As organizations become increasingly digital, the environmental impact of digital infrastructures is gaining growing attention within ESG agendas. However, many organizations still struggle to translate digital infrastructure data into clear, measurable, and reliable ESG reporting outcomes. This study develops and empirically tests a socio-technical model explaining how organizations achieve ESG measurement and reporting readiness through sustainable computing practices. Drawing on a quantitative cross-sectional survey of 312 respondents from government, private, and educational organizations in Saudi Arabia and the GCC region, the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis (MGA). The findings reveal that organizational drivers are the strongest predictors of sustainable computing practices, while organizational barriers exert significant negative effects on adoption. Sustainable computing practices play a critical mediating role by enabling organizations to transform fragmented digital data into structured and credible ESG reporting systems. Sectoral differences further highlight the influence of institutional contexts on adoption pathways. The study contributes by positioning sustainable computing as a foundational organizational capability that bridges digital transformation and ESG reporting, offering both theoretical insights and practical implications for enhancing ESG measurement and reporting readiness.
Abaker et al. (Thu,) studied this question.