Data for: Data-driven hybrid multiple attribute decision-making model for green supplier evaluation and performance improvement
Published: 16 September 2019| Version 1 | DOI: 10.17632/fm7v4dzpfs.1
Contributors:
James J.H. Liou, Yen-Ching Chuang, Edmundas Kazimieras Zavadskas, Gwo-Hshiung TzengDescription
The historical audit data for eight attributes was organized by the three-level interval discretization method: the top third, middle third, and bottom third for the full range of each attribute. Based on the suppliers’ performance, the levels of each attribute were separated into “H (i.e., 1),” “M (i.e.,2),” and “L(i.e., 3)”.
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Categories
Data Mining, Multi-Criteria Decision Making, Supplier Development, Supplier Selection, Supplier Management