Digital Government Development, Regional E-Commerce Ecosystem Competitiveness, and the Sustainable Energy Transition: Causal Inference Based on Spatial DID and Double Machine Learning

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🔬研究者:This paper provides a novel application of double machine learning and spatial DID to study the causal link between digital government, e-commerce ecosystems, and energy transition, offering methodological insights for policy evaluation in sustainable development.

🏢実務担当者:Corporates involved in e-commerce or digital government projects can learn about potential pathways to support decarbonization through market connectivity and inclusive infrastructure.

🏛政策担当者:Policymakers can use the findings to design digital government reforms that leverage regional e-commerce ecosystems to achieve low-carbon energy transition, particularly in emerging economies.

The systemic shift in the energy consumption structure from high-carbon fossil fuels to low-carbon clean energy constitutes a critical pathway toward global climate governance and carbon neutrality. However, this sustainable transition is consistently impeded by deep-seated institutional frictions and structural barriers, such as governance fragmentation and carbon lock-in effects embedded in traditional industrial organization. Whether digital government development can overcome these barriers by nurturing resilient business ecosystems and thereby promote a systemic low-carbon energy transition remains an urgent question within sustainable development research. To address this issue, this study integrates digital government development, regional e-commerce ecosystem competitiveness, and the low-carbon transition of the energy consumption structure into a unified analytical and sustainable governance framework. Using panel data from 30 Chinese provinces from 2012 to 2022, we exploit the institutional reform of provincial big data administrations as a quasi-natural experiment to identify the impacts of digital government. Regional e-commerce ecosystem competitiveness is comprehensively evaluated across four sustainable dimensions: ecological innovation capacity, market connectivity, ecological global integration, and inclusive infrastructure. Methodologically, we employ a spatial difference-in-differences model to capture geographic interdependencies alongside a double machine learning framework to handle high-dimensional confounding and nonlinear disturbances. The empirical findings reveal that both digital government development and regional e-commerce ecosystem competitiveness significantly drive the low-carbon transition of the energy consumption structure. The institutional effect of digital government exhibits strong regional embeddedness with localized impacts, whereas e-commerce ecosystem competitiveness generates positive spatial spillovers that accelerate energy optimization in neighboring regions. Crucially, regional e-commerce ecosystem competitiveness serves as a significant partial mediator, constructing a reliable transmission channel from institutional design to market-based decarbonization. Further pathway analysis indicates that market connectivity and inclusive infrastructure function as the primary transmission channels, effectively mitigating transportation energy intensity and bridging the digital-green divide, while the mediating contribution of ecological innovation capacity is relatively constrained due to cross-organizational coordination thresholds. This study clarifies the interactive mechanism between public digital governance and market ecosystem competitiveness in advancing environmental sustainability, thereby offering fresh theoretical insights and actionable policy implications for emerging market economies striving for economic growth and decarbonization.

• openalex https://doi.org/10.3390/su18147352first seen 2026-07-22 05:23:20