Application of decision-making techniques in supplier selection: A systematic review of literature
Introduction
Supplier selection (SS) has received considerable attention for its significant effect toward successful Logistic and supply chain management (LSCM). At least two valuable academic surveys had well reviewed the literature on SS. Jain, Wadhwa, and Deshmukh (2009) reviewed the main approaches to supplier-related issues including SS, supplier–buyer relationships, and supplier–buyer flexibility in relationships based on a summary of existing research before 2007. Ho, Xu, and Dey (2010) analyzed multicriteria decision making (MCDM) approaches for SS based on journal articles from 2000 to 2008. However, great developments on SS have emerged over the last five years. A large number of new ideas, techniques, and approaches have been contributing to this promising area. Previous surveys are not keeping pace. Therefore, we believe that a new and systematic survey is useful for consolidating the most recent research efforts on this area.
In this paper, we comprehensively collected the literature associated with the descriptors “supplier selection,” “vendor selection,” and “decision making” from academic databases including Science Direct, Emerald, Springer-Link Journals, IEEE Xplore, Academic Search Premier, and World Scientific Net. After a methodological decision analysis of all collected articles, we reviewed 123 international journal articles published from 2008 to 2012. We attempt to answer the following four questions: (1) Which decision-making (DM) techniques have frequently been applied? (2) What are the relationships and categories among these DM techniques? (3) How can the DM techniques discussed in literature be effectively integrated to achieve complex decision goals? (4) What are the development status and research trends for uncertain SS?
The emerging trend in current research is the integration of DM techniques in constructing an effective decision model to address practical and complex SS problems, particularly for the consideration of multitudinous uncertainty factors. Given the diversity and the complexity of SS research, we particularly use a methodological decision analysis framework for the selection of the collected articles. This framework provides a guide for the analysis of the literature based on four aspects: (1) decision problems, (2) decision makers, (3) decision environments, and (4) decision approaches. First, we confine our survey on structural SS and thus eliminate the literature that discusses semi-structural or non-structural decision problems. Consequently, a total of 123 articles are selected for detailed review. Second, the literature that involves multiple decision makers as a group is specifically indicated as reference for readers. Third, we classify the selected articles into seven categories after a decision environment analysis. Fourth, the emerging decision approaches are investigated in detail. Specifically, 26 DM techniques are independently reviewed from three perspectives: MCDM techniques, mathematical programming (MP) techniques, and artificial intelligence (AI) techniques. Major integrated approaches are separately reviewed. These approaches include the integrated analytic hierarchy process (AHP), integrated analytic network process (ANP), integrated data envelopment analysis (DEA), and integrated uncertain approaches, among others.
The remainder of this paper is organized as follows: Section 2 presents the research methodology. This section describes the methods for selecting the literature. In Section 3, we use a methodological decision analysis model to sort the selected articles and then subsequently form a summary table. Section 4 provides a detailed literature review on the DM techniques. Section 5 gives suggestions for future works. We conclude this paper in Section 6.
Section snippets
Research methodology
The research methodology of this survey is depicted in Fig. 1. Our initial objective is to investigate the applications of DM techniques in current research on SS. Thus, we define the following conditions to limit our collection of the articles:
- 1.
Only articles that had been published on decision sciences, computer sciences, or business management-related fields were selected because such articles are most possibly in accordance with the focus of this survey. The articles were searched from
Methodological decision analysis
SS is a typical DM activity. Considering its diversity and complexity, we establish a methodological decision analysis model for a standardized analysis of all collected articles. This model contains four analytic aspects: (1) decision problems, (2) decision makers, (3) decision environments, and (4) decision approaches.
Categorical reviews of decision-making techniques
Considering the practical complexity of SS, current research tends to integrate multiple DM techniques into a hybrid decision approach. In the beginning of this section, we systematically summarized the 26 DM techniques that had been integrated into the decision approaches discussed in our reviewed literature. We then separately reviewed six kinds of major integrated approaches. These approaches include the integrated AHP approaches in Section 4.2, the integrated ANP approaches in Section 4.3,
Distribution of Articles by Journal
Table 4 provides the distribution of the articles based on the journal in which they appeared. The articles related to the application of DM techniques for SS are distributed across 15 journals that cover a wide array of disciplines, including IS, operation research, soft computing, and production management. The journal Expert Systems with Applications contains the most relevant articles, comprising 55 out of the 123 articles reviewed (44.7%). Two journals with similar scopes, International
Conclusion
This paper provides a systematic literature review on articles published from 2008 to 2012 on the application of DM techniques for SS. We aim to analyze the collected articles from four analytical aspects: decision problems, decision makers, decision environments, and decision approaches. A total of 123 journal articles were carefully selected and reviewed in detail. We systematically summarized 26 applied DM techniques from three perspectives: MCDM, MP, and AI. The techniques that integrated
Acknowledgments
The authors are grateful for the partial support of CRG grants G-U756, G-YL14 of The Hong Kong Polytechnic University.
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