Non-Linear Dynamics of Sustainable Communication and Financial Performance: U- and S-Shaped Effects in High-Risk Industries Moderated by Financial Development, ESG Divergence, and Reporting Mandates

Document Type : Original Article

Authors

1 Assistant Prof., Department of Accounting, Payame Noor University, Tehran, Iran.

2 Assistant prof., Department of Management, Faculty of Administrative Sciences and Economics, Arak University, Arak, Iran.

10.30699/ijf.2026.556667.1555
Abstract
Sustainable Communications (SC) is a strategic approach in industries, especially in high-risk sectors, and has gained great importance today. This study explores the non-linear dynamics (U-shaped and S-shaped) between sustainable communication (SC) and financial performance (FP) in high-risk industries, including oil and gas, petrochemicals, mining, and transportation, listed on the Tehran Stock Exchange and Iran Fara Bourse over the period 2015–2024 (48 companies). Utilizing panel regression, cross-sectional regression, quantile panel regression, and Granger causality tests, the analysis integrates organizational learning, supply chain perspectives, and stakeholder theory. Findings confirm U- and S-shaped relationships, suggesting that moderate SC enhances FP, whereas excessive communication may undermine stakeholder trust, with sustained efforts yielding long-term benefits. Financial sector development amplifies the positive effects of SC, while ESG rating divergence exacerbates the adverse impacts of over-communication. Sustainability reporting requirements reinforce the benefits of balanced SC. Quantile regressions reveal heterogeneity, with stronger SC effects in high-performing firms. Granger causality tests indicate unidirectional causality from SC to FP. Industry-specific analyses highlight superior performance in petrochemicals and challenges in transportation. The study offers practical implications for optimizing SC, strengthening financial sector development, and standardizing ESG reporting. Future research should incorporate granular ESG data and dynamic modeling approaches.

Keywords


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