Do ESG and SDG-9 innovations enhance financial performance? Empirical evidence from India’s Top 100 listed firms (2019–2023)

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Type of the article: Research Article

Abstract
Sustainable innovation has become an important driver of corporate value creation in emerging economies like India, where firms increasingly align their operations with Environmental, Social, and Governance (ESG) practices and Sustainable Development Goal 9 (SDG-9). Despite this rising importance, the financial impact of ESG and SDG-9 innovations on firm performance remains underexplored in the Indian context. This study aims to empirically examine the impact of ESG and SDG-9 innovations on firm value, profitability, and shareholder returns among the top 100 listed Indian companies during the period 2019–2023. Using panel data drawn from the Bloomberg and Refinitiv databases, the study applies multiple regression models and random-effects estimations to evaluate the relationships between innovation indicators (ESG and SDG-9 scores) and financial metrics such as Tobin’s Q, Return on Assets (ROA), and Return on Equity (ROE). The findings reveal that ESG innovation scores do not have a statistically significant effect on firm value and profitability. In contrast, SDG-9 innovation exhibits a positive and significant relationship with both ROA and ROE, indicating that companies integrating infrastructure, industrialization, and innovation goals achieve superior financial performance. On average, firms reporting SDG-9 innovations show a 4.27-point higher ROE and 0.51-point improvement in ROA than non-reporting firms. These results highlight that SDG-9 aligned innovation contributes directly to financial value creation, whereas ESG innovation yields more intangible or long-term benefits, offering critical insights for managers, investors, and policymakers promoting sustainable business growth in India.

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    • Table 1. Summary of variables
    • Table 2. Descriptive statistics
    • Table 3. Pearson correlation matrix
    • Table 4. Random effect regression results, Model A
    • Table 5. Random effect regression results, Model B
    • Table 6. Random effect regression results, Model C
    • Data curation
      Manoj Panda
    • Formal Analysis
      Manoj Panda, Manohar Kapse, Vinod Sharma
    • Writing – original draft
      Manoj Panda, Manohar Kapse, Vinod Sharma, Laszlo Vasa
    • Writing – review & editing
      Manoj Panda, Yogesh Mahajan, Laszlo Vasa
    • Conceptualization
      Yogesh Mahajan, Manohar Kapse, Vinod Sharma, Laszlo Vasa
    • Resources
      Yogesh Mahajan, Laszlo Vasa
    • Supervision
      Yogesh Mahajan
    • Methodology
      Manohar Kapse, Vinod Sharma
    • Funding acquisition
      Laszlo Vasa
    • Visualization
      Laszlo Vasa