The impact of innovation on ESG performance

Abstract

Purpose: The main objective of the paper is to explore how different types of innovations contribute to ESG performance in companies. The study aims to distinguish the specific effects of technological and organizational innovations on environmental, social, and governance dimensions, thereby clarifying their role in sustainable corporate development. Methodology: To achieve the research objective, data were collected from 113 companies in Serbia during 2025. Structural Equation Modelling was applied to examine the relationships between types of innovations and ESG performance dimensions, enabling a precise assessment of their individual impacts. Findings: The study confirms that innovations are essential for improving ESG performance. Technological innovations have the strongest impact on environmental outcomes, while organizational innovations are most influential in strengthening governance practices. Social performance is positively affected by both types of innovations, though to a lesser extent. Originality/value: This research provides novel insights into the differentiated effects of innovation types on ESG dimensions, contributing to the literature by linking innovation strategies with sustainability outcomes in a transitional economy context. It highlights the importance of distinguishing between technological and organizational innovations when evaluating ESG performance. Practical implications: The findings can help hotel managers and policymakers design innovation strategies that align with sustainability goals. Companies seeking to improve environmental outcomes should prioritize technological innovations, while those aiming to strengthen governance should focus on organizational innovations. These insights are particularly valuable for decision makers in emerging economies striving to balance competitiveness with ESG commitments. Limitations: The study is limited to companies operating in Serbia, which may restrict the generalizability of findings to other contexts. Additionally, the analysis is based on cross-sectional data collected in 2025, preventing the assessment of long-term innovation effects. Future research should expand to comparative international samples and longitudinal designs.