchases from suppliers more variably than it sells to customers. Such bullwhips (amplifications of demand variability) can lead to mismatches between demand and production and hence to lower supply chain efficiency. We investigate the bullwhip effect in a sample of 4,689 public U.S. companies over . Overall, about two-thirds of firms bullwhip. The sample's mean and median bullwhips, both significantly positive, respectively measure 15.8% and 6.7% of total demand variability. Put another way, the mean quarterly standard deviation of upstream orders exceeds that of demand by $20 million. We decompose the bullwhip by information transmission lead time. Estimating the bullwhip's information-lead-time components with a two-stage estimator, we find that demand signals firms observe with more than three-quarters' notice drive 30% of the bullwhip, and those firms observe with less than one-quarter's notice drive 51%. From 197451%. From -199451%. From to 199551%. From -2008, our sample's mean bullwhip dropped by a third.

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The implications of information sharing on bullwhip effects in a toy supply chain

Cited by 28 publications

References 0 publications

Judgement and Supply Chain Dynamics

Judgement and Supply Chain Dynamics

Relationships between internal and external information systems integration, cost and quality performance, and firm profitability

Information Transmission and the Bullwhip Effect: An Empirical Investigation

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