The role of corporate environmental ethics in shaping environmental management accounting adoption under the institutional theory

  • 466 Views
  • 147 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This study aims to investigate the complex association between institutional pressure, adoption of environmental management accounting (EMA), and financial performance, with corporate environmental ethics as a moderating component. It explains why and how firms adopt EMA in response to institutional demand to factor environmental factors into their strategic decision-making processes. Quantitative information is gathered using a structured questionnaire from 256 manufacturing companies’ environmental managers and executives who monitor environmental practices and policies and decision-makers who shape business environmental ethics and strategy in the Indian state of Karnataka. Data are analyzed using SmartPLS 4, and PLS-SEM tests the hypotheses. The results show that coercive pressure (β = 0.244, p = 0.000), mimetic pressure (β = 0.221, p = 0.000), and normative pressure (β = 0.209, p = 0.000) have a major role in determining the rate of EMA adoption. It is further identified that EMA adoption (β = 0.217, p = 0.000) positively influences the organization's financial performance. Furthermore, EMA adoption mediates the relationship between coercive pressure (β = 0.053, p = 0.000), normative pressure (β = 0.045, p = 0.000), mimetic pressure (β = 0.048, p = 0.000), and firm’s financial performance. Coercive pressure is associated with higher EMA adoption, although the impact of this link is moderated by corporate environmental ethics (β = 0.069, p = 0.000).

view full abstract hide full abstract
    • Figure 1. Research framework
    • Figure 2. Structural model of PLS-SEM
    • Table 1. Demographics of respondents
    • Table 2. Reliability and validity
    • Table 3. Discriminant validity
    • Table 4. R-Square results
    • Table 5. f-square statistics
    • Table 6. Direct effects
    • Table 7. Indirect effects
    • Table 8. Moderating effects
    • Table A1. Questionnaire: Items for survey scale
    • Conceptualization
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Data curation
      Chetanraj D. B., J. P. Senthil Kumar
    • Formal Analysis
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Investigation
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Methodology
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Software
      Chetanraj D. B., J. P. Senthil Kumar
    • Supervision
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Validation
      Chetanraj D. B., J. P. Senthil Kumar
    • Visualization
      Chetanraj D. B., J. P. Senthil Kumar
    • Writing – original draft
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Writing – review & editing
      Chetanraj D. B., J. P. Senthil Kumar, Velaga Sri Sai, Ramegowda K. V.
    • Project administration
      J. P. Senthil Kumar