GREEN IT GOVERNANCE AND CORPORATE SUSTAINABILITY PERFORMANCE: A LINEAR REGRESSION ANALYSIS OF MULTINATIONAL FIRMS
Keywords:
Green IT governance, corporate sustainability performance, energy efficiency, e-waste compliance, sustainability reporting, linear regression, Pakistan, multinational firmsAbstract
The escalating global emphasis on environmental sustainability has positioned Green Information Technology (IT) governance as a strategic mechanism for corporations to align technological operations with ecological objectives. However, empirical evidence from developing economy contexts remains limited. This study examined the relationship between Green IT governance implementation level and three dimensions of corporate sustainability performance: perceived energy efficiency, e-waste reduction compliance, and corporate sustainability reporting quality. A quantitative, cross-sectional design was employed, collecting five-point Likert scale data from 150 employees across two multinational firms operating in Karachi, Pakistan, SAP and SysTech International (an IBM partner). Simple linear regression analysis was conducted separately for each dependent variable. Results revealed that Green IT governance significantly predicted all three sustainability outcomes (p < .001). The strongest effect emerged for e-waste reduction compliance (β = 0.508), followed by perceived energy efficiency (β = 0.483), and corporate sustainability reporting quality (β = 0.382). These findings confirm the central hypothesis that higher levels of Green IT governance are associated with improved sustainability performance. The study contributes new empirical evidence from Pakistan's IT sector, addressing a geographic gap in the existing literature. Practically, the results suggest that investments in structured IT governance frameworks yield measurable environmental returns, even under relatively weak regulatory pressures. Limitations include the cross-sectional design, self-reported data, and sample restriction to two firms. Future longitudinal research across diverse organizational contexts is recommended to establish causality and enhance generalizability.
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