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Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

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  • Salvatore Cannella
  • Roberto Dominguez
  • Jose M. Framinan
  • Manfredi Bruccoleri

Abstract

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.

Suggested Citation

  • Salvatore Cannella & Roberto Dominguez & Jose M. Framinan & Manfredi Bruccoleri, 2018. "Demand Sharing Inaccuracies in Supply Chains: A Simulation Study," Complexity, Hindawi, vol. 2018, pages 1-13, July.
    • Handle: RePEc:hin:complx:1092716
    DOI: 10.1155/2018/1092716
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    References listed on IDEAS

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    1. F J Arcelus & S Kumar & G Srinivasan, 2007. "Manufacturer's pricing strategies in a single-period framework under price-dependent stochastic demand with asymmetric risk-preference information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(11), pages 1449-1458, November.
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    Cited by:

    1. Nguyen, Duy Tan & Adulyasak, Yossiri & Landry, Sylvain, 2021. "Research manuscript: The Bullwhip Effect in rule-based supply chain planning systems–A case-based simulation at a hard goods retailer," Omega, Elsevier, vol. 98(C).

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