PBESProceedings of Business and Economic Studies2209-26412209-265XBio-Byword Scientific Publishing Pty. Ltd.10.26689/pbes.v9i6.15474ArticleEmploying Interval Grey Relational Analysis in ESG Investment Decision-Making Based on Ratingshttps://artdesignp.com/journal/PBES/9/6/10.26689/pbes.v9i6.15474ZhengZhaoyi2026962026-07-15ESG ratings have gradually become an important reference basis in investment decisions. Currently, different rating agencies often give significant differences in ESG scores to the same enterprise based on their own assessment criteria, data sources, and weight settings. The inconsistent scores caused by such multi-source heterogeneous data increase the cognitive uncertainty and decision-making complexity of investors when utilizing ESG information, affecting the accuracy and reliability of investment judgments. In this paper, by introducing the Interval Number Grey Relational Analysis (IGRA) method, an enterprise investment ranking model based on multi-source ESG scores is constructed. The scores from different rating agencies are integrated into the form of interval numbers, effectively reflecting the fluctuation range of the scores. And with the help of the grey system theory, the similarity degree between enterprises and ideal reference objects is measured. Realize the comprehensive processing and scientific ranking of multi-dimensional uncertain information. An empirical analysis was conducted based on the ESG rating data to verify the effectiveness of the method. This research provides methods for ESG investment practices and also offers theoretical references for dealing with uncertain investment issues.

Chen S, Fan M, 2024, ESG Ratings and Corporate Success: Analyzing the Environmental Governance Impact on Chinese Companies’ Performance. Frontiers in Energy Research, 12: 1371616.

Wedajo AD, Salah AA, Bhat MA, et al., 2024, Analyzing the Dynamic Relationship Between ESG Scores and Firm Value in Chinese Listed Companies: Insights From Generalized Cross-Lagged Panel Model. Discover Sustainability, 5(1): 336.

He Z, Guo Z, Lin P, et al., 2020, A Method for Interval-Valued Intuitionistic Fuzzy Multiple Attribute Decision Making Based on Fuzzy Entropy. Journal of Intelligent & Fuzzy Systems, 38(6): 7779–7785.

Jin F, Pei L, Chen H, et al., 2014, Interval-Valued Intuitionistic Fuzzy Continuous Weighted Entropy and Its Application to Multi-Criteria Fuzzy Group Decision Making. Knowledge-Based Systems, 59: 132–141.

Zhao H, Lu J, 2015, Interval Grey Relational Analysis and Its Application in Multi-Criteria Decision Making. Expert Systems With Applications, 42(9): 4603–4612.

Ju-Long D, 1982, Control Problems of Grey Systems. Systems & Control Letters, 1(5): 288–294.

Hou J, 2010, Grey Relational Analysis Method for Multiple Attribute Decision Making in Intuitionistic Fuzzy Setting. J. Convergence Inf. Technol., 5(10): 194–199.

Dey PP, Pramanik S, Giri BC, 2015, An Extended Grey Relational Analysis Based Interval Neutrosophic Multi-Attribute Decision Making for Weaver Selection. Journal of New Theory, 2015(9): 82–93.

Kahraman C, Cebeci U, Ulukan Z, 2003, Multi-Criteria Supplier Selection Using Fuzzy AHP. Logistics Information Management, 16(6): 382–394.

Moore RE, Yang CT, 1959, Interval Analysis I. Technical Document LMSD-285875, Lockheed Missiles and Space Division, Sunnyvale, CA, USA.

Shannon CE, 1948, A Mathematical Theory of Communication. The Bell System Technical Journal, 27(3): 379–423.