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The effect of demand information sharing in a supply chain under demand uncertainty: a simulation study

Author(s): Rito, Pedro Varela

Date: 2012

Persistent ID:

Origin: Repositório Institucional da UNL

Subject(s): Supply chain; Simulation; Uncertain demand; Information sharing


The modern business environments are constantly subject to unpredictable events that can adversely influence the supply chain (SC) performance. In order to remain competitive, SCs are therefore striving to achieve greater coordination and collaboration among SC entities. The advances in technology in the area of information technology are enabling instantaneous information sharing amongst SC entities. Demand information sharing appears as a widely used tool to improve the SC performance. In this context, SC simulation appears as a fundamental tool to quantitatively analyze this management practice in a virtual system environment, enabling multiple scenario analysis. This dissertation intends to verify through the use of discrete event simulation, the impact of the presence of demand information sharing on the performance of a SC and whether this practice can reduce the impact of an uncertain customer demand in terms of the total SC costs and the service level. Considering that the customer demand follows a Normal distribution with an unknown standard deviation, three different scenarios are simulated using three distinct standard deviations. Further, two information sharing scenarios are considered, namely the presence and absence of demand information sharing. This analysis is applied on a case study that is built for this purpose. The software used to develop the simulation model and reproduce the operational behavior of the SC is Arena. The analysis of the simulation results indicates that an increase in the variability of the customer demand worsens all the studied performance measures. However, the introduction of demand information sharing improves the SC performance in terms of the SC costs.

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Document Type Master thesis
Language English
Advisor(s) Barroso, Ana; Machado, Virgínia
Contributor(s) Rito, Pedro Varela
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