Promoting the high-quality development of the tourism economy has become an important challenge. Based on panel data on 31 provinces in China during 2009–2019, this study uses spatial econometric and threshold regression models to analyze the spatial spillover effects and threshold characteristics of tourism industry agglomeration on the high-quality development of the tourism economy. The results show that the overall level of high-quality development of China's tourism economy shows an upward trend, with differences between different regions. The agglomeration of tourism industry has a significant positive impact on the high-quality development of the tourism economy and shows strong spatial spillover effects. Further, the level of agglomeration has a double-threshold effect on the high-quality development of the tourism economy. Based on these results, we propose countermeasures to promote the coordinated and linked development of the tourism industry in different regions, providing important insights for further enhancing the high-quality development of the tourism economy in China.

Digital technologies such as big data are reshaping resource allocation, raising interest in whether and how heterogeneous science and technology innovation (STI) policies can help unlock urban carbon lock-in. Using panel data for 286 prefecture-level cities in China from 2009 to 2023, this paper examines the relationship between heterogeneous STI policy intensity—classified as supply-side, demand-side, complementary-factor, and institutional-reform policies—and urban carbon unlocking efficiency. We develop a mechanism-based framework and empirically assess (i) the moderating roles of digital infrastructure, science and technology finance, and government green attention, and (ii) spatial spillover effects using spatial econometric models. The results show that all four policy types show a significant positive association with local carbon unlocking efficiency, with institutional-reform policies exhibiting the strongest association. When the four types are included jointly, only supply-side and demand-side policies retain statistically significant direct associations. Heterogeneity analyses indicate that demand-side, complementary-factor, and institutional-reform policies are more strongly associated with efficiency gains in low-pollution cities, whereas supply-side and demand-side policies have a stronger association in high energy-consuming cities. Mechanism analysis reveals that regional digital infrastructure exerts a selective moderating effect on the relationship between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. It positively reinforces the effectiveness of supply-side, demand-side, and institutional reform-oriented policies, while its interaction with complementary policies is statistically insignificant. Technology finance and government green policies function as a “resource catalyst” and an “institutional guarantee” respectively, significantly enhancing the correlation between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. Finally, carbon unlocking efficiency displays significant spatial dependence: the intensity of supply-side and institutional-reform policies is positively associated with carbon unlocking efficiency in neighboring cities, while complementary-factor policies exhibit a negative spatial association. Overall, the findings provide empirical evidence to inform the design and coordination of heterogeneous STI policy portfolios aimed at improving urban carbon unlocking efficiency.

Digital technologies such as big data are reshaping resource allocation, raising interest in whether and how Heterogeneous science and technology innovation (STI) policies can help unlock urban carbon lock-in. Using panel data for 286 prefecture-level cities in China from 2009 to 2023, this paper examines the effects of heterogeneous STI policy intensity—classified as supply-side, demand-side, complementary-factor, and institutional-reform policies—on urban carbon unlocking efficiency. We develop a mechanism-based framework and empirically assess (i) the moderating roles of digital infrastructure, science and technology finance, and government green attention, and (ii) spatial spillover effects using spatial econometric models. The results show that all four policy types significantly improve local carbon unlocking efficiency, with institutional-reform policies exhibiting the largest marginal effect. When the four types are included jointly, only supply-side and demand-side policies retain statistically significant direct effects. Heterogeneity analyses indicate that demand-side, complementary-factor, and institutional-reform policies are more effective in low-pollution cities, whereas supply-side and demand-side policies have stronger effects in high energy-consuming cities. Mechanism tests further reveal that digital infrastructure amplifies policy effectiveness by facilitating factor mobility, science and technology finance strengthens policy impacts by easing financial constraints, and government green attention enhances policy effectiveness by improving implementation. Finally, carbon unlocking efficiency displays significant spatial dependence: supply-side and institutional-reform policies generate positive spillovers, while complementary-factor policies exhibit negative spillovers. Overall, the findings provide empirical evidence to inform the design and coordination of heterogeneous STI policy portfolios aimed at improving urban carbon unlocking efficiency.