Effective data governance in the public service sector is a foundational pillar for achieving digital transformation and improving service delivery. This study examines the data governance performance across 31 provinces and municipalities in China, adopting the TOE framework integrated with the “Ternary-World” theory to construct a three-dimensional model encompassing the physical world, social organizations, and information technology. From the dimensions of contextual environment, organizational dynamics, and technological infrastructure, the study systematically analyzes the factors influencing the effectiveness of public service data governance. Combining qualitative and quantitative methods—including policy analysis, statistical yearbooks, and publicly available data—the research applies qualitative comparative analysis and necessary condition analysis to identify both necessary and sufficient conditions that enhance governance performance, and to quantify the influence mechanisms of key factors. The findings reveal significant regional disparities in governance capacity: provinces such as Beijing, Shanghai, Guangdong, and Zhejiang lead the way, followed by coastal regions; central provinces maintain moderate levels, while the northeastern and northwestern regions lag behind. Key determinants for improving governance efficiency include the degree of data openness, financial investment intensity, and technological application capacity. Based on these insights, the study proposes four differentiated pathways for improving public service data governance, taking into account regional variations in geography, resources, culture, and economic development. These pathways provide practical, adaptable strategies for digital advancement and offer valuable comparative cases for localized reform efforts.