Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

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

Risultato della ricerca: Article

1 Citazione (Scopus)

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.
Lingua originaleEnglish
Numero di pagine13
RivistaDefault journal
Stato di pubblicazionePublished - 2018

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Demand Sharing Inaccuracies in Supply Chains: A Simulation Study. / Bruccoleri, Manfredi; Cannella, Salvatore; Dominguez, Roberto; Framinan, Jose M.

In: Default journal, 2018.

Risultato della ricerca: Article

Bruccoleri, Manfredi ; Cannella, Salvatore ; Dominguez, Roberto ; Framinan, Jose M. / Demand Sharing Inaccuracies in Supply Chains: A Simulation Study. In: Default journal. 2018.
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AB - 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.

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