Green it Adoption as CSR - Insights from Indian it Companies
U Nisha et al.
What the paper says
In today's business landscape, the fusion of Information Technology (IT) and Corporate Social Responsibility (CSR) is redefining how companies balance growth with sustainability. A key element of this shift is the adoption of Green Information Technology (GIT) strategies, aimed at reducing the environmental footprint of IT processes. This study investigates the adoption of Green Information Technology (GIT) strategies within Indian IT companies as part of their Corporate Social Responsibility (CSR) efforts. The research aims to map GIT adoption trends, identify key motivations and barriers, and assess the impact on organizational performance and CSR outcomes. A mixed-methods approach, combining surveys and case studies, was used to analyze data from 35 Indian IT firms. Findings reveal that larger, financially robust companies lead GIT adoption, driven by sustainability commitments and internal readiness. Key strategies include energy-efficient data centers and cloud computing, though smaller firms face barriers like high costs and limited awareness. Government incentives and industry collaboration are highlighted as crucial enablers for wider GIT adoption. Case studies of major IT firms—Infosys, Wipro, HCL, and TCS—demonstrate that early investment in green technologies leads to operational efficiency, cost savings, and enhanced corporate reputation. The study concludes that successful GIT implementation strengthens CSR, improves environmental stewardship, and enhances business competitiveness, particularly with government and industry support. This research provides actionable insights for policymakers and industry leaders, emphasizing the importance of collaboration in driving sustainable practices across the Indian IT sector.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.