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 Zavadskas,
Gwo-Hshiung Tzeng

Description

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

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