Search Results (1,236)

This study examines how hotel characteristics and urban spatial context influence tourist satisfaction in Seoul, South Korea, by integrating sentiment analysis of online reviews with regression modeling. Drawing on 4500 TripAdvisor reviews from 75 hotels, sentiment scores were extracted using aspect-based sentiment analysis, and two regression approaches, ordinary least squares (OLS) and spatial autoregressive combined models, were applied to evaluate how hotel specific features, such as the age and scale of the hotels and room rates, and their geographic characteristics, such as the proximity to airports and cultural landmarks, affect both emotional sentiment and formal hotel ratings. The OLS model for sentiment scores identified the scale and rating of the hotels as well as the proximity to the airports as key predictors. Additionally, the spatial autoregressive combined model was also statistically significant, suggesting spatial spillover effects. A separate model for the traditional rating revealed weaker associations, with only the hotel’s opening year reaching significance. These findings highlight a divergence between emotional responses and structured ratings, with sentiment scores more sensitive to spatial context. This study offers practical implications for hotel managers and urban planners, emphasizing the value of incorporating spatial factors into hospitality research to better understand the tourist experience. Full article

Reducing emissions through the invisible hand of the market has become an important way to promote sustainable environmental development. The shadow price of carbon dioxide ($C{O}_2$) is the core element of the carbon market, and its accuracy depends on the micro level of the measurement data. In view of this, this paper innovatively uses enterprise level input-output data and combines the stochastic frontier method to obtain $C{O}_2$ shadow prices in China’s industrial sector. On this basis, the impacts of research and development (R&D) intensity, opening up level, traffic development level, population density, industrial structure, urbanization level, human resources level, degree of education, and environmental governance intensity on shadow price are discussed. In further analysis, this study introduces a Spatial Durbin Model (SDM) to evaluate the spatial spillover effects of $C{O}_2$ shadow price itself and its influencing factors. The research results indicate that market-oriented emission abatement measures across industries and regions can reduce total costs, and it is necessary to consider incorporating carbon tax into low-carbon policies to compensate for the shortcomings of the carbon Emission Trading Scheme (ETS). In addition, neighboring regions should coordinate emission abatement tasks in a unified manner to realize a sustainable reduction in $C{O}_2$ emissions. Full article

Land resources are the basis of human production and life, and they face many challenges in the process of urbanization, such as the prominent contradiction between land supply and demand and the inefficient use of land, which in turn restricts the socio-economic development and the promotion of urbanization. This paper takes China’s ten largest urban agglomerations as its research object and constructs a land resource drag effect model based on the C-D production function. The geographical weighted regression method is used to calculate the coefficient of the land drag effect. Combining kernel density analysis and spatial autocorrelation analysis, the paper reveals the temporal and spatial evolution patterns of the drag effect and discusses the impact of land resources on new urbanization and its temporal and spatial differentiation characteristics. The study shows that during the period of 2006–2022, China’s new-type urbanization as a whole rises, but the development of each urban agglomeration has significant differences, showing a spatial pattern of “east high, west low”; the drag effect of land resources shows a decreasing trend, but regional differences are obvious, showing a distribution of “east strong, west weak”; the kernel density curve of drag effect of land shows a “right-skewed-left-skewed” change, with the overall level weakening and the degree of concentration increasing; the drag effect of land resources shows significant positive global autocorrelation, and there are spatial proximity effect and spillover effect in space. The findings provide a theoretical basis for land resource utilization and spatial development in China’s new-type urbanization process. Therefore, it is necessary to implement differentiated land resource allocation and urban planning policies according to different types of urban spatial agglomeration and to give full play to the cooperative linkage effect of urban agglomerations in reducing the drag effect of land resources. Full article

The establishment of a new green space system based on the green belt has become a new trend in the world. Shanghai’s Outer Ring Ecological Park Belt (formerly the Outer Green Belt) faces challenges of spatial imbalance in recreational service distribution and mismatched supply and demand in functional allocation during its transition from an ecological barrier to a recreational service provider. An approach based on spatial spillover effects serves as a critical solution to address these issues. We integrate RPS and ROS models to build an evaluation framework, map recreational service supply for 2013, 2018, and 2023, delimit core areas via MSPA, and quantify spatial spillovers with models SLM and SEM. The results show that high-value areas of recreational service levels along the ecological park belt have driven the development of neighboring areas through spatial spillovers, with this promoting effect radiating outward from the core zones. As the distance from the core areas increases, the effect weakens, with 400 m as the maximum effect boundary, 1 km as the critical spillover boundary, and unstable effects with decreased significance beyond 2 km. We further conduct localized spatial spillover analysis using representative parks as case studies. The research provides theoretical support and implementation suggestions for the planning and construction of an ecological park belt. Full article

In confronting escalating economic uncertainty, achieving a win–win situation for low-carbon transition and improved employment structure will contribute to economic recovery and sustainable growth but also contribute to building a community with a shared future for mankind. A critical issue for China’s economy and societal welfare, as well as a core component of sustainable development, concerns whether low-carbon economic transition influences employment skill structure. This study utilizes data from 30 provinces (municipalities and autonomous regions) in China from 2006 to 2021. Employing the entropy method, a low-carbon economic development level indicator system was constructed from four aspects: low-carbon output, low-carbon consumption, low-carbon resources, and low-carbon environment to measure the low-carbon economy and explore its direct and indirect effects on employment skill structure and spatial effects. The research findings indicate that low-carbon economies not only directly and significantly promote employment skill structure optimization but also indirectly generate promotional effects through pathways such as industrial structure adjustment, green innovation’s innovative effects, and factor substitution effects of increased pollution control investment. Among these, the indirect impact of industrial structure adjustment contributes most substantially. Low-carbon economies’ influence on employment skill structures exhibits spatial spillover effects, with neighboring regions’ low-carbon economies exerting positive spillover effects on local skill structures. Additionally, significant negative interdependence exists among regional employment skill structures. Based on the aforementioned research conclusions, the following recommendations are proposed: accelerate low-carbon economy development and employment skill structure enhancement in central and western regions to diminish regional disparities; encourage green innovation and promote traditional industry upgrading and transformation; formulate regional coordinated development plans, thereby strengthening the low-carbon economy’s optimizing role upon employment skills structure; and increase educational investment and strengthen labor skill training. Full article

To systematically reveal the influence mechanisms and spatial effects of industrial intellectual property (IP) reform strategies and manufacturing craftsmanship spirit on regional energy intensity, this study aims to provide theoretical support and practical pathways for emerging market economies pursuing dual goals of energy efficiency governance and manufacturing transformation. Based on a “technology–culture synergistic innovation ecology” theoretical framework, the study deepens the understanding of energy intensity governance and introduces two spatial weight matrices—the economic distance matrix and the nested economic–geographic matrix—to uncover the spatial heterogeneity of policy and cultural effects. Using panel data from 30 Chinese provinces from 2010 to 2022 (excluding Tibet, Hong Kong, Macao, and Taiwan), we construct an index of manufacturing craftsmanship spirit (CSM) and its four dimensions—excellence in detail, persistent dedication, breakthrough orientation, and innovation inheritance—via the entropy method. Empirical analysis is conducted through Spatial Difference-in-Differences (SDID) and Double Machine Learning (DML) models. The results show that: (1) Industrial IP reform strategies significantly reduce local energy intensity through improved property rights definition and technology transaction mechanisms, but may increase energy intensity in economically proximate regions due to intensified technological competition. (2) All four dimensions of craftsmanship spirit indirectly mitigate regional energy intensity via distinct pathways, with particularly strong mediating effects from persistent dedication and innovation inheritance. In contrast, breakthrough orientation shows no significant impact, possibly due to limitations from the current stage of the technology lifecycle. (3) Spatial spillover effects are heterogeneous: under the nested economic–geographic matrix, IP reform strategies reduce neighboring regions’ energy intensity through synergistic effects, while under the economic distance matrix, competitive spillovers lead to an increase in adjacent energy intensity. Based on these findings, we propose the following: deepening IP reform strategies to build a technology–culture synergistic ecosystem; enhancing regional policy coordination to avoid technology lock-in; systematically cultivating the core of craftsmanship spirit; and establishing a dynamic incentive mechanism for breakthrough orientation. These measures can jointly drive systemic improvements in regional energy efficiency. Full article

The integration of the digital and real economies (DRI) is an inevitable trend in future economic growth. This study measures DRI levels across 30 Chinese provinces from 2012 to 2022 using a coupling coordination model with panel data and empirically examines DRI’s impact on industrial structure upgrading (ISU) through fixed-effects models, mediation effect models, and panel threshold models. The findings reveal that (1) DRI promotes industrial structure upgrading, a conclusion that remains valid under robustness tests and endogeneity tests; (2) DRI can facilitate ISU by enhancing consumption levels, correcting factor distortions, and accelerating the marketization process; (3) there exists a threshold effect, with a positive effect of DRI on ISU based on the level of digital economy and the scale of the real economy as threshold variables; (4) the impact of DRI on ISU differs across different regions due to differences in policy support and resource allocation; (5) ISU has a significant spatial spillover effect, as shown by spatial econometric analysis. These conclusions offer a new perspective, practical policy implications for China’s high-quality economic development, and strategic insights to enhance industrial competitiveness in the global value chain. Full article

As a pivotal engine driving China’s economic development, new quality productive forces are profoundly shaping the pathways for realizing common prosperity and Chinese modernization. The study constructs multidimensional evaluation frameworks for new quality productive forces and common prosperity, respectively, measures the development levels of new quality productive forces and common prosperity across 277 prefectural-level and above cities in China from 2013 to 2022, and analyzes the spatial and temporal evolution characteristics of China’s new quality productive forces over the past decade using ArcGIS 10.8.1. Meanwhile, the two-way fixed model and the spatial Durbin model are used to analyze the impact of new quality productive forces on common prosperity and its spatial spillover effect. The study finds the following: (1) China’s new quality productive forces development levels generally show a spatial pattern of “high in the east and low in the west”, in which cities located in the Yangtze River Economic Belt and the eastern coastal strip have a higher level of new quality productive forces than other cities, with significant inter-regional differences. (2) New quality productive forces exhibit a robust and significant promoting effect on common prosperity. Mechanism analysis reveals that this effect operates through three channels: enhancing economic agglomeration, advancing industrial structure upgrading, and improving labor misallocation. (3) Regional heterogeneity shows that the promotion effect of new quality productive forces on common prosperity is particularly prominent in Northeast China and Eastern China. Structural heterogeneity reveals that labor materials and objects of labor exhibit more pronounced effects in enhancing common prosperity compared with laborers. (4) Spatial econometric analysis confirms that the new quality productive forces have a significant spatial spillover effect on common prosperity. The findings provide theoretical support for advancing common prosperity while contributing to China’s approach to addressing developmental imbalances among developing countries within the global community with a shared future. Full article

Achieving carbon reduction is essential in advancing China’s dual carbon goals and promoting a green transformation in the transportation sector. Changes in energy structure and intensity constitute key drivers for sustainable and low-carbon development in this field. To explore the spatial spillover effects of the energy structure and intensity on the green transition of transportation, this study constructs a panel dataset of 30 Chinese provinces from 2007 to 2020. It employs a super-efficiency SBM model, non-parametric kernel density estimation, and a spatial Markov chain to verify and quantify the spatial spillover effects of green total factor productivity (GTFP) in the transportation sector. A dynamic spatial Durbin model is then used for empirical estimation. The main findings are as follows: (1) GTFP in China’s transportation sector exhibits a distinct spatial pattern of “high in the east, low in the west”, with an evident path dependence and structural divergence in its evolution; (2) GTFP displays spatial clustering characteristics, with “high–high” and “low–low” agglomeration patterns, and the spatial Markov chain confirms that the GTFP levels of neighboring regions significantly influence local transitions; (3) the optimization of the energy structure significantly promotes both local and neighboring GTFP in the short term, although the effect weakens over the long term; (4) a reduction in energy intensity also exerts a significant positive effect on GTFP, but with clear regional heterogeneity: the effects are more pronounced in the eastern and central regions, whereas the western and northeastern regions face risks of negative spillovers. Drawing on the empirical findings, several policy recommendations are proposed, including implementing regionally differentiated strategies for energy structure adjustment, enhancing transportation’s energy efficiency, strengthening cross-regional policy coordination, and establishing green development incentive mechanisms, with the aim of supporting the green and low-carbon transformation of the transportation sector both theoretically and practically. Full article

Urban carbon reduction is instrumental in enabling cities to realize their developmental sustainability objectives. However, regional disparities in economic development pose significant challenges to low-carbon transitions. This study utilizes panel data from 282 cities in China spanning 2006–2021, considering the energy saving and emission reduction (ESER) fiscal policy as an external shock. Using a multi-period difference-in-differences approach, we assess how ESER impacts urban carbon emissions. Our findings indicate that ESER significantly reduces municipal carbon emissions by an average of 23.3% compared to non-pilot cities. Mechanism analyses suggest that this effect operates through reduced energy consumption, improved industrial structure, and enhanced green innovation. ESER’s impact exhibits heterogeneity across cities with different levels of economic development, population size, innovation capacity, and industrial composition. Moreover, we find evidence of spatial spillover effects, as ESER benefits extend to neighboring regions. These results confirm the effectiveness of ESER in promoting low-carbon development and offer practical implications for enhancing environmental governance through green fiscal instruments. Full article

To advance global climate governance, this study investigates the carbon emission efficiency (CEE) of 110 Chinese resource-based cities (RBCs) using a super-efficiency SBM-GML model combined with kernel density estimation and spatial analysis (2006–2022). Spatial Durbin model (SDM) and geographically and temporally weighted regression (GTWR) further elucidate the driving mechanisms. The results show that (1) RBCs achieved modest CEE growth (3.8% annual average), driven primarily by regenerative cities (4.8% growth). Regional disparities persisted due to decoupling between technological efficiency and technological progress, causing fluctuating growth rates; (2) CEE exhibited high-value clustering in the northeastern and eastern regions, contrasting with low-value continuity in the central and western areas. Regional convergence emerged through technology diffusion, narrowing spatial disparities; (3) energy intensity and government intervention directly hinder CEE improvement, while rigid industrial structures and expanded production cause negative spatial spillovers, increasing regional carbon lock-in risks. Conversely, trade openness and innovation level promote cross-regional emission reductions; (4) the influencing factors exhibit strong spatiotemporal heterogeneity, with varying magnitudes and directions across regions and development stages. The findings provide a spatial governance framework to facilitate improvements in CEE in RBCs, emphasizing industrial structure optimization, inter-regional technological alliances, and policy coordination to accelerate low-carbon transitions. Full article

With the advancement of global climate governance, public attention—an emerging form of social capital—has played an increasingly important role in the carbon emission effects of green technological innovation. Based on panel data from 267 prefecture-level cities in China from 2012 to 2022, this study employed a two-way fixed-effects model to identify the nonlinear relationship between green innovation and carbon emissions, incorporated interaction terms to examine the moderating effect of public attention, and applied a spatial Durbin model to analyze the spatial spillover effects of green innovation. The results reveal an inverted U-shaped relationship between green innovation and carbon emissions, with the inflection point corresponding to 8.58 authorized green patents per 10,000 people—a threshold that most cities have yet to reach. Public attention significantly altered the shape of the carbon effect curve by making it steeper; in cities with a higher share of secondary industry, it delayed the inflection point, whereas in cities dominated by the tertiary industry, the turning point appeared earlier. In addition, green innovation had significant spatial spillover effects, and its impact on carbon emissions in neighboring cities displayed a U-shaped pattern. This paper proposes an analytical framework of “socially empowered innovation” to reveal the nonlinear moderating mechanism through which public attention influences the carbon effects of green innovation. The findings offer important policy implications: efforts should focus on long-term innovation, promote regional coordination, guide rational public participation, and avoid short-sighted and unsustainable mitigation practices. Full article

This study develops an integrated analytical framework to examine the interplay of urbanization, energy consumption, and CO₂ emissions at the city level in China. Utilizing the Entropy-TOPSIS method for multidimensional urbanization measurement, the GM_Combo model for spatial spillover analysis, and Random Forest for identifying emission drivers, we analyze data from 282 Chinese cities from 2006 to 2020. Results reveal significant hierarchical differences in urbanization, with K-means clustering identifying high, medium, and low urbanization groups reflecting diverse regional development pathways. Energy consumption increasingly drives emissions, while urbanization’s influence declines, indicating partial decoupling. Strong spatial spillovers highlight the need for regional coordination. Ecological assets provide moderate mitigation effects. These findings contribute to the literature by introducing a multidimensional urbanization index, uncovering nonlinear energy–emissions dynamics, and quantifying intercity spillovers, offering empirical support for tailored low-carbon policies and sustainable urban governance. Full article

Global water scarcity has emerged as a critical barrier to sustainable socio-economic development, stimulating water rights trading to serve as a policy instrument designed to enhance water use efficiency. This study systematically evaluates the impact of water rights trading (WRT) on agricultural water use efficiency (AWE) using panel data from 30 provinces (2011–2022) and a difference-in-difference (DID) model, while thoroughly investigating the underlying mechanisms and spatial spillover effects. The following are primary conclusions: (1) WRT significantly improves efficiency, reducing water consumption per unit of agricultural output by 4.5% in pilot regions, with robustness checks confirming reliability; (2) the policy’s effects on agricultural water use efficiency vary across regions; (3) mechanism analysis suggests that efficiency improvements are primarily driven by optimized crop planting patterns, adoption of water-saving irrigation technologies, advancements in agricultural mechanization, and strengthened environmental regulations; and (4) the policy exhibits notable spatial spillover effects. These findings contribute to the evaluation of WRT policy and offer practical insights for market-based water allocation reforms, suggesting further expansion of WRT with an emphasis on regional coordination and cross-regional cooperation mechanisms. Full article

The digital economy is a vital driver of industrial transformation and green development in China. This study aims to investigate how formal and informal environmental regulations affected the growth of the digital economy across Chinese prefecture-level cities between 2010 and 2020. Utilizing panel data from official statistical yearbooks and local bulletins, the research employs entropy weighting and ratio analysis to measure regulatory intensity and effectiveness. Spatial econometric models are applied to assess the direct and spillover effects of environmental regulation on digital economy development. Results indicate a nationwide strengthening of both formal and informal regulations, with formal mechanisms exerting a more pronounced influence on digital growth. Regional disparities are evident, with cities under stricter environmental oversight showing faster digital advancement. Spatial spillover effects exist but diminish with distance, likely due to institutional fragmentation. These findings underscore the need for integrated multi-level regulatory approaches, promoting synergy between formal and informal regulations and embedding environmental goals within land-use planning and digital infrastructure investment. The study offers new insights into the interplay between environmental governance and urban digital transformation, providing lessons relevant to China and other developing countries pursuing sustainable transitions. Full article