Search Results (39)

Drawing on evidence from China’s land market, this study systematically investigates the impact of land misallocation on economic resilience and reveals the underlying mechanism that operates by suppressing technological advancement. A theoretical model of economic resilience is developed, incorporating technology and factor allocation. Empirical analysis is conducted using a panel dataset of 95 Chinese cities (2012–2024) through spatial econometric and mediation models. The findings indicate that land misallocation significantly reduces local economic resilience and exhibits negative spatial spillover effects. The core mechanism is identified as follows: subsidies via low-priced industrial land delay the market exit of low-efficiency firms, hindering the reallocation of production factors to more productive sectors. This suppression of technological progress ultimately weakens a region’s capacity to withstand external shocks. Based on the findings, policy implications include optimizing land supply structure, accelerating fiscal system reform, and strengthening policy coordination. Full article

The containment of misinformation diffusion on social media is a critical challenge in computational social science. However, prevailing intervention strategies predominantly rely on static topological metrics or time-agnostic learning models, thereby overlooking the profound impact of temporal–demographic heterogeneity. This oversight frequently results in a “spatio-temporal mismatch”, where limited intervention resources are misallocated to structurally central but temporarily inactive nodes, particularly during non-stationary propagation bursts driven by exogenous triggers. To bridge this gap, we propose a Spatio-Temporal Deep Reinforcement Learning (ST-DRL) framework for proactive misinformation defense. By seamlessly integrating continuous trigonometric time encoding with demographic-aware Graph Attention Networks, our model explicitly captures the coupling dynamics between group-specific circadian rhythms and event-driven transmission surges. Extensive simulations on heterogeneous networks demonstrate that ST-DRL achieves a Peak Prevalence Reduction of 93.2%, significantly outperforming static heuristics and approaching the theoretical upper bound of oracle-assisted baselines. Crucially, interpretability analysis reveals that the agent autonomously evolves a “Preemptive Strike” strategy—prioritizing the sanitization of high-risk bridge nodes, such as bots, prior to event onsets—thus establishing a new paradigm for predictive rather than reactive network governance. Full article

Common prosperity is an essential requirement of socialism with Chinese characteristics for a new era. Problems caused by the urban rural dual structure, such as resource misallocation, ecological-economic imbalance, and insufficient farmer income growth, not only hinder common prosperity but also conflict with the sustainable development strategy. As the core path to break the dual structure and narrow gaps, the multi-dimensional impact and mechanism of urban rural integrated development on common prosperity need systematic verification. Based on panel data of 31 Chinese provinces from 2014 to 2023, this paper uses fixed-effects and mechanism test models to examine its direct, indirect, and spatial spillover effects, focusing on transmission mechanisms of wage, property, and operating incomes. Findings show: First, it exerts significant positive direct and cross-regional spillover effects on common prosperity; Second, wage and property incomes are key transmission paths, while operating income’s mediating effect is unclear; Third, effects vary geographically, stronger in eastern/central China, weaker in northeast China and insignificant in west China; Fourth, economic and spatial integration play prominent roles, social service integration has inhibitory effect, and ecological integration’s effect is under-released. Accordingly, this paper puts forward countermeasures to optimize resource allocation, tackle the rural operating income dilemma, advance regional coordination, and enhance equal social services, providing references for improving common prosperity policies and rural sustainable development. Full article

Building a sustainable and efficient green agricultural product supply chain (GASC) is crucial for ensuring global food security and promoting environmental sustainability. However, at the regional level, the spatial differentiation patterns of its efficiency and underlying driving mechanisms—particularly the synergistic relationship between technical efficiency and scale efficiency—remain to be elucidated. This study focuses on Hebei Province, a key agricultural region in China. By constructing a multidimensional evaluation index system and employing a two-stage approach combining Principal Component Analysis (PCA) with Data Envelopment Analysis (DEA), we measure and analyze the operational efficiency and regional disparities of green agricultural product supply chains across 11 prefecture-level cities. Findings revealed that the overall efficiency of Hebei’s green agricultural product supply chains required improvement and exhibited a distinct spatial pattern characterized by “high-efficiency dominance with localized lags.” The core bottleneck lies in the failure of most regions to achieve effective synergy between technology and scale, resulting in widespread resource misallocation—either “technology without scale” or “scale without technology”—and causing some areas to experience diminishing returns to scale. Furthermore, excessive reliance on single factor advantages in many cities reveals structural vulnerabilities within their supply chain systems. This study’s primary contribution lies in deepening the understanding that efficiency cannot be driven by technology or scale alone. It theoretically emphasizes that the synergistic coupling of “technology-scale” is key to enhancing the efficiency of regional green agricultural product supply chains. These findings provide empirical evidence and policy insights for building a more resilient and balanced regional green agricultural system. Full article

Social assistance is one of the primary programs organized in developing countries in a bid to reduce poverty. In Indonesia, the government has allocated IDR 152 trillion toward poverty alleviation. However, the persistent misuse of social assistance funds has unfolded to be a serious concern. According to the Ombudsman of Indonesia, approximately 81.37% of the 1004 complaints received between 29 April and 29 May 2020 were related to the misuse and misallocation of COVID-19 social assistance funds. Therefore, this study aims to comprehensively describe the legal enforcement model for preventing the misuse of social assistance funds and to identify the challenges faced by law enforcement from the perspective of legal sociology. In order to achieve the stated objectives, a qualitative approach grounded in legal sociology was adopted, utilizing empirical study methods. Data were collected through in-depth interviews with academics specializing in administrative law and public policy, as well as through an extensive review of the relevant literature. Subsequently, the gathered data were analyzed qualitatively using a descriptive approach. The obtained results showed that the key challenges in preventing the misuse of social assistance funds include weak regulatory frameworks, limited competency among law enforcement officials, and inadequate institutional infrastructure. Cultural factors were also found to play a significant role in influencing the effectiveness of law enforcement. Based on these insights, preventive measures were inferred to be essential and should focus specifically on strengthening the legal structure and utilizing technological tools to enhance transparency and monitoring. Accordingly, the substance of social assistance laws must be revised to include more detailed and specific provisions, while repressive measures should impose stricter sanctions on individuals who engage in misuse. Fostering a shift in the legal culture of society was also considered very important. These combined efforts are expected to reduce the misuse of social assistance funds, improve legal enforcement effectiveness, and essentially contribute to poverty reduction in Indonesia. Full article

The three northeastern provinces of China are the country’s most important grain-producing region, particularly for maize, soybean, and rice, and form its largest commercial grain base. Over the past two decades, cropping structures in this region have undergone notable shifts driven by both climate change and human activities. Generating long-term, high-resolution maps of multi-crop distribution and evaluating their suitability is essential for understanding cropping dynamics, optimizing land use, and promoting sustainable agriculture. In this study, we integrated multi-source satellite imagery from Landsat and Sentinel-2 to map the distribution of rice, maize, and soybean from 2000 to 2023 using a Random Forest classifier. A crop suitability assessment framework was developed by combining a multi-criteria evaluation model with the MaxEnt model. Reliable training samples were derived by overlaying suitability evaluation results with stable crop growth areas, and environmental variables—including climate, topography, soil, hydrology, and anthropogenic factors—were incorporated into MaxEnt to assess suitability. Furthermore, the spatial consistency between actual cultivation and suitability was evaluated to identify areas of misallocated land use. The results show that: (1) the six classification maps achieved an average overall accuracy of 91.05% and a Kappa coefficient of 0.857; (2) the cultivation area of all three crops expanded, with maize showing the largest increase, followed by soybean and rice, and the dominant conversion being from soybean to maize; (3) suitability areas ranked as soybean (376,692 km²) > maize (329,056 km²) > rice (311,869 km²), with substantial spatial overlap, particularly between maize and soybean, suggesting strong competition; and (4) in 2023, highly suitable zones accounted for 57.39% of rice, 39.69% of maize, and 28.89% of soybean cultivation, indicating a closer alignment between actual distribution and suitability for rice, weaker for maize, and weakest for soybean, whose suitable zones were often displaced by rice and maize. These findings provide insights to guide farmers in optimizing crop allocation and offer a scientific basis for policymakers in designing cultivated land protection strategies in Northeast China. Full article

Carbon emission efficiency plays a vital role in the realization of the “dual carbon” goals. Taking land resource allocation as the entry point, this paper explores how land resource misallocation (LRM) affects carbon emission efficiency (CEE) to support the enhancement of CEE and the optimal allocation of land resources. Using 108 cities in the Yangtze River Economic Belt from 2003 to 2021 as an example, this paper constructs a panel smooth transition model (PSTR), with industrial structure as the transition variable, to examine the nonlinear impact effects of LRM on CEF and its regional heterogeneity. The research results show that the LRM index as a whole presents a fluctuating downward trend, while CEF shows a fluctuating but slow upward trend, and the regional differences in both LRM and CEF continue to expand. There exists a significant nonlinear relationship between LRM and CEF. When the advancement of industrial structure index shifts from the low regime to the high regime, the impact of LRM on CEF presents an inverted “U”-shaped curve characteristic. The nonlinear impact of LRM on CEF exhibits regional heterogeneity, and the threshold effect of industrial structure is the main reason for the regional differences in the nonlinear impact. Therefore, it is necessary to accelerate the market-oriented reform of land factor allocation, and to formulate phased and differentiated land resource allocation policies adapted to the stages of industrial structure development, so as to effectively serve the goals of green, low-carbon, and high-quality development. Full article

Industrial chain modernization is vital for driving the development of a modern country, boosting national competitiveness and upholding economic security. This study examines the impact of coordinated two-way FDI development on industrial chain modernization from the perspective of factor allocation, using panel data from 30 Chinese provinces from 2013 to 2023. The empirical results show that coordinated two-way FDI development significantly boosts industrial chain modernization. This finding holds across multiple robustness tests. Mechanism analysis confirms that the alleviation of capital-labor factor misallocation serves as a key transmission channel. Furthermore, heterogeneity analysis reveals significant heterogeneous effects across regions, ownership structures, investment types, and industry sectors. Notably, the synergistic interaction between downward-gradient inward FDI and reverse-gradient outward FDI, along with coordinated two-way FDI development in the manufacturing sector, has the highest gray correlation degree with industrial chain modernization. These findings provide a solid theoretical basis and practical policy insights for advancing industrial chain modernization. Full article

Targeted poverty alleviation is a major national initiative in China. The Hotan region, located within the four prefectures of Southern Xinjiang, is one of the 14 contiguous poverty-stricken areas in China as well as a quintessential inland arid zone. Water scarcity is the primary constraint on development in the Hotan region and a major bottleneck for Northwest China as a whole. However, previous assessments of the effectiveness of poverty alleviation measures have primarily focused on industrial growth itself, lacking an analysis of the adaptability between key regional resource elements and industrial poverty alleviation measures. The core of promoting targeted poverty alleviation in arid regions is properly managing the relationships within the “industry–water resources” system and achieving a balance between resource use, environmental capacity, and economic development. Focusing on the coordinated development of industry and water resources, this study evaluates the spatio-temporal evolution of the industry–water resource relationships in the Hotan region after the implementation of the targeted poverty alleviation policy with the aim of measuring the sustainability of industrial poverty alleviation outcomes in this arid region. The results indicate the following: (1) The targeted poverty alleviation policy has reduced industrial water consumption. Following the policy’s implementation, industrial water consumption decreased by 541 million m³, driven by improvements in water use intensity and shifts in the industrial structure. The primary contributor to this reduction was enhanced water use efficiency within the primary sector. (2) The policy exacerbated the misallocation of water resources relative to industrial output across the region. The Gini coefficient for water resources versus GDP across Hotan’s eight counties and cities rose from 0.26 to 0.32, indicating a shift from a ‘relatively balanced’ to a ‘moderately imbalanced’ allocation. Therefore, achieving sustainable poverty alleviation in this arid region necessitates enhanced coordination between industrial development and water resources. Full article

To achieve deep decarbonization in the transportation sector, this study employs life cycle assessment (LCA) and the GREET model to construct baseline and low-carbon scenarios. It simulates the evolution of emissions and energy consumption within Inner Mongolia’s public transportation energy system (including diesel buses (DBs), electric buses (EBs), and hydrogen fuel cell buses (HFCBs)) from 2022 to 2035, while exploring synergistic pathways for its low-carbon transition. Results reveal that under the baseline scenario, reliance on industrial by-product hydrogen causes fuel cell bus emissions to increase by 3.64% in 2025 compared to 2022, with system energy savings below 10%, and decarbonization potential will be constrained by scale limitations and storage/transportation losses in cold regions. Under the low-carbon scenario, deep grid decarbonization, vehicle structure optimization, and green hydrogen integration reduced system emissions and energy consumption by 66.86% and 40.44%, respectively, compared to 2022. The study identifies a 15% green hydrogen penetration rate as the critical threshold for resource misallocation and confirms grid decarbonization as the top-priority policy tool, yielding marginal benefits 1.43 times greater than standalone hydrogen policies. This study underscores the importance of multi-policy coordination and ‘technology-supply chain’ synergy, particularly highlighting the critical threshold of green hydrogen penetration and the primacy of grid decarbonization, offering insights for similar coal-dominated, cold-region transportation energy transitions. Full article

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

Industrial structure upgrading serves as an important driving force for the sustained and healthy development of the economy, and it has a positive effect on reducing carbon emission intensity. This study uses provincial panel data from China from 2004 to 2019, starting from the dual perspectives of green total factor productivity and labor misallocation, and employs a four-stage mediation regression model to estimate the mechanism of industrial structure upgrading on carbon emission intensity. The research findings show that: for every 1% increase in industrial structure upgrading, carbon emission intensity will decrease by 0.296%; the central region shows the most significant effect, followed by the western region, while the eastern region shows no significant effect. From the view of the influencing mechanism, industrial structure upgrading will promote green total factor productivity and labor misallocation. When each of the two mediating variables increase by 1%, carbon emission intensity will decrease by 0.12% and 0.054%, respectively. Under the influence of industrial structure upgrading, the inhibitory effects of green total factor productivity and labor misallocation on carbon emission intensity have weakened, and the two factors have made it difficult to form a mediating superposition effect within the sample period. The research conclusion provides the policy implications for China to continuously adhere to industrial structure upgrading, pay attention to improving green total factor productivity, and enhance the low-carbon technical level of workers to achieve the “dual carbon” goals. Full article

With the rapid advancement of artificial intelligence and smart manufacturing technologies, the penetration of industrial robots into Chinese markets has profoundly reshaped the structure of the labor market. However, existing studies have largely concentrated on the employment substitution effect and the diffusion path of these technologies, while systematic analyses of how industrial robots affect labor resource allocation efficiency across different regional and industrial contexts in China remain scarce. In particular, research on the mechanisms and heterogeneity of these effects is still underdeveloped, calling for deeper investigation into their transmission channels and policy implications. Drawing on panel data from 280 prefecture-level cities in China from 2006 to 2023, this paper employs a Bartik-style instrumental variable approach to measure the level of industrial robot penetration and constructs a two-way fixed effects model to assess its impact on urban labor misallocation. Furthermore, the analysis introduces two mediating variables, industrial upgrading and urban innovation capacity, and applies a mediation effect model combined with Bootstrap methods to empirically test the underlying transmission mechanisms. The results reveal that a higher level of industrial robot adoption is significantly associated with a lower degree of labor misallocation, indicating a notable improvement in labor resource allocation efficiency. Heterogeneity analysis shows that this effect is more pronounced in cities outside the Yangtze River Economic Belt, in those experiencing severe population aging, and in areas with a relatively weak manufacturing base. Mechanism tests further indicate that industrial robots indirectly promote labor allocation efficiency by facilitating industrial upgrades and enhancing innovation capacity. However, in the short term, improvements in innovation capacity may temporarily intensify labor mismatch due to structural frictions. Overall, industrial robots not only exert a direct positive impact on the efficiency of urban labor allocation but also indirectly contribute to resource optimization through structural transformation and innovation system development. These findings underscore the need to account for regional disparities and demographic structures when advancing intelligent manufacturing strategies. Policymakers should coordinate the development of vocational training systems and innovation ecosystems to strengthen the dynamic alignment between technological adoption and labor market restructuring, thereby fostering more inclusive and high-quality economic growth. Full article

The transition to renewable energy is a critical pathway for achieving low-carbon development and addressing global climate change problems. Therefore, we expand the conventional province-level energy balance table to the urban level, providing a refined assessment tool for evaluating renewable energy transition (RET). This study investigates the impact of climate policy uncertainty (CPU) on urban RET and explores the underlying mechanisms. The findings reveal that CPU significantly inhibits urban RET, with this effect being particularly pronounced in non-capital and inland cities. The mechanisms through which CPU hinders urban RET include exacerbating capital and labor misallocation and suppressing industrial structure upgrading. Furthermore, the moderation model indicates that high-intensity government supervision and low public environmental awareness exacerbate the negative impact of CPU on urban RET. Our findings provide governments with adopting forward-looking climate policies to mitigate the adverse effects of urban renewable energy transition. Full article

Promoting structural deleveraging is a key strategy for China to reduce high debt levels and mitigate systemic financial risks. In this context, the deleveraging of state-owned enterprises (SOEs) has become a national strategic priority. This study explores whether enhancing the quality of internal control as an internal governance mechanism can facilitate the deleveraging process of SOEs. Using a sample of A-share state-owned listed companies from the Shanghai and Shenzhen stock exchanges (2009–2023) and based on resource-based theory and signaling theory, we examine the impact and mechanisms through which internal control quality influences SOE leverage reduction. Our results demonstrate that higher internal control quality significantly promotes deleveraging in SOEs, and these findings remain robust after conducting endogeneity tests and employing alternative model specifications. Improved internal control mitigates resource misallocation and encourages firms to adopt two primary strategies: debt reduction (through short-term liability repayment and retained earnings) and equity expansion. However, the positive effect diminishes as Research and Development (R&D) intensity increases, reflecting the trade-off between innovation-driven growth and financial stability. Further heterogeneity analyses reveal that the deleveraging effect is more pronounced in local SOEs and over-indebted SOEs, as enhanced internal control helps eliminate non-performing liabilities. This study contributes to the literature on the economic consequences of internal control and provides empirical insights for policymakers seeking to optimize the capital structures of SOEs. Full article