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The prolonged dependence on industrial development has accentuated the cumulative effects of pollutants. Simultaneously, influenced by land construction activities and green space depletion, the Urban Heat Island (UHI) effect in cities has intensified year by year, jeopardizing the foundation of sustainable urban development. Prudent urban spatial planning holds the potential to robustly ameliorate the persistent deterioration of the UHI phenomenon. This study selects Jinan City as a case study and employs spatial autocorrelation and spatial regression algorithms to explore the spatiotemporal evolution of urban-rural patterns at the township scale. The aim is to identify key factors driving the spatiotemporal differentiation of Land Surface Temperature (LST) from 2013 to 2022. The research reveals a trend of initially rising and subsequently falling LST in various townships, with low-temperature concentration areas in the southern mountainous region and the northern plain area. The "West-Central-East" main urban axis and the southeast Laiwu District exhibit high-temperature zones. Significant influences on LST are attributed to pollution levels, topographical factors, urbanization levels, and urban greenness. The global Moran's Index for LST exceeds 0.7, indicating a strong positive spatial correlation. Cluster analysis results indicate High-High (HH) clustering in the central Shizhong District and Low-Low (LL) clustering in the northern Shanghe County. Multiscale Geographically Weighted Regression (MGWR) outperforms Geographically Weighted Regression (GWR) and Ordinary Linear Regression (OLR), providing a more accurate reflection of the regression relationships between variables. By investigating the spatiotemporal evolution of LST and its driving factors at the township scale, this study contributes insights for future urban planning and sustainable development. [ABSTRACT FROM AUTHOR]

The study draws attention to the associations between monetary and economic elements and their potential environmental impacts. The study uses time series data from 1960 to 2022 to examine the connection between CO2 emissions, industrial growth, GNE, and inflation in China. The researchers utilized the well-known econometric technique of nonlinear autoregressive distributed lag (NARDL) to examine nonlinear correlations between these variables. The results reveal that GDP, inflation, and economic development influence long-term CO2 emissions. The strong positive correlation between gross national expenditures and economic activity increases CO2 emissions. In the short run, CO2 emissions are positively and statistically significantly affected by inflation. While inflation temporarily affects CO2 emissions, this effect dissipates with time. Industrial activity increases CO2 emissions, and China's fast industrialization has damaged the environment. The energy-intensive fertiliser manufacturing process and fossil fuels increase CO2 emissions. The research shows how government officials and academics may collaborate to create tailored measures to alleviate the environmental impacts of economic activity. [ABSTRACT FROM AUTHOR]

Background: The pharmaceutical sector in Pakistan has grown over a period with export potential, however, there are certain barriers in the framework that regulate the growth and export of domestically manufactured pharmaceuticals. The purpose of this study was to highlight the current challenges that hinder the export of pharmaceuticals, especially to the countries with stringent regulatory authorities (SRA), as perceived by the domestic pharmaceutical industry experts, and to highlight the facilitators that may help to resolve the identified challenges. Methods: In a qualitative study, the data were collected from the consented experts from the pharmaceutical industries in Lahore, Karachi, Peshawar, and Quetta. Industrial experts with a minimum of 10 years of experience and who were serving at managerial levels or above were recruited through purposive sampling. The semi-structured interviews were conducted for the collection of data from industrial experts. Thematic content analysis was applied to conclude the data. Results: Data analysis generated 4 themes and 16 codes. The export of pharmaceuticals, despite having greater potential was regarded as poor, which was attributed to the following: (a) inadequate industrial research and development, particularly on new molecules (b) non-compliance with the cGMP standards, (c) absence of high-tech equipment, (d) unwillingness of the pharmaceutical companies for bioequivalence studies on their generics, (e) unavailability of locally manufactured active pharmaceutical ingredients, (f) disruption in the supply of imported raw material, (g) poor international market perception about local pharmaceutical products and (h) lack of support from regulatory in process expedition. The respondents also suggested the measures for overcoming the above challenges to boost the export of domestic pharmaceuticals and expand their international market share in countries with SRA. Conclusion: Export from Pakistan to the SRA countries can be enhanced with mandatory bioequivalence studies during generic registration. The pharmaceuticals export could effectively contribute to the national economy. [ABSTRACT FROM AUTHOR]

Over the last twenty years, there has been swift growth in industrialization and technological advancements, driving economic progress. Nevertheless, it is inevitable that these sectors will bring about environmental shifts. Thus far, endeavors have been undertaken to assess the influence of industrialization and technological advancements on environmental deterioration. Additionally, the extensive discussion surrounding the impact of financial development, trade openness, and technological innovation on the environment has not yielded conclusive empirical findings. Studies often operate under the assumption of symmetric relationships, potentially leading to biased results. Adding to the discussion on the drivers of carbon neutrality, the time-dependent effects of critical aspects such as financial development and technological innovation should inform meaningful policies for environmental management. This article explores the time-varying causal association between trade openness, industrialization, financial development, technological innovation, and CO2 emissions in Thailand using novel time-varying Granger causality tests. The time-varying causality outcomes demonstrate that the associations change significantly over time, in contrast to the results of Toda-Yamamoto causality. Overall, there exists a bidirectional relationship between industrialization, financial development, trade openness, technological innovation, and CO2 emissions over different time sequences. These outcomes have implications for both policy and research. [ABSTRACT FROM AUTHOR]

This study investigates the positive coupling between the sports industry and tourism, exploring the ways to promote their interconnection. Under state guidance, the integration of sports industry services is facilitated to attract sports culture and tourism fairs, leveraging regional economic development advantages to enhance the industrial market appeal. The emerging leisure consumption mode of sports tourism injects vitality into the economy, fostering the core sports service industry. The coupling of the education and tourism sectors is strategically aligned with long-term national policies. Using IoT technology, this paper employs a grey relational analysis to assess the coupling between the sports industry and tourism, revealing a significant correlation. Experimental results demonstrate a positive coupling trend, likened to conjoined twins with a natural material basis and technical support. This coupling not only aligns with industry trends but also resonates with the "environmental protection era," "green era," and "ecological era," marking a pivotal aspect of industrial development. The study contributes valuable insights into the symbiotic relationship between the sports and tourism industries, emphasizing their interconnectedness and the positive implications for economic and environmental sustainability. [ABSTRACT FROM AUTHOR]

Mytilus edulis is a commercially and ecologically important species found along the east coast of the United States. Ecologically, M. edulis improves water quality through filtration feeding and provides habitat formation and coastal protection through reef formation. Like many marine calcifiers, ocean warming, and acidification are a growing threat to these organisms—impacting their morphology and function. Museum collections are useful in assessing long-term environmental impacts on organisms in a natural multi-stressor environment, where acclimation and adaptation can be considered. Using the American Museum of Natural History collections ranging from the early 1900s until now, we show that shell porosity changes through time. Shells collected today are significantly more porous than shells collected in the 1960s and, at some sites, than shells collected from the early 1900s. The disparity between porosity changes matches well with the warming that occurred over the last 130 years in the north Atlantic suggesting that warming is causing porosity changes. However, more work is required to discern local environmental impacts and to fully identify porosity drivers. Since, porosity is known to affect structural integrity, porosity increasing through time could have negative consequences for mussel reef structural integrity and hence habitat formation and storm defenses. [ABSTRACT FROM AUTHOR]

China's rural revitalization strategy has expanded non-agricultural employment opportunities for rural residents. This has directly raised farmers' incomes and household expenditures, which in turn has contributed to the upgrading of industrial structure. Using provincial data for 2012–2021, our study investigates how this employment transition affects industrial development. The effect of rural residents' consumption expenditures on this relationship is also explored through a linkage model to help measure the extent of the impact. This study further explores the regional differences in this effect and its robustness. The findings suggest that non-farm employment significantly contributes to industrial structural upgrading. However, this effect is not consistent across regions. Moreover, rural residents' consumption plays a pivotal role in this relationship. Governments should therefore encourage more non-farm jobs, stimulate domestic demand and use rural consumption as a key growth catalyst, especially after the demographic dividend disappears. It is also important to take into account regional nuances in policy formulation and make adjustments to cater for these differences to prevent any potential imbalances. [ABSTRACT FROM AUTHOR]

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development. [ABSTRACT FROM AUTHOR]

With the development of the digital economy, industrial structure upgrading plays an important role in realizing high-quality development. Exploiting the quasi-natural experimental setting provided by the Big Data Comprehensive Pilot Zone (BDCPZ) policy in China in 2016, this study evaluates the impacts of the BDCPZ policies on regional industrial structure upgrading using a combination of propensity score matching and difference-in-differences (PSM-DID) with panel data of 30 regions for the period 2008–2021. The results are as follows: (1) BDCPZ policies significantly promote regional industrial structure upgrading. This finding holds after conducting the placebo test and replacing explained variables. (2) BDCPZ policies enhance upgrading through technological innovation and financial deepening. (3) Heterogeneity analysis shows that the promotional effect of BDCPZ policies on industrial structure upgrading is more obvious in economically developed regions, megacities, and east-central regions; overall, regions with high industrialization benefit more. These findings have important implications: First, they provide new empirical evidence from the perspective of policy evaluation on how the digital economy affects industrial structure upgrading. Second, this study sheds light on the mechanism underlying this relationship, helping us understand how the digital economy can further affect the development of the industrial structure. Third, the policy effect is heterogenous, providing a scientific basis for the government to formulate differentiated implementation policies for different regions. This can help local industrial transformation and upgrading, and economic development in these regions through the implementation of big data and digital technologies. [ABSTRACT FROM AUTHOR]

The sustainable development of the sports industry has garnered extensive attention worldwide. In this study, after a rigorous explanation of the connotation of the sports industry development resilience coefficient (SIDRC), the Topsis model and exploratory spatial data analysis were comprehensively employed to evaluate and visualize the SIDRC of 285 cities in China. Additionally, a spatial econometric model was constructed to explore the influencing factors of SIDRC. The major conclusions drawn from this study are as follow: (1) While the SIDRC has improved significantly over the study period, it still remains overall at a low level of resilience with a widening gap between cities. (2) A strong spatial imbalance exists in the distribution of SIDRC, with coastal regions demonstrating greater resilience compared to the central and western regions, and provincial capital cities faring better than other cities. (3) Policy support index, economic development level, structural diversity of the sports industry, and social participation play crucial roles in promoting SIDRC. Finally, social participation has a positive impact on SIDRC in neighboring cities by facilitating resource sharing, market expansion, and extending the industrial chain. The paper concludes by offering recommendations such as increasing the construction of sports markets and public participation, which can optimize the layout of the sports industry and enhance industrial development resilience. [ABSTRACT FROM AUTHOR]

This study introduces the principle of resilience into the study of human settlements. In this study, a comprehensive evaluation model of urban human settlements' resilience based on the provincial region of China was constructed using the Driver–Pressure–State–Impact–Response framework. The spatio-temporal evolution characteristics of urban human settlements' resilience was explored. The influencing factors were analysed by geographical detectors, and the driving mechanism was constructed. Results show that the following. (1) The resilience level of human settlements in China continued to increase, and the resilience level of each province and city changed significantly. The overall clustering effect showed a tendency to fluctuate and weaken. The distribution of cold spot areas became less and less, and the hot spots were moving from northeast China to southeast China. (2) Significant differences existed in the intensity of the impact of different indicators on the resilience system. The value of the impact factor showed an overall upward trend, and the number of key impact factors increased. (3) Improving the ability of scientific and technological innovation, accelerating the transformation and upgrading of the regional economy, increasing the training of talents and making financial inclination in scientific and technological development and industrial pollution control were all important ways for developing and maintaining the resilience of urban human settlements. This study not only introduces a new evaluation of urban human settlements from the perspective of resilience but also explores key impact indices and driving mechanisms, which provides new ideas for studying urban human settlements. [ABSTRACT FROM AUTHOR]

The long-standing development pattern dominated by international circulation makes China face the risk of "low-end lock-in" and "being decoupling". In addition, the current global climate change and environmental crisis are becoming increasingly severe, coupled with the COVID-19 impact. Chinese enterprises must actively build a green development system for domestic industries in a mutually reinforcing manner in the context of the domestic general circulation, in order to adapt to the new dual circulation environment as soon as possible. This paper analyzes the specific coupling and coordination relationship between the two systems based on the relevant data of China's three major industries from 2008–2014 using Index DEA, entropy value method, gray correlation analysis and coupling coordination model. The results of the study show that: the two systems of dual circulation pattern and industrial green development have a strong correlation and basically present a coupling relationship, but within the industry, there is a problem of the collapse of the tertiary industry. In terms of the type of coupling, the domestic and international circulation in general gradually present the green development leading state, except for the primary industrial segment of the international circulation. On the whole, the coupling quality of the two systems needs to be further improved. Based on this, this paper puts forward the following suggestions: (1) coordinate the internal and external development of the industry; (2) take innovation as the driving force to promote the green transformation of industries; (3) take green sharing as the goal to strengthen the policy orientation of green development; (4) take the opportunity of mutual promotion of dual circulation to stabilize the steady state of green development coupling. [ABSTRACT FROM AUTHOR]

The logistics industry and the manufacturing industry are mutually productive factors and service objects, which determines that the two must develop cooperatively. In the increasingly fierce market competition, open collaborative innovation is more conducive to improving the level of linkage between the logistics industry and the manufacturing industry, and promoting industrial development. Based on the patent data of 284 prefecture-level cities in China from 2006 to 2020, this paper uses Gis spatial analysis, spatial Dubin model and other methods to analyze the collaborative innovation between the logistics industry and manufacturing industry. The results lead to several conclusions. (i) The overall collaborative innovation level is not high, and in terms of the evolution cycle, collaborative innovation has experienced three stages: embryo, rapid development and stable development. (ii) The spatial agglomeration characteristics of the collaborative innovation between the two industries are more and more obvious, and the Yangtze River Delta urban agglomeration and the middle reaches of the Yangtze River urban agglomeration play an important role in the collaborative innovation between the two industries. (iii) The hot spots of collaborative innovation between the two industries are concentrated in the eastern and northern coastal areas, while the cold spots are concentrated in the south of the northwest and southwest areas in the late stage of the study. (iiii) The positive influencing factors of local collaborative innovation between the two industries include economic development, scientific and technological level, government behavior, and employment, while the negative influencing factors include information technology level, and logistics infrastructure. Economic development has a negative spatial spillover effect on surrounding areas, while the spatial spillover effect of scientific and technological level is significantly positive. This article aims to explore the current situation and influencing factors of collaborative innovation between the two industries, with a view to proposing countermeasures and suggestions for improving the level of collaborative innovation between the two industries, and also providing new ideas for research on cross industry collaborative innovation. [ABSTRACT FROM AUTHOR]

The logistics industry is closely related to the high-quality economic development. At different levels of industrial structure, the relationship between high-quality development of the logistics industry and the high-quality economic development will vary, resulting in different roles and paths in promoting economic development. However, there is still a lack of research on the relationship between high-quality development of the logistics industry and high-quality economic development at different levels of industrial structure, and further empirical research is needed. It used the benchmark regression model to analyze the impact of the high-quality development of the logistics industry on high-quality economic development, and the panel threshold model was used to analyze the impact of the logistics industry on high-quality economic development at different levels of industrial structure development. The results show that the high-quality development of the logistics industry has a positive role in promoting the high-quality economic development, and in different levels of industrial structure development, the impact of high-quality development level of logistics industry on the high-quality economic development is different. Therefore, it is necessary to further optimize the industrial structure, promote the deep integration and development of logistics and related industries, and continue to promote the high-quality development of the logistics industry. And when formulating development strategies for the logistics industry, governments and enterprises need to consider factors such as changes in industrial structure, the overall goals of national economy, people's livelihood, and social development, in order to provide solid support for achieving high-quality economic development. This paper demonstrates the importance of high-quality development of the logistics industry in high-quality economic development, and it encourages the adoption of different strategies at different stages of industrial structure development to promote high-quality development of the logistics industry, and achieve high-quality economic development. [ABSTRACT FROM AUTHOR]

Innovation efficiency is an important manifestation of regional innovation capacity, and how to improve regional innovation efficiency is crucial to regional development. This study empirically explores the impact of industrial intelligence on regional innovation efficiency and the possible influence of approaches and mechanisms. The empirical results revealed the following. First, the development level of industrial intelligence can positively affect regional innovation efficiency, while beyond a certain level, its role in promoting regional innovation efficiency will weaken, exhibiting an inverted U-shaped effect. Second, compared with the application research by enterprises, industrial intelligence plays a stronger role in promoting the innovation efficiency of basic research by scientific research institutes. Third, human capital situation, financial development level, and industrial structure upgrading are three significant channels for industrial intelligence to promote regional innovation efficiency. Therefore, accelerating the development of industrial intelligence, formulating individualized policies for different innovative entities, and rationally allocating resources related to the development of industrial intelligence are needed to be taken to improve regional innovation. [ABSTRACT FROM AUTHOR]

Whether the place-based industrial policy promotes regional economic growth is a hot issue in the field of regional industrial economic practice. As a major national strategy in China, the Beijing-Tianjin-Hebei industrial coordinated development policy has been implemented more than 8 years. Verifying its effect on regional economic growth and revealing the policy action path will help to further optimize the policy implementation process through feedback. In this paper, the policy effect and its differentiation are empirically studied from 'quality' and 'quantity' respectively by establishing a growth model using the Dual Differences method. The results show that the Beijing-Tianjin-Hebei industrial coordinated development policy improves total factor productivity by 2.26% in terms of 'quality', and reduces GDP growth rate by 4.65% in terms of 'quantity'. For the different region, the GDP growth rate increased by 1.28%, while total factor productivity decreased by 2.63% in Beijing, the GDP growth rate decreased by 3.17% and total factor productivity increased by 0.87% in Tianjin, and the GDP growth rate increased by 2.56% and total factor productivity increased by 1.58% in Hebei. The policy is mainly realized by fixed asset investment, capital deepening degree and enterprise scale expansion, while the effect of labor input, R&D investment and enterprise number is not significant. The policy is to give full play to the driving role of fixed asset investment such as "new infrastructure", increase investment in labor and research and development in the region, strengthen the construction of a competitive market environment, and stabilize the 'quality' and 'quantity' to further release policy dividends. [ABSTRACT FROM AUTHOR]

Infrastructure construction related to the new generation of information technology and 5G technology is an important measure taken by the Chinese government to promote regional economic development. Large-scale infrastructure investment is being carried out simultaneously in China's core and peripheral regions. The COVID-19 pandemic has dealt a severe blow to China's tourism industry, and the application of new technologies seems to blur the spatial boundaries of the tourism industry. Therefore, it is debatable whether the zealous development of large investment projects can really improve the competitiveness of the regional tourism industry. This paper discusses this topical issue by empirically analyzing data from 31 Chinese provinces and cities from 2008–2019 and draws the following conclusions (1) The continuous expansion of new infrastructure investment in China indeed has a positive effect on improving China's overall tourism competitiveness. However, the inverted U-shaped relationship between the two shows that China should not blindly expand the scale of infrastructure construction and make appropriate investment according to the regional industrial development level. (2) Although convergent infrastructure plays an important role in regional industrial competitiveness, the marginal effect has begun to weaken, so the problem of scale inefficiency needs to be addressed. In contrast, the input of innovation infrastructure is insufficient to enhance industrial competitiveness and can be moderately increased to achieve better results. (3) China's core economic areas have a good driving effect on new infrastructure investment, but the original technological innovation and transformation-type facilities are still the key to limiting the improvement of industrial competitiveness. Peripheral areas are more passive recipients with strong demand. Therefore, investment in various types of infrastructure can drive regional development. [ABSTRACT FROM AUTHOR]

China is in a critical period of economic restructuring and optimization, and the vigorous development of the digital economy plays a vital role in the transformation and upgrading of the industrial structure. Using the panel data of 249 prefecture-level cities from 2011 to 2018, this study empirically investigates the relationship and mechanism between digital economy and industrial structure upgrading. The results show that the digital economy significantly promotes the upgrading of the industrial structure, and this conclusion is still valid after robustness tests such as selecting historical data as instrumental variables. The analysis of the mechanism of action shows that the improvement of labor efficiency and the promotion of technology spillover are the important mechanisms of the digital economy to promote industrial structure upgrading. Finally, the study of regional differences shows that the eastern region has the most obvious promotion effect of digital economy development, the central region is the second, and the western region has the least impact. The research here promotes the understanding of the motivation of industrial structure upgrading and the effect, mechanism, and regional differences of the digital economy enabling the development of a modern industrial system. [ABSTRACT FROM AUTHOR]

In the funding statement, the project number from the funder Prince Sattam bin Abdulaziz University is listed incorrectly. The correct project number is: PSAU/2024/01/99520.By Dan Zheng; Abdullah Addas; Liaqat Ali Waseem; Syed Ali Asad Naqvi; Muneeb Ahmad and Kashif SharifReported by Author; Author; Author; Author; Author; Author [Extracted from the article]

Policy synergy is necessary to promote technological innovation and sustainable industrial development. A radial basis function (RBF) neural network model with an automatic coding machine and fractional momentum was proposed for the prediction of technological innovation. Policy keywords for China's new energy vehicle policies issued over the years were quantified by the use of an Latent Dirichlet Allocation (LDA) model. The training of the neural network model was completed by using policy keywords, synergy was measured as the input layer, and the number of synchronous patent applications was measured as the output layer. The predictive efficacies of the traditional neural network model and the improved neural network model were compared again to verify the applicability and accuracy of the improved neural network. Finally, the influence of the degree of synergy on technological innovation was revealed by changing the intensity of policy measures. This study provides a basis for the relevant departments to formulate industrial policies and improve innovation performance by enterprises. [ABSTRACT FROM AUTHOR]

Agriculture faces a contradiction between sustainable resource utilization and maintaining market competitiveness. As a major agricultural product, the sustainability and competitiveness of the apple industry have become important topics. This study analyzes the competitiveness of China's apple industry and the factors affecting it. Using 2004 and 2018 data for eight Chinese provinces, principal component analysis and spatial autocorrelation are used to examine competitiveness in terms of five aspects: market, production, technology, organization, and environment. The results indicate that Shandong, Shaanxi, and Gansu were the most competitive during the study period while Hebei, Henan, and Ningxia lagged behind. Regional differences are obvious, with Shandong in particular showing a clear competitive advantage. Although no spatial agglomeration is observed in China's apple industry, with ongoing industrial development, local spatial correlations in the five aspects of competitiveness in the eight provinces have been increasing and gradually stabilizing. This study's findings suggest that improved scientific production, reasonable capital investment, and an established industrial chain are needed to promote local agriculture, economic development, and the central role of the apple industry. [ABSTRACT FROM AUTHOR]

The economic growth of a nation under the competition among countries can result from the interaction of the diversity and complexity of product export and import relations on the globe. This research aims to evaluate the competitiveness of South Korea's trading products and its partner countries' dependency by implementing a product and partner-based analysis. This research raises questions about the transactional positions of products and trading partners based on the diversification of import-export relations of South Korea. This study utilizes the matrix of products and trading partners from the Korean product export and import data from 1995 to 2015. The research analyzes Korea's product competitiveness and dependency of trading countries on Korea using the Revealed Comparative Advantage (RCA) and a nonlinear iterative method (NIM). The study finds that the products of several manufacturing industries showed a large production scale. From the global perspective, the trade dependency on Korea was high in Asia and in Africa and South America where the portion of underdeveloped or developing countries is relatively large. This research suggests that Korea may face difficulties of continuing growth if it maintains or intensifies its trade relation pattern under the environment of rapidly changing technology and economy. Therefore, diversification and mutual complementarity could be important for the export of promising products and industrial development policy. [ABSTRACT FROM AUTHOR]

The funding statement for this paper is incorrect. The correct funding statement is: This research is funded by the University of Economics and Law, Ho Chi Minh City, Vietnam, and Vietnam National University, Ho Chi Minh City, Vietnam.By Nguyen Thi Quy; Nguyen Chi Hai and Ha Thi Thieu DaoReported by Author; Author; Author [Extracted from the article]

As the Chinese economy grows, the imbalance of industrial structure is prominent, and the optimization of industrial structure has become an urgent problem. Evaluation of industry is an important step in industry optimization. To this end, this study proposes an integrated evaluation method combining social network analysis (SNA) and the multi-criteria decision making (MCDM) method. Specifically, SNA method are used to calculate indicators, the measurement weights are calculated by the Entropy Weight (EW) Method, and the rank of each industry is determined by the TOPSIS method. Critical industries are identified based on China's input-output data from 2002 to 2017. The results indicate that Manufacturing Industry and the Metal products have a high evaluation, but the Research and Development have a low evaluation value at all times. According to the results, we suggest that the government should optimize the allocation of resources and promote the transfer of resources to balance industrial development. [ABSTRACT FROM AUTHOR]

Background: China's economy has been transitioning from a phase of rapid growth to high-quality development. The high-quality development of industry is the foundation of a sustainable and healthy growth of national economy, and is of great significance to improve people's living standards, and to meet people's needs for a better life. Methods: We develop an evaluation index system of high-quality development of industry from the perspectives of industrial benefit, innovation ability, coordination ability, green ability, opening ability and sharing ability. Based on a panel data of 30 provinces in China during 1999–2018, we evaluate the level of high-quality development of industry using the entropy-weight method and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Meanwhile we select six specific years and adopt the Natural Breaks method to classify the provinces according to their levels. At last, Moran's I index is used to analyze the spatial correlation among the provinces. Results: Opening ability and innovation ability are found to have greater impacts on industrial high-quality development than other indices, and their influence has been increasing in recent years. There are large spatial and temporal differences among different provinces. Municipalities and coastal provinces are found to be at constantly high levels. The levels in the central region dropped first and then increased, however it was the opposite in the western region. In the northeast region, the levels fluctuated greatly. Overall, the high-quality development of industry among China's provinces shows positive spatial correlation. Most provinces in China are in High-High and Low-Low clustering States. The High-High clustering type is mainly distributed in the eastern region and the Low-Low clustering type is mainly distributed in the western and central regions. Conclusion: (1) Innovation ability and open ability are the most important factors. (2) Green ability has not sufficiently contributed to China's industrial development. (3) Regional and time evolution differences are significant. (4) There is a significant and stable spatial clustering effect in the high-quality development of industry among China's provinces. [ABSTRACT FROM AUTHOR]

This paper empirically studies the relationship among inclusive finance, industrial structure upgrading and farmers' income, using the panel data of 28 provinces in China from 2006 to 2016.The research finds that inclusive finance can significantly promote the increase of farmers' income. Moreover, the Upgrading of Industry Structure (UIS) is the intermediary mechanism of inclusive finance to promote the increase of farmers' income, and this intermediary mechanism is heterogeneous among farmers with different income levels. Finally, the promotion effect of the UIS on farmers' income is affected by the threshold effect of inclusive finance. Compared with the development level of low inclusive finance, the promotion effect of the UIS on farmers' income is stronger under the development level of high inclusive finance. According to the results of empirical analysis, we suggest that the development strategy of inclusive finance should aim at the industrial development in rural areas, promote the organic connection between farmers and modern agricultural industry, and drive farmers to increase their income through the transformation and upgrading of rural industries. [ABSTRACT FROM AUTHOR]

The spatial agglomeration of capital factors has become an important force affecting regional economic development and industrial structure. Investigating the spatial relationship of capital factor agglomeration is a key way to accelerate the upgrading of urban industrial structure and realize sustainable development. Based on the panel data of 284 cities in China from 2008 to 2017, we use the theoretical framework of spatial econometrics and estimate the spatial effects of capital factor agglomeration on the upgrading of urban industrial structure. Both the global Moran index and the local Moran scatter chart present that the agglomeration of capital factors and the upgrading index of urban industrial structure shows the characteristics of spatial agglomeration. The results reveal that the agglomeration of capital factors can significantly promote the upgrading of the industrial structure of local and surrounding cities. Still, the spatial spillover effect is not significant. We then explore the possible factors that limit the spatial spillover effects of capital agglomeration. Using the results of the paper, we provide policy suggestions for strengthening urban industrial construction and optimizing the urban governance model. [ABSTRACT FROM AUTHOR]

The I PLOS ONE i Editors retract this article [[1]] because it was identified as one of a series of submissions for which we have concerns about peer review integrity and similarities across articles. Reference 1 Du E, Ji M (2021) Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms. [Extracted from the article]