High-quality Development Research Articles

A Study of Tesla's Impact on China's New Energy Vehicle Market

Nowadays, the issue of carbon emission is getting more and more attention, and China also attaches great importance to the development of the new energy industry. China is steadily developing its new energy automobile industry, and at the same time, new energy automobiles have provided a new "track" for the transformation and upgrading as well as the high-quality development of China's automobile industry. In this context, this paper provides an in-depth study of Tesla's market strategy and its impact on China's new energy vehicle market, outlining the complex interplay between market dynamics, government policies, and corporate strategies, and covering a number of important aspects, including government support, market expansion, consumer demand, competition and pricing strategies, product differentiation, infrastructure development, technological advances, and raw material foreign trade relations. Overall, these results and data show that Tesla's impact on China's new energy vehicle market is very important, intensifying the competition in China's new energy vehicle market, prompting similar new energy vehicle companies in China to innovate, improving the industrial level of China's new energy vehicle companies, and helping to improve China's policies in this area.

Enhancing IEP Goal Development for Preschoolers with Autism: A Preliminary Study on ChatGPT Integration.

The impact of well-crafted IEP goals on student outcomes is well-documented, but creating high-quality goals can be a challenging task for many special education teachers. This study aims to investigate potential effectiveness of using ChatGPT, an AI technology, in supporting development of high-quality, individualized IEP goals for preschool children with autism. Thirty special education teachers working with preschool children with autism were randomly assigned to either the ChatGPT or control groups. Both groups received written guidelines on how to write SMART IEP goals, but only the ChatGPT group was given handout on how to use ChatGPT during IEP goal writing process. Quality of IEP goals written by the two groups was compared using a two-sample t-test, and categorization of goals by developmental domains was reported using frequency counts. Results indicate that using ChatGPT significantly improved the quality of IEP goals developed by special education teachers compared to those who did not use the technology. Teachers in the ChatGPT group had a higher proportion of goals targeting communication, social skills, motor/sensory, and self-care skills, while teachers in the control group had a higher proportion of goals targeting preacademic skills and behaviors. The potential of ChatGPT as an effective tool for supporting special education teachers in developing high-quality IEP goals suggests promising implications for improving outcomes for preschool children with autism. Its integration may offer valuable assistance in tailoring individualized goals to meet the diverse needs of students in special education settings.

The Impact of Climate Change on the Development of Circular Economy in China: A Perspective on Green Total Factor Productivity

<p>In the process of China's transition to high-quality development, the circular economy, as a key strategy for achieving green growth, is of significant importance in addressing climate change and promoting sustainable development. This study employs the SBM-GML model to analyze the Green Total Factor Productivity (GTFP) of 30 provinces in China from 2005 to 2019, exploring the influence of climate change on the development of the circular economy. The research finds that although China's GTFP shows an overall upward trend, indicating some achievements in the circular economy, the performance in the eastern region significantly outperforms other regions, with technological progress being the primary driver of growth. The impact of climate change on GTFP varies with temperature changes and exhibits differentiated characteristics in different regions. Based on these findings, this paper puts forward a series of policy recommendations aimed at strengthening the practice of the circular economy, enhancing resource utilization efficiency, reducing greenhouse gas emissions, and addressing the challenges of climate change through promoting green low-carbon development, optimizing industrial structure, and formulating adaptive environmental regulations.</p>

Analyzing the Spatiotemporal Dynamics and Driving Forces of Ecological Environment Quality in the Qinling Mountains, China

The Qinling Mountains serve as a vital ecological barrier for China, needing regular monitoring for sustainable progress. The present study analyzed the Qinling Mountains (sections in Shaanxi province) via the Google Earth Engine (GEE) and Landsat images, constructing a Remote Sensing Ecological Index (RSEI) for quantitatively analyzing the spatiotemporal evolution of the ecological environment quality from 1990 to 2020. Additionally, this study integrated geodetector and multiscale geographically weighted regression (MGWR) to discern the driving factors influencing ecological quality. The results indicated the following: (1) over the 30 years, the RSEI in the study area initially declined (1990–2005) and then began to improve (2005–2020), demonstrating an overall upward trend; (2) RSEI varied with topography: lower values corresponded to lower elevations (<1200 m) and gentle slopes (<10°), whereas higher values were linked to higher elevations (>1600 m) and steeper slopes (>20°); and (3) NDVI, DEM, land use, and the presence of protected areas emerged as the main driving forces of ecological quality. The interaction between ecological conservation policies and socioeconomic factors enhanced the explanatory strength for the differentiation in ecological environment quality. In conclusion, factors like increased vegetation cover and the establishment of protected areas have significantly promoted the improvement of ecological environment quality in the Qinling region, making this study a scientific reference for providing ecological environment protection and promoting high-quality development.

Research on the coordinated development of provincial urbanization and carbon emission efficiency of construction industry in China

BackgroundEnergy conservation and emission reduction policies restrict the economic and social development of all countries in the world, and the impact on China, which has low urbanization, is more serious. In the process of promoting urbanization, the pressure of carbon emission reduction in the construction industry has increased, and the high emissions of the construction industry have made the low-carbon development of cities face severe challenges. China is at a critical stage of urbanization development, and there is become a general consensus on how to improve the carbon emission efficiency of the construction industry. The interaction between urbanization and the carbon emission efficiency of the construction industry is a long-term and complex process. As one of the industries contributing to China’s urbanization process and carbon emissions, it is of great practical significance to explore the coordination relationship between urbanization and the carbon emission efficiency of the construction industry (CEECI) to realize the goal of “double carbon”, promoting urbanization construction and solving the problem of “green development”. Taking 30 provinces in China as the research target area, the double weighted summation method and the undesirable output superefficiency window-EBM-DEA model are used to measure the provincial urbanization level and CEECI, respectively. Then, the coupling coordination degree model of the relative development index is introduced, and the spatial autocorrelation model and the spatial and temporal differentiation characteristics of the coordination level of urbanization and the CEECI are analysed.ResultsFrom 2010 to 2021, China’s urbanization level increased steadily, but the growth rate gradually decreased. There were significant differences in urbanization levels among provinces. The eastern provinces have a higher level of urbanization but lack an impetus in the later period, while the western provinces have a lower level of urbanization but a faster growth rate. The low-carbon development trend of China’s construction industry is good, and the overall development of the CEECI shows an “N” type, and the inflection points appear in 2013 and 2018. The interprovincial urbanization level is significantly different from that of the CEECI, and the development form of the central and western provinces is better than that of the eastern provinces. The coordination level of urbanization and the CEECI in China is transitioning from the running-in stage to the coordination stage, and the coupling coordination degree between systems is on the rise, while the relative development degree is on the decline. The spatial distribution pattern is in a dynamic state of change, and the overall distribution pattern is “high in the east and low in the central and western regions”. The differences among provinces were significantly decreased, with 63.33% of provinces at the high running-in level. The provinces that entered the coordination stage were mainly located in the eastern region, and only Beijing was in the coordination stage by the end of the study. In addition, 90% of the provinces exhibited lagging efficiency, and only Jiangxi, Guangxi and Chongqing, which had low coordination levels maintained synchronous development of the two systems. The coordination level between provincial urbanization and the CEECI showed a positive spatial distribution, the global Moran index showed a “V” shape trend, and the spatial dependence of the coordination level between the two systems gradually weakened. In the local spatial distribution, there are two types of convergence: high and low.ConclusionsThe coordination degree of urbanization and the CEECI analysed in this study is an extension of the research on the relationship between the two. By integrating the two into a unified framework, the method of combining quantitative and qualitative analysis is used to further explore the coordination relationship between the two, which not only enhances the scientificity and accuracy of the research but also extends the breadth and depth of relevant theoretical research. At the same time, according to the coordination type between urbanization and the CEECI, China should propose corresponding targeted coordination and optimization paths from the perspective of urbanization and low-carbon development of the construction industry to achieve high-quality development of China’s economy and society.

Research on the Evaluation of the High-Quality Development of the Modern Service Industry under the Background of Reduction Development: A Case Study of Beijing

With the popularization and practice of the concept of reduction development, how to accurately and comprehensively evaluate the high-quality development effect of the modern service industry has become crucial. This paper combines the concept of reduction development and high-quality development. According to the specific background of reduction development, this paper constructs the evaluation index system of high-quality development of the modern service industry in the context of reduction development from the four dimensions of total scale control, urban function strengthening, economic quality improvement and livable environment optimization and puts forward the evaluation model of high-quality development of the modern service industry based on the entropy weight TOPSIS method. Taking Beijing’s modern service industry as an example, our empirical analysis showed that from 2008 to 2021, its high-quality development level showed a steady upward trend. The total scale has been effectively controlled, and the service industry has performed well in employment absorption. Scientific and technological innovation and cultural functions have developed significantly, but the level of openness needs to be improved. Economic quality maintained stable development, and the livable environment also showed a good development trend.

Growth Models and Influencing Mechanisms of Total Factor Productivity in China’s National High-Tech Zones

Total factor productivity (TFP) serves as a crucial indicator of high-quality development, showcasing a region’s utilization of technological advancements and innovative strategies to enhance production efficiency. With China’s regions experiencing varying levels of development, the paths to high-quality development in NHTZs also exhibit significant disparities. Analyzing data from 88 NHTZs between 2011 and 2018, this research aims to explore differences in TFP growth models and the mechanisms influencing these models. Employing stochastic frontier analysis (SFA) and the Tobit model, the study identifies three TFP growth models: technology-led, multi-efficiency improvement, and scale efficiency compensation. While factors such as capital accumulation, overseas market participation, and patent output moderately hinder TFP growth, innovation platforms, R&D investment, and overseas talent acquisition significantly contribute to TFP enhancement. Distinguishing itself from existing TFP studies, this paper focuses on NHTZs, highlighting their role in regional high-tech industry development. It introduces three TFP growth models and their characteristics while also uncovering influencing factors for each model. This research offers valuable insights into regional disparities in high-quality development and contributes to understanding TFP growth dynamics in NHTZs.

Spatiotemporal Changes in China’s Tourism Industry Development

As a strategic pillar of the Chinese economy, high-quality development of the tourism industry has become a pressing demand in the contemporary era. Following the new developmental concept advocated by the Chinese government, this study has constructed a comprehensive set of indicators for high-quality tourism development. A thorough spatial analysis of the developmental quality of China’s provincial tourism industry from 2000 to 2021, as well as the developmental conditions of various subsystems, was conducted by employing the entropy–value–TOPSIS method, Dagum Gini coefficient, and ESTDA approach. The research has found that (1) the overall quality of China’s tourism industry has significantly improved, (2) the determinants of differences in tourism-development quality in China transitioned from endowment advantages to innovation capabilities. (3) positive spatial-agglomeration effects are evident in the developmental landscape of China’s tourism industry, (4) the quality of regional tourism development is closely related to the economic development of urban agglomerations, (5) China’s tourism industry demonstrates resilience and capacity for restructuring in the post-pandemic era.

Evaluation and promotion path of high-quality development in the Chinese construction industry under the context of carbon neutrality

Evaluation and promotion path of high-quality development in the Chinese construction industry under the context of carbon neutrality

The Impact of Artificial Intelligence Development on Urban Energy Efficiency—Based on the Perspective of Smart City Policy

China’s economy is stepping into a new stage of high-quality development. The shift not only marks the optimization and upgrading of the economic structure, but also reflects the in-depth implementation of the concept of sustainable development. In this context, the development of AI technology is playing an important role in balancing economic growth and ecological protection with its unique advantages. This paper empirically studied the impact of AI development on urban energy efficiency by constructing panel data for 282 prefecture-level cities from 2006 to 2019 and then using the super-efficiency SBM model based on non-expected outputs to evaluate the urban energy efficiency indicators of prefecture-level cities. It was discovered that the development of AI had a key influence on increasing urban energy efficiency and the optimization of the energy structure by speeding up green technology innovation and digital economy development, which in turn improved urban energy efficiency. In terms of heterogeneity analysis, AI development had a greater impact on urban energy efficiency in the eastern region, which has higher levels of human capital, financial independence, and government intervention. This study combined the smart city pilot policy with a multi-period DID model, based on the treatment of endogeneity issues, in order to perform a parallel trend test and investigate further the effects of policy implementation on the advancement of AI in the context of improving urban energy efficiency. Accordingly, to achieve green and sustainable urban development, the relevant government departments should increase funding for AI research and development, pay attention to the introduction and cultivation of professionals, establish a platform for international exchanges and cooperation between AI and energy management, and continue to advocate for the pilot development of smart cities to increase urban energy efficiency.

The Coupling Coordination between Digital Economy and Green High-Quality Development of Industries in China’s the Yangtze River Economic Belt

The Coupling Coordination between Digital Economy and Green High-Quality Development of Industries in China’s the Yangtze River Economic Belt

The Impact of Digital Transformation on the High-Quality Development of Enterprises: An Exploration Based on Meta-Analysis

With the rapid development of the digital economy and digital technologies, the significance of digital transformation for high-quality enterprise development has been growing. Anchored in the framework of the Resource-Based View, this study employs a meta-analytic approach to systematically, quantitatively analyze 40 empirical studies published between 2010 and 2022. The aims are to synthesize and identify the impact mechanisms of digital transformation on high-quality enterprise development, while also further examining the moderating effects of heterogeneity. The findings reveal that digital transformation exerts a significantly positive influence on high-quality enterprise development through three mechanisms: factors related to innovation, factors linked to enterprise performance, and factors associated with capital market performance. Notably, irrespective of the degree of heterogeneity, both the primary effects of digital transformation on high-quality enterprise development and the moderating effects of various impact mechanisms are statistically significant. The results underscore the importance of digital transformation in driving high-quality enterprise development and offer valuable insights for relevant decision makers.

Development of a digital transformation maturity model for the construction industry

PurposeDigital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.Design/methodology/approachThis study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.FindingsThe results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.Originality/valueThis paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.

Digital economy, innovation factor allocation and industrial structure transformation-A case study of the Yangtze River Delta city cluster in China.

The attainment of regional high-quality development necessitates the critical role of the digital economy in facilitating the transformation of industrial structures. This study intends to investigate the effect of the digital economy on industrial structure transformation from the perspective of innovation factor allocation using a panel dataset of 41 cities in the Yangtze River Delta region for the period from 2011 to 2020. This paper considers four dimensions to measure the level of industrial structure transformation i.e. industrial structure servitization, industrial structure upgradation, service industry structure upgradation and industrial interaction level. The results of the study suggest that the digital economy can significantly improve industrial structure transformation. The results remain consistent even after several robustness checks. Further, the analysis of the mechanism of action shows that the digital economy can promote industrial structure transformation by optimizing the innovation factor allocation. The study provides several policy implications for the digital economy and its role in the promotion of industrial structure transformation.

Advanced Linguistic Complex T-Spherical Fuzzy Dombi-Weighted Power-Partitioned Heronian Mean Operator and Its Application for Emergency Information Quality Assessment

Against the background of a major change in the world unseen in a century, emergencies with high complexity and uncertainty have had serious impacts on economic security and sustainable social development, making emergency management an important issue that needs to be urgently resolved, and the quality assessment of emergency information is a key link in emergency management. To effectively deal with the uncertainty of emergency information quality assessment, a new fuzzy multi-attribute assessment method is proposed in this paper. First, we propose the linguistic complex T-spherical fuzzy set (LCT-SFS), which can deal with two-dimensional problems and cope with situations in which assessment experts cannot give quantitative assessments. Then, the advanced linguistic complex T-spherical fuzzy Dombi-weighted power-partitioned Heronian mean (ALCT-SFDWPPHM) operator, which incorporates the flexibility of Dombi operations, is proposed. The partitioned Heronian mean (PHM) operator can consider attribute partitioning and attribute correlation, the power average (PA) operator can eliminate the effect of evaluation singularities, and the advanced operator can circumvent the problem of consistent or indistinguishable aggregation results, which provides a strong comprehensive advantage in the evaluating information aggregation. Finally, a fuzzy multi-attribute assessment model is constructed by combining the proposed operator with the WASPAS method and applied to the problem of assessing the quality and sensitivity of emergency information; qualitative and quantitative comparison analyses are carried out. The results show the method proposed in this paper has strong feasibility and validity and can represent uncertainty assessment more flexibly while providing reasonable and reliable results. The method can provide new ideas and methods for the quality assessment of emergency information, and promoting sustainable, efficient, and high-quality development of emergency management.

Multidimensional measurement of the High-Quality development of city Clusters: Dynamic Evolution, regional differences and trend forecasting--based on the basic connotation of Chinese-style modernization

Chinese-style modernization has led to new requirements for city clusters strategies, which is highly important for the high-quality development (HQD) of city clusters and new urbanization. Based on the basic connotation of Chinese-style modernization, an evaluation index system for the HQD of city clusters is constructed from five dimensions, namely, demographic advantages, coordinated regional development, material and cultural-ethical advancement, ecological sustainability, and opening-up. The HQD of 19 city clusters was measured from 2011 to 2021 using the entropy weight-CRITIC method, and the dynamic evolution, spatial correlation and long-term trend were analyzed. The study revealed that (1) the overall HQD of Chinese city clusters has shown continuous growth, and the spatial distribution of the gradient of HQD in the 'East, Center and West' has decreased, but the spatial pattern of 'South High and North Low' has further emerged. (2) The overall and intra-regional differences in the HQD of city clusters gradually narrowed, while the differences between city clusters remained significant. (3) The HQD of city clusters shows obvious positive spatial correlation and obvious spatial agglomeration characteristics, with high-value agglomerations mostly in mature-stage city clusters along the east coast. (4) There is an obvious 'club convergence' phenomenon in the HQD of city clusters; the higher the HQD of neighboring regions is, the greater the probability of upward HQD of city clusters, and the higher the quality of Chinese city clusters shows an upward trend in the long run.

Research On the Path of High Quality Development Enabled by Big Data Technology in the Curved Area of The Yellow River

Big data is a key factor of production to promote the current social development, and the good use of big data technology is a must to achieve high-quality development. Jiziwan of the Yellow River is a strategic overlapping area of the western development and the overland Silk Road, which has very important strategic value both in terms of geographical space and historical development. Therefore, it is particularly important to enable the high-quality development of the Yellow River Jiziwan region with big data technology. By analyzing the relevant data of the high-quality development of the main provinces of the Yellow River Bend in recent years, this paper makes a comparison of the gross product of the region in recent years, the added value of the three major industries, and the R&D investment of the industrial enterprises, so as to get the results of the high-quality development of the Yellow River Bend area and the existing problems. Through these analysis results, this paper puts forward some solutions: using big data technology to optimize regional industrial structure, promote high-quality ecological development and promote innovative development. These optimization paths help promote the importance of the digital economy and promote high-quality, sustainable and coordinated development in the region.

Does ESG advantage promote total factor productivity (TFP)? Empirical evidence from China’s listed enterprises

ABSTRACT The question of whether enterprises are incentivized to improve their environment, society, and governance(ESG)performance is uncertain since scholars have long debated whether or not ESG directly benefits the enterprise. In this study, this research question is addressed by investigating the potential effect on productivity of the net advantage yielded by corporations taking specific ESG behaviours. Using panel data of A-share listed companies spanning from 2010 to 2022, this paper draws multiple research findings. Firstly, the fundamental result of this study shows that the corporate ESG advantages significantly enhance the relevant total factor productivity(TFP). This means that firms have a willingness to adopt behaviours to achieve net ESG advantages due to the productivity gains. Secondly, the heterogeneous analysis indicates that ESG advantages improve TFP for large, state-owned enterprises(SOEs),labour-intensive corporations, and non-mature corporations. Thirdly, in terms of the influential mechanism, ESG advantages improve TFP by enhancing labour expenses and reducing agency costs within the enterprise while assisting enterprises in overcoming external environment uncertainty. The findings illuminate that China’s enterprises are interested in achieving ESG advantages since this enables firms to improve productivity and achieve high-quality development. Simultaneously, this offers novel perspectives for investors to assess ESG performance.

Ecological Safety Assessment and Convergence of Resource-Based Cities in the Yellow River Basin

Promoting the sustainable development of resource-based cities is of great significance for the ecological protection and high-quality development of the Yellow River Basin. In order to solve the dilemma of the sustainable development of resource-based cities in the Yellow River Basin, this paper constructs an ecological security evaluation system. It calculates the ecological security level of 30 resource-based cities in the Yellow River Basin from 2006 to 2020 using the TOPSIS model and carries out a classification convergence analysis. The DID empirical test of ecological security factors by sustainable development planning policies is used to distinguish the development characteristics of different resource-based cities. The results show that (1) the ecological security level of resource cities in the Yellow River Basin is generally well developed, and there are differences between different types of resource cities; (2) the resource cities in the Yellow River Basin mainly rely on industrial transformation to improve the ecological security level; and (3) the local governments pay limited attention to environmental protection.

Measurement and spatial correlation analysis of high-quality development Level: A case study of the Yangtze River Delta urban agglomeration in China

Against the backdrop of slowing economic growth and increasing environmental pressure, the Yangtze River Delta city cluster, as one of the largest city clusters in the world, has become more driven in its pursuit of high-quality development. We constructed a system of 24 evaluation indexes and used entropy-weighted TOPSIS to calculate and study the high-quality development index of urban agglomerations in the region. First, the level of high quality development (HQD) of the Yangtze River Delta city cluster generally improved from 2010 to 2021, with 2017 was the best year, while 2010 was the worst year. Second, in the multidimensional evaluation of HQD, Jiangsu excels in innovation and people's livelihood with 0.524 and 0.534, respectively; Shanghai (0.531) excels in coordinated development; Zhejiang excels in green and economic development with 0.557 and 0.484, respectively; and Anhui lags behind in all aspects. Third, the development process of HQD in the Yangtze River Delta region is uneven, and the level of HQD development varies greatly among the city clusters in the province. The measurement results show that Shanghai (0.511) has the highest score, followed by Zhejiang (0.484), Jiangsu (0.440) and Anhui (0.435). Fourth, spatial correlation analysis shows that Shanghai and Jiangsu are mainly distributed in the double-high region, Zhejiang is distributed in the high-low region, while Anhui is concentrated in the low-low region. The results of this study help us understand more deeply the characteristics and challenges of high-quality development in the Yangtze River Delta urban agglomerations and provide a scientific basis for more precise urban development policies.