Spatial and Temporal Dynamics of Urban Comprehensive Efficiency in China (2015-2019)

The study investigates sustainable urban development in China by examining the comprehensive efficiency of 38 major cities over 2015–2019. It addresses how governance effectiveness, information and communication technology (ICT) readiness, and resource allocation influence urban sustainability outcomes, set against national strategies such as the Urbanization Plan and the Belt and Road initiative. The purpose is to understand spatial and temporal disparities—particularly coastal versus inland performance—and to identify institutional and structural factors affecting efficiency.

The analysis evaluates the comprehensive efficiency of 38 Chinese cities from 2015 to 2019 using official data sourced from the China City Statistical Yearbook (National Bureau of Statistics of China). The study computes annual efficiency scores and conducts spatial comparisons across cities, visualized through maps showing spatial distribution of efficiency. Rankings and intertemporal changes are assessed to identify benchmark and underperforming cities. The data availability section indicates the dataset is accessible via the National Bureau of Statistics website, with additional datasets available by request from the corresponding author. While the detailed model specification is not included in the provided excerpt, the tabulated results and cited foundations suggest a data envelopment analysis (DEA)-based approach to measure comprehensive efficiency across decision-making units (cities).

- Spatial heterogeneity is evident: coastal cities consistently outperform inland cities in comprehensive efficiency throughout 2015–2019. - Notable rank dynamics include an unnamed city improving from 33rd (2015) to 16th (2019), while Shenzhen declined from 1st (2015) to 18th (2019). - Changzhou and Jiaxing are persistent benchmark cities, reflecting strong capabilities in optimal resource allocation and utilization. - Policy and structural factors matter: strategic industrial restructuring (e.g., Changzhou’s shift from secondary to tertiary industry beginning in 2015) and leveraging geographic advantages correlate with higher efficiency. - Widespread inefficiencies are identified in governance and ICT: issues in fiscal structures, potential over-employment in government bodies, and underinvestment in science and technology limit smart city progress and sustainability outcomes.

The findings indicate that cities with stronger governance capacity, better ICT infrastructure, and proactive industrial restructuring achieve higher comprehensive efficiency, helping address the core research question about drivers of sustainable urban development performance. Coastal cities’ persistent advantage underscores the role of location, openness, and mature industrial ecosystems. The observed declines in some leading cities (e.g., Shenzhen) suggest that advantages are not guaranteed and can erode without continuous institutional and technological upgrading. National initiatives like the Urbanization Plan and Belt and Road have shaped development trajectories but have not fully resolved regional imbalances. Addressing governance inefficiencies, streamlining bureaucracy, optimizing fiscal structures, and accelerating ICT adoption and integration with traditional industries are central to sustaining and diffusing efficiency gains.

Sustainable urban development in China requires coordinated improvements in governance, ICT, the economy, society, and the environment. While substantial progress has been made, mitigating negative externalities of rapid urbanization remains essential. The study highlights governance, ICT, and sustainability as pivotal levers for addressing multifaceted urban challenges. Policy recommendations include strengthening ICT infrastructure, increasing science and technology investment, restructuring industrial systems toward green sectors, and enforcing rigorous environmental controls to reduce resource consumption and emissions while enhancing public services and living environments.