China's significant contribution to global carbon emissions necessitates effective strategies for energy intensity reduction. While technological innovation is crucial, many Chinese firms lack independent R&D capabilities. IUR collaborative innovation, integrating resources from industry, universities, and research institutes, offers a potential solution. However, the impact of IUR collaboration on energy intensity and the influence of political turnover on this relationship remain under-researched. This study addresses these gaps by examining the impact of IUR collaborative innovation on energy intensity in China and exploring the moderating role of political turnover, defined as changes in top leadership positions. The research aims to provide insights into driving factors of energy intensity reduction and inform policy development aligned with China's carbon emission reduction targets.

Existing literature extensively examines factors influencing energy intensity, including economic growth, energy prices, trade liberalization, and government policies. The role of technological innovation in energy intensity reduction is widely acknowledged, although its direct effect is debated. Collaborative innovation, a more complex model than closed or open innovation, is increasingly recognized for its ability to enhance innovation capacity with limited resources. Studies on IUR collaborative innovation often use patents, publications, and new processes as proxies for innovation output, but these indicators have limitations. While the impact of government factors on technological innovation has been studied, fewer studies address how local government officials directly influence technological innovation, particularly the effects of political turnover. Existing research on political turnover focuses primarily on environmental pollution, energy conservation decisions, and public services, with limited exploration of its impact on IUR collaborative innovation and energy intensity. This study bridges these research gaps to understand how IUR collaboration affects energy intensity and the potential moderating role of political turnover.

This study utilizes a panel dataset of 30 Chinese provinces from 2010 to 2018, excluding Tibet, Hong Kong, Macau, and Taiwan due to data limitations. The dataset covers over 90% of China's population and economic output, ensuring high representativeness. Data sources include the China Energy Statistical Yearbook, China Science and Technology Statistical Yearbook, and China Statistical Yearbook. Missing data are filled using supplementary sources. Energy intensity is the dependent variable, calculated as the ratio of primary energy consumption to gross domestic regional product (GRDP). IUR collaborative innovation is the independent variable, measured using a novel synergy model of a composite system. This model assesses the degree of synergy among university, industry, and research institute subsystems, incorporating input (R&D personnel, internal expenditure, R&D projects) and output (scientific papers, patent applications, sales revenue of new products) indicators. The weights of indicators are determined using an entropy method incorporating time variable. Political turnover, measured as a dummy variable indicating the appointment of a new provincial secretary, serves as the moderating variable. Control variables include R&D expenditure input intensity, population density, foreign direct investment (FDI), and industrial structure. Multiple regression analyses are employed, including OLS, fixed effects (FE), random effects (RE), and system generalized method of moments (SYS-GMM) to account for potential endogeneity. Robustness tests include instrumental variable methods, variable substitution, grouped regressions, counterfactual simulations, and consideration of energy-related policies. Regional heterogeneity is analyzed by dividing the provinces into eastern, central, and western regions based on development levels.

The analysis reveals a significant negative relationship between IUR collaborative innovation and energy intensity. This effect is particularly pronounced in the eastern region. Political turnover significantly moderates this relationship, strengthening the negative effect in central and western regions but not in the east. Robustness tests, including instrumental variable estimation, variable substitution (using patent numbers as a proxy for IUR collaboration), grouped regression, counterfactual simulation (testing the model under different assumptions about the timing of political turnover), and the inclusion of energy-related policy variables (carbon trading pilot and low-carbon pilot policies) consistently support the main findings. Regional heterogeneity suggests that the inhibitory effect of IUR collaborative innovation on energy intensity is significant in the eastern region, but not in the central and western regions. Furthermore, the moderating effect of political turnover is significant in the central and western regions, but not in the eastern region.

The findings highlight the importance of IUR collaborative innovation for reducing energy intensity in China, particularly in the eastern region. The moderating role of political turnover suggests that the Chinese official promotion system incentivizes newly appointed officials to prioritize energy efficiency improvements. The regional heterogeneity indicates that context matters; policies need to be tailored to specific regional conditions. In the eastern region, a more developed market mechanism might diminish the impact of political turnover on IUR collaboration, unlike in central and western regions. These findings contribute significantly to the understanding of the complex interplay between innovation, political dynamics, and energy efficiency in China, adding to the literature by focusing on the synergistic effect of IUR collaboration and the contextual influence of political turnover.

This study demonstrates the significant role of IUR collaborative innovation in reducing China's energy intensity, particularly in the eastern region, and the moderating influence of political turnover, especially in central and western regions. The regional heterogeneity emphasizes the importance of context-specific policies. Future research could disaggregate political turnover into promotion, leveling, and demotion to understand its differentiated effects, or analyze data at the municipal level for a more granular analysis. The study's policy implications highlight the need to foster IUR collaboration, especially in less developed regions, and to consider the impact of political turnover on policy design and implementation.

The study's limitations include the potential for omitted variable bias, despite the inclusion of control variables, and the reliance on available data which may not capture the full complexity of IUR collaboration. The data on political turnover is limited to changes in provincial secretary positions; other leadership changes might also influence outcomes. Future research could explore alternative measures of IUR collaboration and incorporate additional contextual factors to enhance the analysis's comprehensiveness.