
A literature review of criteria selection in supplier
Author(s) -
Agus Ristono,
_ Pratikto,
Purnomo Budi Santoso,
Ishardita Pambudi Tama
Publication year - 2018
Publication title -
journal of industrial engineering and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.385
H-Index - 29
eISSN - 2013-8423
pISSN - 2013-0953
DOI - 10.3926/jiem.2203
Subject(s) - selection (genetic algorithm) , multiple criteria decision analysis , originality , computer science , management science , supplier evaluation , operations research , engineering , supply chain management , machine learning , supply chain , business , marketing , qualitative research , social science , sociology
Purpose: This paper proposes a new model for further research on how to select criteria in supplier selection, through a literature review and analysis of the advantages and disadvantages of previously used methods.Design/methodology/approach: The methods used to select criteria in supplier selection were extracted from various online academic databases. The weaknesses and advantages of these methods were then analyzed. Based on these findings, several opportunities for improvement are proposed for further research. Finally, criteria design methods for the selection of suppliers are proposed using statistical multi-criteria decision making (S-MCDM) methods.Findings: Direction and guidance for subsequent research to select the criteria used in supplier selection, based on the advantages and disadvantages of the decision methods used.Research limitations/implications: Limitations of this study are that it is focused on the methods of criteria design in supplier selection.Practical implications: This study can provide a research direction on the selection of criteria for supplier selection.Social implications: This study provides ongoing guidance and avenues for further research.Originality/value: New ideas for working out the developmental strategy for criteria selection are provided by statistical MCDM methods in supplier selection.