On the bullwhip and inventory variance produced by an ordering policy

By Stephen M. Disney, Denis R. Towill. 2003

397 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Management Information Systems

View Paper: https://www.semanticscholar.org/paper/906632f5638389e8bf721de451550efb337fa29e

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In Industrial and Manufacturing Engineering

In Management Information Systems

Citations in the corpus

Closed-loop supply chains: What reverse logistics factors influence performance? (2016, background): “(15)), proposed by Disney and Towill (2003).”
The application of discrete event simulation and system dynamics in the logistics and supply chain context (2012, methodology): “26 No Article BE PFD ISH IPM PPSCH DTP BPR CP DR SP RCP SCI SCS SS CR SCO RL 30 Disney and Towill 2003c [37] SD SD SD 31 Dong and Chen 2005a [38] DES 32 Dong and Chen 2005b [39] DES DES DES 33 Fiala 2005 [40] SD SD 34 Fleisch and Tellkamp 2005 [41] DES DES DES 35 Fleischmann et al 2003 [42] DES DES ”
Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain† (2019, methodology): “The rationale behind this formula is the standard analysis of order variance as a measure for bullwhip effect computation (Disney and Towill 2003; Ivanov, Tsipoulanidis, and Schönberger 2019).”
The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains (2003, background): “Furthermore, we consider demand signal processing and non-zero lead times to be encompassed to the ‘‘demand amplification’’ or the ‘‘Forrester Effect’’ after Jay Forrester (1961) who encountered the problem in many real-world supply chains and demonstrated it via DYNAMO simulation.”
On bullwhip in a family of order-up-to policies with ARMA(2,2) demand and arbitrary lead-times (2009, neutral): “See, for instance, Disney and Towill (2003) and Dejonckheere, Disney, Lambrecht and Towill (2003).”
Dynamic modeling and control of supply chain systems: A review (2008, background): “Motivated by the need to develop a new framework that could be used as a base for seeking new novel control laws and/or new feedback paths in production/inventory systems, Towill [21] presented the inventory and order based production control system (IOBPCS) in a block diagram form, extending the wo”
The Bullwhip Effect in Supply Chains (2014, methodology): “One example is the use of vendor-managed inventory in supply chains to reduce the variance of orders (Disney & Towill, 2003a; Hohmann & Zelewski, 2011).”
Exploring the oscillatory dynamics of a forbidden returns inventory system (2014, positive): “This policy determines the replenishment order quantity as the sum (cid:3)the demand forecast, plus a fraction of inventory discrepancy, plus a fraction of work-in-process discrepancy(cid:4) (Disney and Towill, 2003a).”
Reducing the bullwhip effect: Looking through the appropriate lens (2007, background): “This will be exact if behaviour is linear (Dejonckheere et al. 2002, Disney and Towill, 2002, Disney and Towill 2003, Dejonckheere et al. 2004), but more and more tenuous as non-linearities impact.”