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Voluntary green technology adoption: The effects of regulatory uncertainty and competition

Author

Listed:
  • Du, Shaofu
  • Huang, Chong
  • Yan, Xia
  • Tang, Wenzhi

Abstract

Stricter environmental regulations force firms to adopt green technology. However, firms have realized that the more they voluntarily adopt green technology, the higher the probability that stricter new regulations will be enforced. Thus, firms may delay adopting green technology to resist stricter regulations. Conversely, some firms choose voluntary adoption to gain a market advantage over their rivals. Considering the impact of firms’ adoption decisions on the enforcement of new regulations and product competition, this study develops a two-period game model to investigate how competing firms adopt green technology when facing a potentially stricter regulation. The Nash equilibrium shows that if the basic probability of the new regulation is moderate, firms will differentiate their products through green technology to alleviate price competition; if the probability is high, firms will voluntarily adopt green technology; otherwise, they will wait until the government enforces a stricter regulation and mandates them to adopt green technology. Interestingly, our results show that potentially stricter regulations will induce firms to behave strategically. When firms’ green cost difference is small, competing firms will collude to delay stricter regulations by not adopting green technology. However, when firms’ green cost difference is significant, the low-cost firm tends to adopt green technology to lobby for new regulations and gain a cost advantage. Our work not only provides an economic explanation for the different adoption behaviors of firms but also provides managerial insights for competing firms as well as policy insights for the government.

Suggested Citation

  • Du, Shaofu & Huang, Chong & Yan, Xia & Tang, Wenzhi, 2024. "Voluntary green technology adoption: The effects of regulatory uncertainty and competition," European Journal of Operational Research, Elsevier, vol. 315(2), pages 528-540.
  • Handle: RePEc:eee:ejores:v:315:y:2024:i:2:p:528-540
    DOI: 10.1016/j.ejor.2023.11.042
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