Journal Published Online: 24 November 2015
Volume 44, Issue 5

A Novel General Approach for Solving a Supplier Selection Problem

CODEN: JTEVAB

Abstract

Due to the progress of information technology and the era of globalization, supply chain management (SCM) is now the key activity to obtaining and maintaining the competitive advantage of firms in the global competitive environment. In order to maximize total supply chain profitability, supplier selection plays a very important role in supply chain management. However, the supplier selection process is a complex multiple-criteria decision making (MCDM) problem where both qualitative and quantitative aspects need to be considered. Moreover, there are many unknown, partly known, missing, or inexistent data in the process of collecting data from the supplier selection, increasing the difficulty of supplier selection. It cannot be fully solved by the traditional analytical hierarchy process (AHP) method. Therefore, this study integrated the AHP and the soft set approach for solving the supplier selection problem. The advantage of this proposed method in research is that it has not lost any expertise in providing useful information. A numerical example of the application was also presented. This study compared the results with the traditional AHP method for dealing with incomplete data. The results of the comparison showed that the approaches presented in this paper are preferable in terms of reflecting practical feasibility.

Author Information

Chang, Kuei-Hu
Department of Management Sciences, R.O.C. Military Academy, Kaohsiung, TW
Chain, Kai
Department of Computer and Information Science, R.O.C. Military Academy, Kaohsiung, TW
Wen, Ta-Chun
Ministry of Science and Technology, Hsinchu Science Park Bureau, Hsinchu, TW
Yang, Gino
Department of Computer Science and Information Management, Hungkuang University, Taichung, TW
Pages: 14
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE20150038
ISSN: 0090-3973
DOI: 10.1520/JTE20150038