A decision support system for procurement risk management in the presence of spot market
In the presence of spot market, this paper presents a decision support system to model risks for procurement processes and to design a robust purchasing plan, including supplier selection and order allocation. Taking advantages of contract supplier and spot market, the buyer can better meet business...
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Main Authors: | , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
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Online Access: | https://hdl.handle.net/10356/106814 http://hdl.handle.net/10220/16656 http://dx.doi.org/10.1016/j.dss.2012.12.031 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | In the presence of spot market, this paper presents a decision support system to model risks for procurement processes and to design a robust purchasing plan, including supplier selection and order allocation. Taking advantages of contract supplier and spot market, the buyer can better meet business requirements in this dynamic business environment. However, there are limitations of existing methods for modeling multiple correlated risks to support decision makers for allocating orders among multiple suppliers in the presence of spot market. Therefore, Monte Carlo simulation algorithm termed as Expected Profit–Supply at Risk (A-EPSaR) is proposed to quantify each supplier's risk so as to let decision maker realize the trade-off between profit and risk. The goal programming model helps to allocate orders among the supplier pool and the contract-spot allocation model can assign orders between the spot market and the supplier pool, respectively. The significance of this paper is to propose a novel decision support framework which helps the buyer to make optimal and robust procurement decision including supplier selection and order allocation among multiple supplier sources in the existence of correlated demand, yield and spot price uncertainties. A case study is used to illustrate the performance of the proposed framework and the proposed methods show the promising result. |
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