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Leveraging 4IR Technologies as a Corporate Social Responsibility to Reduce Environmental Impact in the Extractive Industry

In: Corporate Social Responsibility in Developing Countries

Author

Listed:
  • Tessa Reddy

    (Durban University of Technology)

  • Stanley Chibuzor Onwubu

    (Durban University of Technology)

Abstract

Recently, the natural environment has been at the forefront of discussions concerning global warming and climate change. The negative ramifications of mining, oil, and gas industries have attracted international attention. Stakeholders are more aware and concerned about human activities and their negative impact on the natural environment. In particular, the extractive industry, such as mining, oil, and gas, contributes heavily to environmental pollution, degradation, and resource depletion. Corporate social responsibility is tasked with ensuring that all industries implement best practices to ensure the safety of humans and the natural environment. Therefore, industries are seeking ways in which they can positively contribute to combating climate change and saving the planet. Hence, the adoption of 4IR technologies, namely, artificial intelligence, the Internet of Things, machine learning, and robotics, is critical to helping the extractive industry reduce environmental degradation. This chapter highlights the importance of adopting 4IR technologies in the extractive industry to help reduce the negative impact on people and the natural environment while simultaneously fulfilling organizational corporate social responsibility.

Suggested Citation

  • Tessa Reddy & Stanley Chibuzor Onwubu, 2023. "Leveraging 4IR Technologies as a Corporate Social Responsibility to Reduce Environmental Impact in the Extractive Industry," CSR, Sustainability, Ethics & Governance, in: Steven Kayambazinthu Msosa & Shame Mugova & Courage Mlambo (ed.), Corporate Social Responsibility in Developing Countries, pages 47-64, Springer.
  • Handle: RePEc:spr:csrchp:978-3-031-27512-8_4
    DOI: 10.1007/978-3-031-27512-8_4
    as

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