In today’s information and digital era, data has become an important basic and strategic resource. Based on the perspective of resource science, this paper systematically discusses the historical inevitability and practical necessity of data becoming a basic and strategic resource, and further discusses the basic and high-order attributes of matching data resources with traditional resources, and then explores the practical difficulties and breakthrough paths faced by the development of data resources. It is found that data becoming resources is the inevitable result of the development of scientific and technological revolution and conforms to the objective law of economic development. With the in-depth development of scientific and technological revolution, data not only has the attribute characteristics matching with traditional resources, but also has high-order attributes such as invisibility, reproducibility, high complementarity and high liquidity. However, data resources also have inherent limitations such as scene dependence, time decay, ambiguity in ownership confirmation, and face practical constraints such as insufficient effective supply, low utilization rate and imperfect governance system. Therefore, it is necessary to attach importance to the resource attributes of data, activate the value of data resources, coordinate the bilateral matching of data supply quantity and quality, promote the cooperation of multi-party data entities and build a unified governance framework system. The future research directions mainly include the academic system construction of data resources, the construction of data basic systems and facilities, the innovative application scenarios of data resources,and the research on data resource governance system, etc., so as to better play the role of data as a basic resource and an innovation engine.
[Objective] This study explores how post-productivist organic agricultural practices facilitate rural return migration. It is of great significance for clarifying the mechanisms through which post-productivism promotes rural revitalization and for identifying sustainable rural development pathways under post-productivist contexts. [Methods] The“Thousand Students, Hundred Villages” social survey data collected by Renmin University of China across 30 provinces from 2018 to 2019 were utilized, combined with geographic location data of villages and satellite imagery data. Regression models were employed to systematically examine the impact and mechanisms of organic agriculture development on rural return migration. [Results] (1) For every 1-percentage-point increase in the level of organic agriculture development, rural return migration increased by 1.4%. (2) Each 1-percentage-point improvement in organic agriculture development led to a 0.4% increase in rural per capita net income, 0.1-percentage-point enhancement in residents’ life satisfaction, and 0.052 μg/m3 reduction in PM2.5 concentration, collectively contributing to return migration. (3) The positive effect of organic agriculture development on return migration was more pronounced in regions with abundant economic, educational, and housing, and healthcare resources, while being relatively weaker in resource-scarce regions. (4) Organic agriculture development not only promoted voluntary return migration, but also helped reduce involuntary return flows. [Conclusion] Organic agriculture development can meet the needs of households through the supply of production, living, and ecological resources, thereby attracting return migrants. Promoting context-specific organic agriculture can help diversify rural functions and achieve rural revitalization.
[Objective] The return migration of highly educated groups represents a new phenomenon in China’s current population mobility. Investigating its spatial and demographic characteristics helps understand new trends in China’s population migration during the transitional period. [Methods] Based on the dual sticky effects of hometown ties and educational ties on highly educated groups, this study defined return migration of highly educated groups as their relocation to either household registration location or university location. Three types of return migration were identified: Type I, returning to home province after educational migration; Type II, returning to home province after employment migration; Type III, returning to the province of their university after employment migration. Building upon this, this study utilized 2020 recruitment data for primary and secondary school teachers in Wuhan, combined with models for spatial and statistical analyses, to reveal the return migration pathways of highly educated groups targeting Wuhan as their intended destination. Then, the spatial and demographic characteristics of this migration were analyzed. [Results] (1)The return migration of highly educated groups with Wuhan as the destination exhibited a concentrated pattern in southeastern China. It formed a diamond-shaped spatial structure, with the Yangtze River Delta, Pearl River Delta, Beijing, and Chengdu-Chongqing regions as four key nodes, while additional nodal points included Shenyang, Kunming, and Changchun. Notably, the majority of return migrants originated from within this diamond-shaped structure. (2) Distinct regional differences were observed among return migration types. Type I migrants predominantly originated from the northeastern and southwestern parts of China, Type II migrants were more concentrated in eastern China, and Type III migration exhibited localized mobility patterns within proximate regions. (3) Samples characterized by “younger age, county-level birth origin, higher education attainment, elite academic institutions, recent graduates, and employment or study location in higher-tier cities” exhibit a higher probability of return migration. [Conclusion] Compared to international skilled migrants and China’s rural migrant workers, highly educated groups in China are more likely to gain human capital advantages in their hometowns or university locations, which strengthens local utility and fosters return migration through hometown ties and educational ties. Moreover, their return migration largely results not from aspiration failures but rather from a spatial re-selection aimed at maximum benefits, which has positive implications.
In response to multiple internal and external challenges, China has proposed the formation of a new development pattern that is dominated by a domestic macrocycle and mutually reinforcing domestic and international dual cycles, which has triggered a shift in the study of regional industrial dynamics from a focus on intraregional factors to one on interregional relatedness. Transportation is an important form of interregional relatedness. This paper first presents an analysis of the research hotspots in existing core Chinese and English literature using CiteSpace software, aiming to clarify the conceptual connotations of transportation from the perspective of relatedness. It then tries to construct a research framework of transportation and regional industry dynamics under the relatedness perspective, and summarizes the research progress of transportation and regional industry dynamics in terms of the intensity, directionality and heterogeneity of transportations. It has three major conclusions. First, in the perspective of relatedness, the change of transportation intensity as a whole significantly affects the scale and structure of industries in the region. Second, the directionality of transportation emphasizes the heterogeneity of the role of factor inflow and outflow between regions, thus affecting the industrial division of labor between regions. Third, according to the heterogeneity of carrying factors, transportation under the perspective of relatedness can be classified into different situations such as material flow or knowledge flow, and have differentiated impacts on regional industrial development. Based on the research progress of intensity, directionality and heterogeneity of transportation, the comprehensiveness and network of transportation, the progress of research methodology and its dynamic association with regional industries may become the focus of future research. Therefore, in the future, it is possible to further expand the comprehensiveness and network nature of transportation under the perspective of relatedness, and integrate multiple transportation modes and network structure analysis methods to serve the theoretical and practical needs of regional industrial dynamic development.
[Objective] Intercity technology transfer is a crucial means of facilitating the diffusion of technological knowledge. This study aims to examine the impact of high-speed rail (HSR) on intercity technology transfer and investigate the mediating pathways from the perspective of information, talent, and capital, thereby providing insights for improving transportation infrastructure and promoting regional innovation-driven development. [Methods] Based on the intercity technology transfer data of 2007-2019, this study employs a panel negative binomial panel model and an intermediary effect model to assess the impact of HSR operation, accessibility, and connectivity on intercity technology transfer. The analysis is conducted from the perspective of city pairs consist of 287 cities, exploring both the direct effects and the mediating pathways. [Results] (1) The commencement of HSR operation, improved accessibility, and enhanced connectivity significantly contribute to the promotion of technology transfer. Notably, accessibility exerts the most substantial influence. (2) The influence of HSR on technology transfer displays heterogeneous patterns. Specifically, the introduction of HSR and enhanced connectivity effectively stimulates the transfer of technology between cities that are situated within a range of 2000 km. The impact of accessibility extends across the entire distance range. Nevertheless, as the distance between cities grows, the effect gradually diminishes. The opening of HSR, connectivity, and accessibility have exerted the most significant impacts on intercity technology transfer from the northeast to western regions, from central to western regions, and from central to eastern regions, respectively. The effect of HSR on patent transfers in cities with high innovation growth types and on patent assignments in cities with low innovation growth types is more effective. (3) The intermediary pathway through which HSR affects technology transfer involves the flow of innovation-related factors such as information, talent, and capital. These factors indirectly facilitate intercity technology transfer among enterprises, resulting in a positive impact. [Conclusion] HSR exerts a significant impact on intercity technology transfer, with its effects exhibiting heterogeneity in terms of distances, regions, and cities. Different regions should optimize urban transportation infrastructure, train schedules, and the transport network to enhance urban accessibility, thereby maximizing the role of HSR in facilitating intercity technology transfer.
[Objective] As an essential production factor for business operation, industrial land prices play an important role in promoting the efficient use of urban industrial land and supporting regional industrial economic growth. This study aims to elucidate the variations in the impact of manufacturing structure upgrading on industrial land prices under different degrees of government intervention, thereby providing references for the market-oriented reform of industrial lands. [Methods] This study selected 98599 micro-level industrial land transaction records from 40 cities in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) urban agglomerations from 2007 to 2019. Using a threshold regression model, this study revealed the impact of the manufacturing structure upgrading on industrial land prices under different degrees of government intervention, considering both full-sample analysis and heterogeneity across urban agglomerations. [Results] (1) Manufacturing structure upgrading has a significantly driving effect on industrial land prices. (2) From the perspective of government intervention, the effect of manufacturing structure upgrading on land prices varied. As the level of intervention increased, its positive impact on land prices gradually weakened. (3) The impact of manufacturing structure upgrading on industrial land prices showed significant differences across urban agglomerations. In the BTH urban agglomeration, this effect was statistically insignificant. However, in the YRD urban agglomeration, it significantly boosted land prices, although this effect weakened as government intervention intensified. [Conclusion] Manufacturing structure upgrading drives up industrial land prices by increasing returns on industrial land; however, this positive relationship weakens as government intervention intensifies. In the future, the Chinese government should fully leverage market mechanisms’decisive role in industrial land allocation, improve the land valuation framework, and establish a sound and transparent pricing system.
[Objective] Scientifically evaluating the spatiotemporal differentiation characteristics of shrinkage and transformation of resource-based cities in China, and understanding their functional relationship and interaction mechanisms are crucial for achieving sustainable development in these cities. [Methods] Based on socioeconomic statistical data and remote sensing monitoring data, an evaluation indicator system was established for shrinkage and transformation of resource-based cities. Using the comprehensive index model, coordinated development model, and geodetector, the spatiotemporal characteristics of shrinkage and transformation from 2000 to 2020 were analyzed, their interactive relationship types were classified, and the key influencing factors were identified. [Results] (1) From 2000 to 2020, both shrinkage and transformation in China’s resource-based cities showed increasing trends, with a spatial clustering patterns. Shrinkage was mainly reflected in the population dimension, while transformation was most evident in the industrial and innovation dimensions. Resource-based cities in Northeast China demonstrated the highest shrinkage degree, while those in the eastern coastal areas showed the highest transformation degree. (2) Most resource-based cities achieved a coordinated state between shrinkage and transformation, but a significant number showed signs of imbalance, predominantly characterized by interactive adaptation types. The effectiveness of urban transformation in alleviating shrinkage remained limited, and spatial variations existed in coordinated development types and interactions between shrinkage and transformation. (3) The interaction between shrinkage and transformation in resource-based cities intensified. Interactions among factors within each system exerted stronger effects than individual factors, with both the depth and breadth of these interactions showing increasing trends. Urban shrinkage restricted transformation through a complex mechanism centered on population outflow and economic growth slowdown, while urban transformation alleviated shrinkage through a reverse mechanism driven primarily by energy-saving and emission-reduction policies. [Conclusion] Over the past 20 years, China’ s resource-based cities have achieved remarkable progress in urban transformation, though its mitigating effects on urban shrinkage remain insufficient. The key approach to achieving sustainable development in resource-based cities lies in promoting comprehensive transformations, establishing differentiated economic and ecological compensation mechanisms, and enhancing energy efficiency and green production levels. This study not only provides an effective framework for analyzing the shrinkage-transformation relationship in resource-based cities, but also offers scientific references for achieving sustainable development in resource-based cities.
[Objective] Promoting the synergistic development of digital and green villages serves as an effective approach to accelerate the cultivation of new-type productive forces and achieve the modernization of agriculture and rural areas. A scientific analysis of the spatiotemporal characteristics and influencing factors of the synergistic development of digital and green villages is crucial for bridging regional development gaps and promoting the comprehensive revitalization of rural areas. [Methods] A comprehensive evaluation indicator system for digital and green villages was established based on the “production-living-ecological” framework. Methods such as the coupling coordination degree model, kernel density estimation, Dagum Gini coefficient, Markov chain, and panel Tobit model were employed to analyze the spatiotemporal characteristics and influencing factors of the synergistic development of digital and green villages in 31 provinces of China from 2011 to 2021. [Results] (1) During the study period, the development index of digital villages in China exhibited rapid growth, while that of green villages showed slower growth. The synergistic development of digital and green villages was still in a state of “low-level coordination”. (2) The degree of synergistic development showed a spatial distribution of “eastern region> central region> northeast region> western region”, with provinces on the east side of the Hu Line showing significantly higher values than those on the west side. (3) An expanding spatial disparity in the degree of synergistic development was observed, and the inter-regional difference was identified as the primary contributor to the overall variation. (4) A notable “club convergence” phenomenon and “spatial spillover” effect were identified in synergistic development degree. Specifically, low-level neighboring areas hindered the synergistic development in a province, and vice versa. (5) Economic growth, industrial structure upgrading, human capital level, and government regulatory capacity, could significantly promote the synergistic development of the two systems, with regional variations in their effects. [Conclusion] Substantial potential remains for improving the synergistic development of digital and green villages in China, with pronounced inter-regional disparities. Accordingly, this paper proposes targeted suggestions to promote the synergistic development of digital and green villages by region and category.
[Objective] In the context of the increasingly urgent need for green and low-carbon transition of economy and society, exploring the impact and mechanisms of artificial intelligence (AI) development on inclusive green growth has become a crucial research priority. [Methods] Using panel data of prefecture-level cities in China from 2010 to 2021, this study measured the levels of inclusive green growth. Building upon this, methods such as the mediating effect model and panel threshold model were employed to empirically examine the impact of AI on urban inclusive green growth and its underlying mechanisms. [Results] The study found that: (1) current AI development significantly promoted urban inclusive green growth, but exhibited a typical inverted U-shaped relationship. Specifically, as AI levels increased, its impact on urban inclusive green growth first increased and then decreased. The current AI development level (0.003) was substantially below the theoretical optimal threshold (0.441). This conclusion remained valid after using Bartik instrumental variables and other robustness tests. (2) In regions with weak digital infrastructure, non-resource-based cities, and peripheral cities, the empowering effect of AI on inclusive green growth was more pronounced. (3) AI indirectly promoted urban inclusive green growth mainly through three channels: optimizing industrial structure, driving technological innovation, and accumulating human capital. (4) Local government competition could dynamically strengthen the empowering effect of AI on urban inclusive green growth. Among them, environmental competition showed a significant positive U-shaped strengthening mechanism, and its coordination with economic competition could better unleash the potential of AI for inclusive green growth. [Conclusion] It is necessary to diversify AI’s transmission channels to promote urban inclusive green growth, formulate differentiated support policies for weak areas, and properly guide local competition, so as to accelerate the release of growth dividends.
[Objective] Digital infrastructure serves as a sustained driving force for the formation of new-quality productive forces. This study aims to reveal the spatiotemporal evolution, regional disparities, and spatial convergence characteristics of digital infrastructure development in China. This is of great significance for promoting balanced regional development and empowering high-quality growth, and thereby driving the development of new productive forces. [Methods] Using China’s provincial panel data from 2013 to 2022, an indicator evaluation system for digital infrastructure construction and application was established. Methods such as the entropy method, Theil index, convergence models, two-way fixed effects models, and spatial econometrics were employed to conduct an in-depth analysis of the spatiotemporal evolution, regional disparities, and spatial convergence of digital infrastructure. [Results] (1) The level of digital infrastructure development in China exhibited an overall upward trend, but there are spatial differences. It shows a spatial distribution pattern where the eastern region has a higher level, while the western and northeastern regions are relatively lower. (2) The overall differences in the development level of digital infrastructure are gradually narrowing. The differences are shifting from being mainly between regions to being more pronounced within regions. The regional differences within regions show a hierarchical structure of “eastern > western > central > northeastern”. (3) In terms of convergence characteristics, a gradually weakening trend was observed in the convergence of China’s digital infrastructure development level. Both national and regional levels of digital infrastructure development demonstrated spatial conditional convergence, with convergence speeds ranked as follows: the central region was th e fastest, followed by the western and eastern regions, while the northeastern region was the slowest. [Conclusion] Bridging the gaps in digital infrastructure development, reducing regional disparities, and strengthening cross-regional collaboration are key to balanced regional development. This study provides theoretical support and practical guidance for promoting the convergent development of regional digital infrastructure and formulating tailored policies based on regional conditions.
[Objective] Promoting low-carbon transformation of grain production is a key measure to ensure food security. Exploring the impact of new quality agricultural productive forces on carbon emissions in grain production can help to expand new avenues for ensuring the sustainable development of the grain system. [Methods] Based on the provincial panel data of China from 2011 to 2022, this study used the fixed effects model, mediation effect model, and threshold effect model to explore the impact of new quality agricultural productive forces on carbon emissions from grain production and its mechanism. [Results] (1) The new quality agricultural productive forces in China shows a continuous upward trend, and the overall regional differences are characterized by the main grain sales areas>main grain production areas>balanced production and sales areas. (2) There was a significant inhibitory effect of new quality agricultural productive forces on carbon emissions from grain production. (3) Mechanism analysis revealed that new quality agricultural productive forces mainly suppresses carbon emissions from grain production by expanding the scale of farmers’ operations. (4) Heterogeneity analysis showed that all three dimensions of new quality agricultural productive forces can reduce carbon emissions from grain production, and the carbon reduction effect was high for new agricultural workforce, followed by new agricultural means of production, and low for new agricultural objects of work; In terms of grain production functional areas and geographical locations, the carbon reduction effect of new quality agricultural productive forces mainly occurred in the main grain producing areas, production and sales balanced areas, and northern regions. (5) There was a single threshold in the process of new quality agricultural productive forces affecting carbon emissions from grain production. When the new quality agricultural productive forces exceeded the threshold value of 0.144, its inhibitory effect on carbon emissions in grain production is stronger than before the threshold. [Conclusion] The development of new quality agricultural productive forces helps to replace small-scale farmers with large-scale households, thereby reducing carbon emissions from grain production. We should actively cultivate new types of agricultural management entities, fully utilize intelligent green new technologies and modern agricultural machinery and equipment, develop moderate scale operations, and achieve organic integration with emerging industries related to agriculture in the future, so as to fully tap into the carbon reduction potential of new quality agricultural productive forces.
[Objective] Low-carbon production represents a key approach for the agricultural sector to facilitate the achievement of the “ dual carbon” goals, and policy interventions significantly influence farmers’low-carbon production behavior. An in-depth investigation into the effect of policy tools on farmers’ low-carbon production behavior can not only evaluate the effectiveness of existing policies but also provide data support for future policy adjustments. [Methods] Using randomized controlled trial (RCT) data collected from 793 Chinese medicinal herb growers in the Qinling-Daba Mountain area in 2022, this study explored the effect of information-embedded policy tools on farmers’ low-carbon production behavior using the binary Logit model, causal mediation analysis, and propensity score matching (PSM) method. [Results] (1) In terms of intervention effect, information-embedded policy tools generally outperformed standalone information-based or structural policy tools in promoting farmers’ low-carbon production behavior. Specifically, command-and-control tools embedded with environmental benefit information and economic incentive tools embedded with self-benefit information demonstrated the optimal intervention effects. (2) Environment-benefit information-embedded policy tools and self-benefit information-embedded policy tools influenced farmers’ low-carbon production behavior through ecological value identification and self-interest value perception, respectively. (3) Under the intervention of environment-benefit information-embedded tools, individuals’ low-carbon information processing pathways follows the central path. However, among self-benefit information-embedded tools, only the economic incentive types follows the central path, while command-and-control tools embedded with self-benefit information for individuals resulted in a dual-path mode of “peripheral path + central path”. [Conclusion] Information-embedded policy tools significantly promote farmers’ low-carbon production behavior. Therefore, when guiding farmers to develop low-carbon agriculture, the government should not only adopt both information-based and structural tools to enhance policy synergy, but also contextualize interventions by making them specific, scenario-based, and life-relevant. Furthermore, an enabling environment must be created to facilitate the value realization of farmers’ low-carbon behavior.
[Objective] How to promote carbon reduction and sequestration in agriculture and rural areas from the macro policy level is a topic of great concern. As an important institutional design for promoting the modernization of agriculture and rural areas, the pilot policy of ecological circular agriculture should have a profound impact on agricultural carbon reduction. The extent of its impact and the mechanism of action deserve in-depth study. [Methods] Based on clarifying the mechanism by which the pilot policy of ecological circular agriculture affects agricultural carbon emission reduction, this paper conducts quasi-natural experiments with the pilot policy of ecological circular agriculture. Based on the balanced panel data of 31 provinces in China from 2000 to 2021, The impact of the pilot policy of ecological circular agriculture on agricultural carbon emission reduction and the spatial spillover effect were systematically investigated by using the regression control method, synthetic control method and difference-in-differences method. [Results] (1) Overall, the pilot policy of ecological circular agriculture significantly reduced the value of agricultural carbon emissions and had a significant inhibitory effect on agricultural carbon emissions in the three pilot provinces of Zhejiang, Anhui and Hainan. Moreover, the benchmark results remained valid after a series of robustness tests; (2) Based on the framework of “scale-structure-technology”, the mechanism test results show that the pilot policy of ecological circular agriculture mainly has an impact on agricultural carbon emission reduction from three aspects: agricultural operation scale, agricultural planting structure and agricultural scientific and technological progress; (3) The results of the spatial spillover effect show that the pilot policy of ecological circular agriculture has a significant promoting effect on agricultural carbon reduction in this region and neighboring regions. [Conclusion] The pilot policy of ecological circular agriculture has great potential for reducing carbon emissions in agriculture and provides theoretical basis and practical support for the promotion of the pilot policy. It is suggested to promote moderate-scale agricultural operations, optimize the agricultural planting structure, and strengthen the support of agricultural science and technology and equipment, so as to accelerate the comprehensive green transformation of agricultural development.
[Objective] As a key initiative of China’s national food security strategy, the policy of major grain-producing areas serves as an important tool for coordinating stable and increased grain production with green agricultural development. Systematically evaluating its effect on the synergistic reduction of agricultural pollution and carbon emission holds significant theoretical and practical significance. [Methods] This study treated the establishment of major grain-producing areas as a quasi-natural experiment. Using panel data from 31 Chinese provinces from 1997 to 2022, a difference-in-differences (DID) method was employed to empirically examine the policy’s effect on the synergistic reduction of agricultural pollution and carbon emission. [Results] (1) The policy of major grain-producing areas significantly promoted the synergistic reduction of agricultural pollution and carbon emission, with a series of robustness tests and instrumental variable estimations confirming the robustness of results. However, the policy effects exhibit heterogeneity across regions with different quantiles of agricultural pollution reduction and carbon mitigation synergy, varying degrees of rural population aging, and levels of agricultural labor transfer. (2) From the perspective of mechanisms, promoting large-scale agricultural operations, advancing agricultural technology, and adjusting the crop structure were effective pathways through which the policy of major grain-producing areas facilitated the synergistic reduction of pollution and carbon emission in agriculture. (3) Environmental regulation and fiscal support for agriculture played positive moderating roles in the process of promoting the synergistic reduction of agricultural pollution and carbon emissions by the policy of major grain-producing areas. (4) The policy of major grain-producing areas also generated additional socioeconomic benefits in the process of promoting the synergistic reduction of agricultural pollution and carbon emission, including ensuring food security, promoting agricultural economic growth, and improving employment levels in the agricultural sector. [Conclusion] The policy of major grain-producing areas can effectively promote the synergistic reduction of agricultural pollution and carbon emission. Therefore, it is recommended to further leverage the policy’s advantages, actively explore synergistic pathways and long-term mechanisms, and promote the synergistic reduction of agricultural pollution and carbon emission tailored to regional characteristics.
The 2022 guiding cases of advance execution of ecological restoration reflect the urgent need for timely restoration in environmental litigation and highlight the necessity of establishing corresponding judicial mechanisms. However, due to the conflict between the requirement for clarity and the urgency of restoration, such cases are extremely rare. Therefore, to ensure the timely restoration of the ecological environment, it is necessary to demonstrate the theoretical legitimacy of excluding the clarity requirement from the conditions for obligating parties to carry out restoration before judgment. This study used logical and normative analysis methods to argue for the legitimacy of excluding the clarity requirement based on the principle of necessity. Since clarity is an institutional prerequisite for advance execution, the function of timeliness in ecological restoration can only be achieved within the injunction system. An injunction, by nature, is a judicial order compelling obligated parties to act or refrain from acting. While prohibitory injunctions (requiring inaction) have already been established through “conservatory injunction measures”, “ecological restoration injunctions” (requiring action) should also be incorporated into the scope of environmental protection injunctions. However, considering the practical need to balance interests, proof of case facts should not be completely excluded. Flexible provisions should be made in legislation, with case-by-case analysis.
