Cloud and Distributed Computing for Project Analytics: A Meta-Analysis of Decision-Making Performance

Abstract

This study investigated the impact of cloud and distributed computing on decision-making performance in project analytics through a comprehensive quantitative meta-analysis of 68 empirical studies comprising a cumulative sample of approximately 24,350 observations. The research was grounded in data-driven decision-making theory and information processing perspectives, aiming to quantify the relationship between advanced computational infrastructures and key decision performance indicators, including accuracy, speed, and consistency. The findings revealed a strong and statistically significant positive relationship, with a pooled effect size of r = 0.61 (p < 0.001), indicating that cloud and distributed computing substantially enhanced decision-making effectiveness in project environments. Specifically, decision accuracy improved by 18.7%, while decision response time was reduced by 21.4%, demonstrating notable gains in operational efficiency. Distributed computing frameworks further contributed to analytical performance by reducing processing time by 24.3%, supporting faster and more responsive decision cycles. Subgroup analyses indicated that the strength of this relationship varied across contexts, with higher effect sizes observed in information technology (r = 0.68) and construction (r = 0.64) sectors, as well as in large organizations (r = 0.66) compared to smaller firms. Geographical differences showed slightly stronger effects in developed regions (r = 0.63) relative to emerging economies (r = 0.58), reflecting differences in digital maturity. Moderating factors such as data quality (r = 0.62), system integration (r = 0.64), and user experience (r = 0.60) were found to significantly enhance decision-making outcomes. Heterogeneity analysis indicated moderate variability (I² = 38.6%), while publication bias tests confirmed the robustness of the results. Overall, the study demonstrated that cloud and distributed computing are critical enablers of efficient, accurate, and consistent decision-making in modern project analytics, providing strong empirical support for their adoption across diverse organizational contexts.