Search Results (47)

This present study aims to investigate the influence of board characteristics on the level of climate change disclosures and the extent to which the implementation of the corporate governance code (CGC) moderates these factors. The ordinary least squares statistical method is used to analyze the panel data. In addition, the Tobit regression model is also estimated to check the robustness of the study findings. This study suggests that larger board sizes, more independent directors, and board meeting frequency are positively associated with higher levels of climate change disclosure. However, the study does not find any association between CEO duality, foreign ownership, and climate change disclosure. In addition, it is also observed that CGC can enhance the influence of board characteristics on the likelihood of disclosing climate information. The study offers necessary directions for regulatory authorities, business firms, and practitioners to be more transparent in disclosing climate information and extends guidelines to tackle climate change disclosure issues. Full article

Amid China’s “dual carbon” goals and technological transformation, the traditional energy–economy–environment (3E) framework fails to capture evolving urban sustainability patterns, as digitalization and innovation emerge as endogenous drivers. This study constructs an expanded five-system framework (3E-D-T: energy, economy, environment, digitalization, technology) and examines its coupling coordination. Using panel data from 13 Jiangsu cities (2015–2024), we employ entropy weighting, coupling coordination models, Dagum Gini decomposition, spatial autocorrelation, and panel Tobit regression. Results show that incorporating digitalization and technology alters coordination assessments, revealing structural disparities overlooked by the traditional framework. Significant intra-provincial heterogeneity exists across Jiangsu’s regions, with distinct spatial gradients. External factors—economic development, industrial structure, fiscal support, and environmental regulation—exert differentiated regional impacts. Contributions include: (1) expanding 3E to 3E-D-T by endogenizing digitalization and technology; (2) establishing an integrated measurement-evolution-mechanism analytical system; (3) providing empirical evidence on internal heterogeneity and differentiated governance pathways in eastern China. Full article

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven. Full article

The global shift towards sustainable energy and stringent climate policies has underscored the need for decarbonizing energy systems, electrifying transportation, and transforming supply chains. In this context, China’s new energy vehicle (NEV) industry, as the largest global producer and consumer of automobiles, is pivotal in advancing energy substitution and achieving carbon reduction goals. This study investigates the energy efficiency and supply chain transformation within China’s NEV sector, leveraging panel data from 12 representative provinces over the period 2017–2023. Employing a robust analytical framework that integrates the DEA-BCC model, Malmquist index, and Tobit regression, the study provides a dynamic and regionally differentiated assessment of NEV industry efficiency. The results reveal significant improvements in total factor energy efficiency, predominantly driven by technological progress. R&D intensity, infrastructure development, and environmental regulation are identified as key enablers of efficiency, while excessive government intervention tends to hinder performance. The findings offer valuable empirical insights and policy recommendations for optimizing China’s NEV industry in the context of energy system transformation and sustainable industrial development. Full article

The shipping service industry plays a pivotal role in enhancing port competitiveness and fostering urban economic growth, yet limited studies systematically integrate its spatial temporal dynamics with the processes driving port–city synergy. This study constructs a three-dimensional analytical framework encompassing port operations, urban economic development, and shipping service industry agglomeration. Using data from 13 port cities in Jiangsu Province (2015–2023), we apply the entropy weight method, coupling coordination degree model, relative development model, and panel Tobit regression to evaluate interaction intensity, coordination patterns, and influencing factors. Results reveal a clear spatial gradient in coupling coordination, higher in southern Jiangsu and lower in the north, driven by disparities in economic foundations, port capacities, and service industry structures. In most cities, port operations and urban economies lag behind shipping service industry agglomeration, reflecting the predominance of low- and mid-end services. Port construction level, cargo and container throughput, economic development, openness, fixed asset investment, and population density significantly promote coordination, whereas R&D capacity shows no significant effect. The findings advance understanding of port–city service interlinkages and provide targeted policy recommendations for differentiated regional development, infrastructure enhancement, and upgrading toward high-end shipping services, with implications for maritime regions worldwide. Full article

The impact of urbanization on the agricultural economy has long attracted scholarly attention. Taking China as a case, this study investigates the relationship between urbanization and agricultural development under the dual progress of urbanization and the rural revitalization strategy. Based on panel data from 31 mainland provinces, this paper measures agricultural economic efficiency using the global slack-based measure (SBM) model and employs quantile regression to systematically analyze the influence of various urbanization factors across different levels of agricultural efficiency. A Tobit regression model is further adopted for robustness checks. The results show that representative urbanization factors, such as the proportion of urban population and the prevalence of higher education, exert significant negative impacts on agricultural efficiency, particularly in regions with higher efficiency levels. Freight volume has a significantly negative effect in regions with medium and low efficiency, while freight turnover negatively impacts medium- to high-efficiency areas. In contrast, improvements in healthcare services and digital infrastructure are found to consistently enhance agricultural efficiency. Although the corporatization of agriculture is often regarded as a key outcome of urbanization, its efficiency-improving effect is not statistically significant in most models and is mainly concentrated in high-efficiency regions. Overall, the improvement in China’s agricultural economic efficiency relies more on direct support from the rural revitalization strategy, while rapid urbanization has failed to bring substantial benefits and has even led to structural negative effects. These adverse outcomes may stem from the rapid occupation of suburban farmland, increased logistics costs due to the relocation of agricultural activities, and the ineffective absorption of surplus rural labor. This study highlights the need for future urbanization policies in China to pay greater attention to the coordinated development of the agricultural economy. The methods and findings of this research also provide reference value for other developing regions facing similar urbanization-agriculture dynamics. Full article

Exploring the law and evolution mechanism of coupling and coordination between agricultural carbon emission efficiency (ACE) and agricultural economic growth (AEG) can provide a reference basis for agricultural low-carbon transformation. This study takes 11 cities in Jiangxi Province as the research object; measures the level of ACE based on the panel data from 2008 to 2022; and analyzes the development and influencing factors of the coupling and coordination between ACE and AEG by using the coupling coordination degree model, the Dagum Gini coefficient decomposition method, and the Tobit regression model. The results reveal the following: (1) The overall ACE in Jiangxi Province displays a significant upward trend, with the average efficiency value increasing from 0.172 to 0.624, reflecting an average annual growth rate of 72.43%. Nonetheless, there remains clear regional heterogeneity, characterized by lower efficiencies in Central and Southern Jiangxi compared to the higher efficiencies found in Northern and Western Jiangxi. (2) Despite gradual improvements in regional coordination, the Central and Southern Jiangxi regions still lag Northern and Western Jiangxi in terms of the linked coordination between ACE and AEG, symptoms of which had been previously misaligned. (3) The results of Dagum’s Gini coefficient decomposition show that inter-regional disparities are the main source of overall disparities, with a contribution of 37.43%, which is higher than the synergistic effect of intra-regional disparities and hyper-variable densities, corroborating the core contradiction of uneven development across regions. (4) The Tobit model reveals that government investment, industrial structure optimization, urbanization, and educational attainment exert a significant positive influence on promoting coupling coordination. To establish a scientific basis for achieving a low-carbon agricultural transformation and equitable AEG in Jiangxi Province, this research recommends bolstering regional cooperation, fostering innovations in agricultural science and technology, optimizing the industrial structure, and enhancing farmers’ awareness of low-carbon practices. This study expands the theoretical system of agricultural low-carbon transition in terms of research methods and scales to provide a scientific basis for agricultural provinces to realize agricultural low-carbon transition and balanced economic development. Full article

With the growth of the new energy sector, China’s energy industry is experiencing significant transformations. This research aims to evaluate the technological progress and changes in scale efficiency of listed companies in China’s energy industry, with a particular focus on the comparison between new and traditional energy sectors. This research investigates various efficiency values, types of returns to scale, the role of patents in fostering technological progress, and the influence of financial leverage on scale efficiency changes, a comprehensive evaluation of the industry that offers a critical foundation for formulating targeted strategies. This research uses data from A-share listed energy companies spanning from 2017 to 2023, constructs input–output indicators centered on research and development (R&D) and profitability, and applies the DEA model to examine the operating efficiency of energy listed companies. A Malmquist indices is developed to analyze the dynamic evolution of technological change and scale efficiency change. In contrast to the conventional approach of using DEA efficiency scores as the dependent variable in Tobit regressions, this research uses the Malmquist indices, which more effectively captures the dynamic evolution of technological progress and scale efficiency. The study empirically assesses the impact of patent accumulation on technological progress through a Tobit panel model with random effects and the effect of financial leverage on scale efficiency changes using a Tobit four-stage incremental regression. Finally, the study draws the following conclusions: 1. In terms of industry static correlation, listed new energy companies exhibit polarization in returns to scale types; in contrast, traditional energy listed companies have a more stable and mature returns to scale structure. 2. In terms of dynamic correlation, technological progress in the new energy sector is substantial, while the traditional energy sector faces bottlenecks; efficiency changes in both industries are dependent on scale efficiency changes, rather than pure efficiency changes. 3. Regarding influencing factors for new energy listed companies, patent accumulation has a limited impact on technological progress, while financial leverage and scale efficiency change exhibit a non-linear relationship, with an inflection point effect observed in companies with high financial leverage. Finally, this study offers targeted policy recommendations for new energy and traditional energy listed companies based on the findings. Full article

The digital economy offers new solutions for reconciling the growth of the non-timber forest-based economy (NTFBE) with ecological and environmental protection. Utilizing panel data from China’s provinces between 2011 and 2020, this study constructed a comprehensive indicator system for the purpose of examining the coordinated development of the NTFBE and the ecological environment. The employment of a panel of econometric methods, including Tobit models, mediated effects models, spatial Durbin models and threshold regression models, has enabled us to ascertain that the digital economy can effectively drive this coordinated development. The digital economy has a positive spillover effect in neighboring regions, although there is no discernible impact in central and northeastern China. Improvements in human capital and digital infrastructure reinforce this effect. Furthermore, the empowerment of green technology and industrial transformation, as well as the adoption of differentiated development strategies across distinct forest economic models, would be of paramount importance. These findings indicate a necessity for the standardization of the NTFBE. In conclusion, these implications offer novel solutions from China’s forested regions that reconcile socioeconomic growth and environmental protection, thereby fostering the sustainable development of forests. Full article

This study investigated the influence of cultural industry agglomeration on the energy carbon emission performance (CEP). Based on panel data from 276 cities in China, we used the Super-SBM model to measure the CEP. We then used the Tobit regression model to calculate the influence coefficient of cultural industry agglomeration and eight control variables on the CEP and analyzed the complex effects of cultural industry agglomeration on the CEP. The results showed that there is the phenomenon of “diseconomies of agglomeration” in cultural industry agglomeration, which cannot improve the CEP. For each unit of cultural industry agglomeration increase, the CEP decreases by 0.055; however, this phenomenon is not linear. Further research showed that the effects of cultural industry agglomeration showed a trend from good to inferior in the order of east, central, and west and did not improve with time. Finally, we used the panel quantile regression model and found that as the CEP levels rise, the negative impact of cultural industry agglomeration improves. Our research results show that strengthening the technical level to promote the upgrading of the cultural industry is the best way to achieve sustainable development. Governments at all levels should pay attention to the emission reduction potential of cultural industry agglomeration under high CEP levels and strengthen the benign agglomeration of the cultural industry. Full article

Over the past two decades, the industrial sector of China has experienced rapid development, which has correspondingly led to a significant increase in water resource consumption. To better understand the dynamics of industrial water use, and formulate appropriate water resource conservation and management policies, it is necessary to evaluate the evolution of industrial water use efficiency and its influencing factors in China. Given the high sensitivity and accuracy of the stochastic frontier analysis (SFA) model for efficiency assessment, the Tobit model is more suitable for regression analyses of truncated data. This study employed the SFA–Tobit panel model to evaluate the industrial water use efficiency of provinces in China from 2003 to 2021. The results indicate that national industrial water use efficiency improved from 0.41 to 0.65 during the study period. All provinces showed significant improvements, with developed provinces exhibiting higher industrial water use efficiency than undeveloped provinces. Regionally, the eastern areas demonstrated superior industrial water use efficiency compared to the western regions, with the central regions having the lowest overall water use efficiency. Moreover, the efficiency gap between regions has been narrowing. The national industrial water-saving potential is estimated at 31.306 billion cubic meters, with Jiangsu province having the highest saving potential at 3.709 billion cubic meters. In comparison, Beijing has the lowest at just 32,000 cubic meters. The Tobit regression results reveal that economic development and technological progress positively contribute to increased industrial water use efficiency. In contrast, water use intensity, openness, and urbanization levels negatively impacted the improvement of industrial water use efficiency. Therefore, it is necessary to increase investment in technological innovation, strictly control industrial water intensity, appropriately balance import and export trade with urbanization levels, and promote sustainable economic development. This study can provide effective support for the subsequent green transformation of China’s industry. Full article

Due to the continuous growth of global energy demand and the urgent pursuit of sustainable development goals, renewable energy development has become a vital strategy to deal with energy challenges and environmental issues. Renewable energy generation efficiency (REGE) around the world has begun to be examined, and ambitious goals with a sense of mission within a predetermined timeline have been set. The goal of this paper is to use the dynamic slacks-based measure (DSBM) data envelopment analysis (DEA) method to obtain the REGE for 44 Asian economies from 2010 to 2021. This paper also uses Tobit regression analysis to explore the factors that may affect the REGE. The empirical results indicate that the REGE in 17 economies reached the efficiency target during this period. When classified by income level, differences in average REGE are observed among high-income, upper-middle-income, lower-middle-income, and low-income economies. Additionally, differences in average REGE exist between tropical and temperate economies when classified by geographic latitude. Furthermore, through the Tobit regression model, we determine that information digitalization, financial openness, technological innovation ability, and renewable energy device capacity share all have significant positive effects on REGE, but life quality and democracy degree have significant negative impacts on REGE. Moreover, it has been found that the REGE scores of Asian economies exhibit a status similar to the middle-income trap. The outcome of the research provides Asian governments and those middle-income economies with ways to enhance REGE. Due to data limitations, this study cannot estimate the convergent solution based on the data of the research sample, and a new advanced Panel Tobit model is required. Full article

Tourism eco-efficiency has played a significantly essential role in the sustainable development of tourism destinations and tourism industries, providing ideal inputs and outputs amidst the deepening environmental crisis. This study evaluates the development level of tourism eco-efficiency using the Super-SBM model with undesirable outputs, employing the Malmquist-Luenberger (ML) index to analyse the internal optimisation forces of tourism eco-efficiency. Furthermore, human capital is assessed through both horizontal and vertical education levels, followed by a panel Tobit econometric analysis to explore the external impact mechanisms on tourism eco-efficiency. The results show that (1) Technological advancement is the core intrinsic driver for optimising tourism eco-efficiency. (2) In the analysis of influencing mechanisms, Human capital significantly contributes to enhancing tourism eco-efficiency, a conclusion upheld even after conducting robustness tests. (3) Analysis of mediating mechanisms indicates that tourism industry agglomeration is a critical pathway through which human capital enhances tourism eco-efficiency. This correlation has been proven reliable by regional regression analysis. (4) Results of the threshold model test suggest a law of “increasing marginal effect” concerning the positive impact of human capital on tourism eco-efficiency within the regulation of tourism industry agglomeration. Consequently, regions should actively promote the roles of human capital and tourism industry agglomeration in advancing tourism eco-efficiency, improving resource utilization efficiency, and tourism industry specialization to foster sustainable tourism development. Full article

Globally, karst regions face the dual challenges of urbanization and ecological protection, with the coupling coordination of multi-dimensional urbanization (MDU) and ecological security (ECS) being a necessary condition for achieving sustainable development. This study, based on statistical data on MDU and ECS in the Yunnan–Guizhou Region (the YGR) in China, employs the entropy weight TOPSIS model, degree of coupling coordination (CCD) model, and panel Tobit regression model to explore the coupling relationship between MDU and ECS. The main conclusions are as follows. (1) MDU in the YGR increased from 0.299 to 0.305, indicating low-level and sluggish development. Spatially, it is characterized by a “dual-core” structure centered on Kunming and Guiyang. (2) ECS decreased from 0.456 to 0.423, with a spatial pattern of “high in the east, low in the west”. The impact of human activities on ECS increased from 0.579 to 0.631 due to the increase in social and economic activities. (3) CCD increased to 0.579, achieving moderate coordination. The spatial feature evolved into a tri-cluster pattern of “high–low–high” across the “eastern–central–northwestern” regions. (4) Regression results indicate that annual average precipitation has a “both promoting and limiting” dual effect on CCD. The coefficient for the proportion of afforested land area is 0.205, with a significance level of 5%, suggesting that increasing forest cover is a key measure for improving CCD. The study reveals the factors influencing the evolution of MDU and ECS from a negative to a positive correlation, providing a basis for decisions related to sustainable development for urban and ecological management in karst landscapes globally. Full article

For high-quality growth to occur, new-type urbanization and environmental preservation must coexist and advance at the same time. The focus has shifted to maintain a balance between ecological quality and urbanization growth. This study focuses on the Yangtze River Delta (YRD) in China, utilizing panel data from 41 cities in the YRD spanning from 2009 to 2021 to construct evaluation index systems for new (type of) urbanization and ecological environment. To analyze spatial-temporal evolutionary aspects and determine the causes of the degree of coupling coordination between new-type urbanization and the ecological environment, methodologies such as the entropy weight method, coupled coordination degree model, and Tobit regression approach were used. The results show that (1) economic urbanization has experienced the most growth in the level of new-type urbanization in the YRD, which has been steadily increasing. Moreover, the ecological environment evaluation score increased from 0.581 in 2009 to 0.701 in 2021, revealing a cyclical pattern of increase and decrease in its evolutionary trajectory. (2) Within the scope of the study, the overall coupling coordination degree between new-type urbanization and ecological environment has increased, with the average value rising from 0.512 in 2009 to 0.540 in 2021. In comparison to Lishui, Huaibei, Huainan, Ningbo, Chuzhou, and Bozhou saw a greater increase in coupling and coordination degree, with pronounced variations and clustering patterns visible in their spatial distribution. (3) According to the Tobit regression analysis, the level of economic development, technological progress, industrial concentration, global openness, and educational investment had significant positive effects on the degree of coupled coordination between new-type urbanization and the ecological environment in the YRD, whereas the level of information technology did not reach the significance threshold. The findings of the study are crucial for establishing a regional framework for green and sustainable development, as well as for facilitating the coordinated growth of new-type urbanization and ecological environment. These findings hold great potential for driving positive change in both urban development and environmental conservation efforts. Full article