Bui Thi Hai Yen
Beijing Jiaotong University, Beijing, China

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RELATIONSHIP BETWEEN ESG DISCLOSURES AND FINANCIAL PERFORMANCE IN SINGAPORE PUBLIC LISTED LOGISTICS COMPANIES: A TEXT MINING APPROACH Handy Bugiman; Bui Thi Hai Yen; Nunung Ayu Sofiati; Rikko Putra Youlia; Samuel Darwisman
Journal of Scientech Research and Development Vol 8 No 1 (2026): JSRD, June 2026
Publisher : Ikatan Dosen Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56670/jsrd.v8i1.1631

Abstract

This study investigates the relationship between environmental social and governance (ESG) disclosure density and financial performance within the Singapore logistics sector. It explores the theoretical tension between the Resource Based View and Legitimacy Theory by examining whether sustainability reporting acts as a strategic differentiator or a mere compliance mechanism. Analyzing a purposive sample of seventeen publicly traded logistics entities on the Singapore Exchange for the 2023 financial period this study employs a quantitative deductive design. A custom Python based computer aided text analysis script was developed to extract and normalize ESG disclosures. To mitigate symbolic greenwashing a novel boilerplate subtraction algorithm was introduced to penalize repetitive text. Nonparametric statistical methods were utilized to test main effects sequential pathways and the moderating roles of firm size and financial leverage. The results reveal no statistically significant direct correlation between aggregate ESG disclosure density and financial performance. This null finding challenges the Resource Based View and strongly supports Legitimacy Theory suggesting that sustainability reporting in this regulated hub functions primarily as a mandatory compliance exercise to maintain a social license to operate. However, moderation analysis indicates a descriptive divergence showing that large firms are better equipped to convert substantive sustainability initiatives into tangible operational advantages. By integrating an algorithmic boilerplate penalty this research provides a scalable objective methodological alternative to opaque third party ESG rating agencies. It contributes robust empirical evidence that generic reporting volume does not yield financial dividends urging industry executives and regulators to prioritize operational substance over disclosure form.