Skip to main content

Impact of Demand Nature on the Bullwhip Effect. Bridging the Gap between Theoretical and Empirical Research

  • Conference paper
  • First Online:
Proceedings of the Seventh International Conference on Management Science and Engineering Management

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 242))

Abstract

The bullwhip effect (BE) consists of the demand variability amplification that exists in a supply chain when moving upwards. This undesirable effect produces excess inventory and poor customer service. Recently, several research papers from either a theoretical or empirical point of view have indicated the nature of the de- mand process as a key aspect to defining the BE. Nonetheless, they reached different conclusions. On the one hand, theoretical research quantified the BE depending on the lead time and ARIMA parameters, where ARIMA functions were employed to model the demand generator process. In turn, empirical research related nonlinearly the demand variability extent with the BE size. Although, it seems that both results are contradictory, this paper explores how those conclusions complement each other. Essentially, it is shown that the theoretical developments are precise to determine the presence of the BE based on its ARIMA parameter estimates. Nonetheless, to quan- tify the size of the BE, the demand coefficient of variation should be incorporated. The analysis explores a two-staged serially linked supply chain, where weekly data at SKU level from a manufacturer specialized in household products and a major UK grocery retailer have been collected.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Box GEP, Jenkins GM, Reinsel GC (1994) Time series analysis: Forecasting and Control. 3rd edn, Upper Saddle River, Prentice Hall, New Jersey

    Google Scholar 

  2. Byrne PJ, Heavey C (2006) The impact of information sharing and forecasting in ca- pacited industrial supply chains: A case study. International Journal of Production Economics 103(1):420–437

    Google Scholar 

  3. Cachon G, Randall T, Schmidt G (2007) In search of the bullwhip effect, M&som- Manufacturing & Service. Operations Management 9:457–479

    Google Scholar 

  4. Chen F, Drezner Z, Ryan JK et al (2000) The impact of exponential smoothing forecasts on the bullwhip effect. Naval Research Logistics 47(4):269–286

    Google Scholar 

  5. Dejonckheere J, Disney SM, Lambrecht MR et al (2003) Measuring and avoiding the bullwhip effect: A control theoretic approach. European Journal of Operational Research 147(3):567–590

    Google Scholar 

  6. Duc TTH, Luong HT, Kim YD (2008) A measure of bullwhip effect in supply chains with a mixed autoregressive-moving average demand process. European Journal of Operational Research 187(1):243–256

    Google Scholar 

  7. Fildes R, Goodwin P (2007) Against your better judgment? How organizations can improve their use of management judgment in forecasting. Interfaces 37(6):70–576

    Google Scholar 

  8. Fildes R, Goodwin P, Lawrence M et al (2009) Effective forecasting and jugdmental ad- justments: An empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting 25(1):3–23

    Google Scholar 

  9. Fransoo JC, Wouters MJF (2000) Measuring the bullwhip effect in the supply chain. Supply Chain Management: An International Journal 5(2):78–89

    Google Scholar 

  10. Geary S, Disney SM, Towill DR (2006) On bullwhip in supply chains-historical review, present practice and expected future impact. International Journal of Production Economics 101(1):2–18

    Google Scholar 

  11. Gilliland M (2010) Defining ‘demand’ for demand forecasting. The International Journal of Applied Forecasting (18):4–8

    Google Scholar 

  12. Lee HL, Padmanabhan V, Whang S (1997) The bullwhip effect in supply chains. Sloan Man- agement Review 38(3):93–102

    Google Scholar 

  13. Li G, Wang S, Yan H et al (2005) Information transformation in a supply chain: A simulation study. Computers & Operations Research 32(3):707–725

    Google Scholar 

  14. Luong HT (2007) Measure of bullwhip effect in supply chains with autoregressive demand process. European Journal of Operational Research 180(3):1086–1097

    Google Scholar 

  15. Schwartz G (1978) Estimating the dimension of a model, Annals of Statistics 6(2):461–464

    Google Scholar 

  16. Trapero JR, Fildes R, Davydenko A (2011) Nonlinear identification of judgmental forecasts effects at SKU level. Journal of Forecasting 30(5):490–508

    Google Scholar 

  17. Zotteri G (2013) An empirical investigation on causes and effects of the bullwhip-effect: Evidence from the personal care sector. International Journal of Production Economics 143(2):489–498

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Juan R. Trapero .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Trapero, J.R., Garc′ıa, F.P., Kourentzes, N. (2014). Impact of Demand Nature on the Bullwhip Effect. Bridging the Gap between Theoretical and Empirical Research. In: Xu, J., Fry, J., Lev, B., Hajiyev, A. (eds) Proceedings of the Seventh International Conference on Management Science and Engineering Management. Lecture Notes in Electrical Engineering, vol 242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40081-0_95

Download citation

Publish with us

Policies and ethics