Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead

被引:135
作者
Chai, Junyi [1 ]
Ngai, Eric W. T. [2 ]
机构
[1] Hong Kong Baptist Univ, Div Business & Management, Beijing Normal Univ, United Int Coll, Zhuhai, Peoples R China
[2] Hong Kong Polytech Univ, Dept Management & Mkt, Kowloon, Hong Kong, Peoples R China
关键词
Supplier selection; Decision making; Big data; Multiple criteria; Artificial intelligence; Literature review; ANALYTIC NETWORK PROCESS; BOTTOM-LINE APPROACH; ORDER ALLOCATION; INTEGRATED APPROACH; PROSPECT-THEORY; SUPPORT-SYSTEM; PERFORMANCE EVALUATION; MODELING PREFERENCES; CHAIN CONFIGURATION; FUZZY TOPSIS;
D O I
10.1016/j.eswa.2019.112903
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Supplier selection (SS) is considered a sophisticated, application-oriented, decision-making (DM) problem and has received considerable attention. In the past two decades, DM theories and techniques continue to be incorporated into and contribute to the development of SS applications. Maintaining the pace of the rapid transitions in this field, this paper systematically reviews the relevant articles published between 2013 and 2018. Articles that orient various DM techniques are selected and analyzed under a well-established framework. State-of-the-art developments in the adoption of DM techniques are summarized in a SS process. We pay particular attention to promising directions that can dominate future research in this field. This paper further extends the history of several interacting fields, including big data and economic theories, toward methodological rather than application dimensions. The potential of such fields for SS is discussed from an interdisciplinary perspective. (C) 2019 Elsevier Ltd. All rights reserved.
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页数:16
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