Date of Award

2014

Publication Type

Doctoral Thesis

Degree Name

Ph.D.

Department

Industrial and Manufacturing Systems Engineering

Keywords

Fast Fashion Apparel Industry, Perishable Product, Risk Assessment, Supply Chain, System Dynamics Methodology

Supervisor

Pasek, Zbigniew

Rights

info:eu-repo/semantics/openAccess

Abstract

With the fast progress of science and technology and with the continuously growing customer expectations, share of merchandise exhibiting characteristics of perishability is on the rise. Perishable products, through their own nature, are subject to decay, deterioration or obsolescence. As a result, their usefulness, value or functionality is gradually reduced or even lost in a short window of time and cannot be regained if it is not used or sold within a specific time window. When producing perishable products, all stages of the supply chain are exposed to much higher uncertainty than in the case of durable products, which directly means higher risk. The phases of inventory planning, lead time control, and demand forecasting for perishable products play a critical role in the overall effectiveness of the supply chain. For this reason, the system dynamics methodology, a simulation and modeling technique developed specifically to address the long term and dynamic management issues, is adopted in this study. The focus of the proposed model is on the interaction between physical processes, information flows and managerial policies of a three-level supply chain for perishable products, in general, and fast fashion apparel supply chain, in particular, so as to create the dynamics of the variables of interest. The values of supply chain key factors such as, for example, inventory, backlogs, stock-outs, forecast error, cost, and profit for each time period are some of the outputs of the proposed model. Moreover, the Conditional Value at Risk (CVaR) measure is applied to quantify and analyze the risks associated with the supply chain for this type of product and also to determine the expected value of the losses and their corresponding probabilities. With the focus on three prominent categories of risks including risks of delays, forecast, and inventory, multiple business situations for effective strategic planning and decision making are generated and analyzed.

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