International Journal of Scientific Research and Engineering Development

The rapid digitalization of India’s economy has significantly amplified the demand for data infrastructure across major metropolitan cities, fostering the rise of large-scale data centers. However, this growth has simultaneously intensified environmental challenges, including high energy consumption and carbon emissions. Green data centers, which employ renewable energy, advanced cooling technologies, and sustainable IT hardware, offer a path toward responsible technological growth. Integrating these practices with corporate social responsibility (CSR) strategies enables businesses to align technological advancement with ecological accountability. In metropolitan regions such as Delhi, Mumbai, Kolkata, Chennai, Bengaluru, and Hyderabad, the transition to green data centers has become a central element of corporate governance and sustainability. Leading operators are utilizing solar, wind, and hybrid energy models to reduce their carbon footprints while improving operational efficiency. Furthermore, government collaborations with organizations such as TERI and NSEFI are accelerating renewable energy integration into IT infrastructure, reinforcing India’s broader sustainability agenda. This transition symbolizes not only environmental stewardship but also strategic CSR-driven competitiveness among urban corporations.
This paper investigates the relationship between green data center adoption and CSR enhancement within India’s metropolitan context. It explores the environmental, economic, and managerial impacts of green transformation in data infrastructure and its implications on corporate reputation and governance. Using empirical and secondary data analysis, the study highlights best practices, challenges, and long-term policy implications for firms adopting eco-responsible IT solutions. The findings aim to support corporate decisionmakers and policymakers in promoting sustainable business ecosystems through technologically advanced yet responsible data solutions.