Evaluating the Green Innovation Ability of Engineering Teams  in a Hesitation Fuzzy Environment

Yuhan Nie; jiafu su

doi:10.47654/v26y2022i5p53-76

Authors

Yuhan Nie International College, Krirk University Author
Jiafu Su International College, Krirk University Corresponding Author

DOI:

https://doi.org/10.47654/v26y2022i5p53-76

Keywords:

hesitant fuzzy set, multi-attribute decision-making, engineering team, green innovation ability, evaluation method

Abstract

Purpose: In this paper, the hesitant fuzzy multi-attribute decision-making method is used to present a green innovation ability (GIA) assessment technique for engineering teams.

Design/methodology/approach: In the evaluation method, we propose four evaluation indicators for GI input, GI implementation ability, GI development ability, and GI resource integration ability based on the evaluation indicators of GIA proposed by previous scholars, and use hesitant fuzzy sets as the expression tool for evaluation information. Thereafter, by improving the method proposed by Su et al. (2023) for positive and negative ideal points, this paper proposes a new evaluation method.

Findings: Through the use of this method, we found that it can fully consider the fuzziness and hesitancy of evaluators in uncertain environments, and express them in the form of fuzzy numbers. This shows that the method is viable, reasonable, and applicable to genuine evaluation procedures. Furthermore, this study provides a theoretical reference for the evaluation of engineering teams and other fields.

Originality/value: In this research, a decision-making reference point for the ideal point is proposed using the three-point estimate method, an integrated time estimation approach in the program evaluation and review technique (PERT). The research applies the hesitant fuzzy multi-attribute decision-making method to evaluate the green innovation capability of engineering teams by improving it. Further, the decision-making method is extended and applied to make some contributions to decision science.

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