The bullwhip effect: Progress, trends and directions

By Xun Wang, Stephen M. Disney. European Journal of Operational Research, 2016

387 citations recorded by the source corpus.

The bullwhip effect refers to the phenomenon where order variability increases as the orders move upstream in the supply chain. This paper provides a review of the bullwhip literature which adopts empirical, experimental and analytical methodologies. Early econometric evidence of bullwhip is highlighted. Findings from empirical and experimental research are compared with analytical and simulation results. Assumptions and approximations for modelling the bullwhip effect in terms of demand, forecast, delay, replenishment policy, and coordination strategy are considered. We identify recent research trends and future research directions concerned with supply chain structure, product type, price, competition and sustainability.

Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/0553fa4c811f79521b0160bac032cd749786beed

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In Management Information Systems

In Management Science and Operations Research

In Strategy and Management

Citations in the corpus

Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability (2020, neutral): “This concept is ifferent from the bullwhip effect ( Dolgui, Ivanov & Rozhkov, 020 ; Lee, Padmanabhan & Whang, 1997 ), as the bullwhip effect is riggered by small demand vulnerabilities but does not necessarily mply a severe operational failure ( Chatfield, Hayya & Cook, 2013 ; ang & Disney, 2016 ).”
Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain† (2019, background): “…risks such as demand fluctuations, and is described as the amplification of demand variation on production and ordering quantities in supply chains (SC) (Lee, Padmanabhan, and Whang 1997; Chen et al. 2000; Sterman 2000; Dejonckheere et al. 2004; Ouyang and Li 2010; Wang and Disney 2016).”
The inventory performance of forecasting methods: Evidence from the M3 competition data (2019, background): “The wellknown bullwhip effect and inventory amplification, commonly defined as the variance of order quantity (vo) and inventory level (vi), can be seen as quadratic cost functions (Wang and Disney, 2016).”
The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain (2017, background): “These characteristics may lead to the expensive bullwhip effect (Lee et al., 1997; Metters, 1997; Wang and Disney, 2016).”