Capita Disposable Income Research Articles

Temporal and spatial evolution of the coupling and coordination between tourism and rural development: A case study of 33 counties in southern Xinjiang

AbstractTourism plays an important role in promoting rural transformation and development globally. Based on the logical relationship between tourism and rural development, this study constructs a tourism and rural development index using two models. The projection pursuit model is used to analyse the temporal and spatial evolution characteristics of the level of tourism and rural development, while the coupling coordination degree model measures the relationship in the counties of four southern Xinjiang prefectures from 2010 to 2019. A panel regression model is used to analyse the influencing factors of the coupling coordination relationship between them. The results show the following: (1) The level of tourism and rural development fluctuates and increases in time, and both demonstrate high‐level agglomeration in some counties (cities) in the northeast and southwest of the four prefectures, spatially. (2) During the study period, the level of tourism and rural development changed from ‘high coupling and serious imbalance’ to ‘high coupling and barely coordinated’. Spatially, the degree of coupling is similar to the high‐value region of the coupling coordination degree. Over time, the spatial heterogeneity of the coupling degree decreases and the spatial heterogeneity of the coupling coordination degree increases. (3) The main influencing factors for the coordinated development of tourism and rural areas are tourism resource endowment, tourist density index, rural employees, rural per capita disposable income, and tourism contribution rate.

Carbon inequality in residential buildings: Evidence from 321 Chinese cities

All human beings contribute to climate change; however, their contributions are not equal. Using China as an example, the core objective of this study is to explore the city-level carbon inequality of residential buildings from 2015 to 2020 combined Theil index and Gini coefficient. The outcomes indicate that: (1) Total residential buildings' carbon emissions in 321 Chinese cities increased from 987.81 million tons (Mt) in 2015 to 1161.70 Mt. in 2020; the leading five cities that own the largest carbon emissions are Beijing, Tianjin, Shanghai, Shenyang, and Harbin in 2020. (2) Among eight major economic zones of China, the highest residential buildings' carbon emission per capita and residents' disposable income per capita are the Northeast Economic Zone and Eastern Coastal Economic Zone, respectively. (3) Both the Theil index and Gini coefficient show that the overall carbon inequality is higher than income inequality; the Theil index decomposition indicates that city-level carbon inequality has declined; the key forces of carbon emission per capita and disposable income per capita inequality are inter-regional inequality (contribution rate: 55%–63%) and intra-regional inequality (contribution rate: 59%–63%), respectively. (4) Moreover, regarding income earners during 2015–2020 period, the top 10% of 321 cities occupy about 33% in the total national residential buildings' carbon emissions; the medium 40% of cities account for about 42% in total carbon emissions; in contrast, the bottom 50% of cities represent only about 25% of the total carbon emissions. These discoveries emphasize the necessity for the Chinese government to pay more attention to city-level residential building carbon emissions to track advances toward residents' sustainable lifestyles.

Social-economic assessment of integrated waste pickers in municipal solid waste management system: A case of Tianjin in China

Currently, China's municipal solid waste (MSW) management system has been changing from mixed collection and treatment system into separated collection and treatment system. Therefore, the source separated ability of MSW, the relevant policies of MSW classification and the MSW management system are still in the stage of exploration and improvement. This study chooses to integrate waste pickers (WPs) from the informal sector into the MSW management system, so that they can conduct secondary sorting of waste as a supplement to source separation. However, the existing research does not provide a method that allows the evaluation of integrated WPs from a dynamic and long-term perspective. In this paper, the system dynamics model of MSW management is improved to provide the ability to analyze the long-term evolution of social economic benefits of integrating WPs for secondary sorting. Taking Tianjin as an example, the scenario analysis is carried out. The results show that, on the basis of the existing mixed management mode, integrating WPs for secondary sorting (80% separated rate) can reduce the waste management cost per ton by 55 yuan in 2030. Under the current situation in Tianjin where the source separation rate of food waste is 20% and the source separation rate of recyclable waste is 60%, integrating WPs can reduce the social economic cost of Tianjin's urban MSW management system by 422.45 million yuan per year from 2022 to 2030. In addition, the results show that even if the source separated rate of food and recyclable waste increases, there is still room for 20%–80% increase in wages based on giving WPs a salary higher than the national per capita disposable income in 2022. This study provides a basis for integrating WPs into Tianjin MSW management system, as well as methods and quantitative tools to integrate WPs for cities in developing countries.

Spatiotemporal evolution of healthcare service capacity at township health centers in China.

This study analyzes the efficiency, spatiotemporal evolution, and influencing factors of provincial township health centers' healthcare service capacity in China. It utilizes an unexpected output super-efficiency slacks-based measure (SBM) model, exploratory spatiotemporal data analysis methods, and a quantile regression model. The results show that the healthcare service capacity of township health centers is better in provinces with a larger proportion of hierarchical diagnoses and treatments pilot projects in cities, and the regional efficiency trend is ordered central > eastern > western > northeastern. The healthcare service capacity of provincial township health centers mainly shows significant spatial correlation and a spatiotemporal distribution pattern of "high agglomeration, low differentiation." Rural population density and per capita GDP significantly improve the healthcare service capacity of township health centers, while local governments' healthcare and health expenditure increases the healthcare service capacity of township health centers in certain quantiles. The urbanization rate and per capita disposable income inhibit the improvement of the healthcare service capacity of township health centers in certain quantiles. The provinces should accelerate the promotion of hierarchical diagnoses and treatment pilot projects in cities and establish national cooperative development models to promote public health.

Agri-food evolution and carbon emissions in Chinese residential consumption: A life cycle analysis of urban-rural disparities and socioeconomic influences

At present, residential food consumption is not only the main driver of global energy expenditure but also a crucial factor shaping the development of the agri-food system. It is guided by the macro-food paradigm and serves as a cornerstone for ensuring comprehensive food security. This study examines both direct and indirect carbon emissions stemming from urban and rural food consumption in China between 2000 and 2021, employing a life cycle perspective. The research also delves into the associated factors influencing these emissions. Through the utilization of the LMDI (Logarithmic Mean Divisia Index) decomposition method, the study estimates the contributory significance of total carbon emissions attributed to residents' food consumption. Furthermore, the investigation undertakes an in-depth analysis of the disparities in the compositional makeup of food consumption among urban and rural populations, along with an exploration of the pertinent driving forces behind these distinctions. The study's outcomes indicate that, overall, there is a reduction in per capita direct carbon emissions, accompanied by a corresponding rise in per capita indirect carbon emissions. Relative to the index of plant-based food consumption, both the carbon emissions associated with, and the proportion of animal-based food consumption exhibited an ascending trend. The carbon dioxide (CO2) emissions stemming from the dietary patterns of urban inhabitants notably surpass those attributed to their rural counterparts, with a discernible and widening disparity between the two cohorts. Within the context of the life cycle analysis, consumption and production serve as pivotal components of the intricate network of indirect carbon emissions. Notably, the proportion of carbon emissions attributed to urban residents surpasses that of their rural counterparts in both the domains of food production and the subsequent phases of processing and transportation. Owing to the irrational configuration of cooking energy utilization among rural inhabitants, direct carbon emissions within the food consumption continuum, as well as carbon emissions derived from cooking energy usage, surpass corresponding metrics among urban dwellers. This discrepancy can be attributed to the unsystematic nature of the cooking energy framework prevalent in rural contexts. Population growth, per capita food consumption and changes in the structure of food consumption are important factors driving the growth of total food carbon emissions. Within this context, an augmentation in the intake of vegetables, alongside desiccated fruits, and vegetables, exhibits the potential to notably curtail carbon emissions emanating from the dietary practices of rural denizens. Similarly, an elevation in egg consumption emerges as a key determinant in substantially mitigating the carbon emissions stemming from the dietary patterns observed among urban inhabitants. The carbon emissions originating from both animal-based and plant-based food consumption among urban and rural populations are substantially influenced by the intricate interplay of factors such as the demographic composition and the per capita disposable income within both these strata of society.

Research on Strategic and Financial Performance of Pop Mart

At present, with the continuous growth of per capita disposable income, Chinas consumption mode has undergone a comprehensive upgrade, and consumers have begun to pursue a more sophisticated lifestyle, and have begun to pay more attention to the spiritual satisfaction brought by goods. With the development of pan-entertainment market and social media, the trend culture has been widely popularized, and the trend toy market in China has ushered in rapid development. More and more enterprises have joined the trend play industry, and the trend play market is facing fierce competition. Chinas per capita GDP continues to soar, the consumption structure has changed, 90 and 00 have become the main consumer groups in the consumer market. Trend toys began to rise, Pop Mart as a representative of the trend toy industry, rose rapidly in a short period of time, and experienced two strategic transformations, leading the development of the trend play industry. This paper mainly analyzes the two strategic layout of Pop Mart in this era, that is, the centralized strategy and the diversified business strategy, and analyzes the impact of its strategic transformation on its financial performance from four aspects: debt paying ability, operating ability, growth ability and profitability.

Prediction of Carbon Tax Levied in China and Its Effects Based on BP Neural Network

Historical data of crude oil, coal and natural gas in China are used to calculate the carbon emission and carbon tax in recent years. It is proved that the nonlinear model, BP Neural Network, is more suitable for the calculation of carbon tax under the influence of various energy factors. Then BP Neural Network and GM (1, 1) have a good learning ability to forecast the carbon tax revenue from 2020 to 2030. BP Neural Network, however, has less error and shows that Per capita disposable income, GDP and Per capita GDP play a decisive role in the development of carbon tax and environmental protection. Based on the assumption that the carbon tax will be imposed and increased, the carbon emission intensity of each province and the carbon tax acceptance of urban residents will be within the ideal range in the next decade. All evaluation indicators of models and data analysis show that the carbon tax has a good policy guidance for energy saving and emission reduction. This study about carbon tax provides a new solution for domestic environmental protection.

Impact of the introduction of high-speed rail on the income gap between urban and rural residents.

The unprecedented expansion and development of high-speed rail (HSR) in China provides a unique opportunity and a new way of thinking for addressing the problem of urban-rural wealth disparities. In this paper, I examine the impact of the introduction of HSRs on the income disparity between urban and rural residents in China. Using panel data from 285 prefecture-level cities from 2004 to 2018, in this paper I employ the double-difference method to assess the impact of HSR on the income gap between urban and rural populations and the mechanism of its action; furthermore, I explore the influence of HSR on urban residents' per capita disposable income and rural residents' per capita net income, as well as the impact of HSR on the flow of elements such as labor and capital. My research findings reveal that the introduction of HSR has greatly widened the income gap between urban and rural residents; however, there is heterogeneity between different East, Central, and West regions, as well as between different levels of cities. A further mechanism study finds that HSR lowers farmers' per capita net income, raises urban residents' per capita disposable income, and widens the urban/rural income gap via mechanisms such as facilitating the interregional mobility of labor and capital factors. Therefore, it is necessary to comprehensively assess the economic effects brought about by HSR, strengthen the construction of urban-rural transport networks, and improve support for rural areas, so as to promote the coordinated development of inter-regional and urban-rural areas.

Economy or ecology? The relationship between biodiversity and human health in regions with different economic development

Climate change and the rapid loss of biodiversity pose threats to human survival and development. However, there remains a limited understanding of the relationship between biodiversity and human health, especially in the context of developing countries. This study pursues two objectives: (1) to explore the relationship between biodiversity and human health; and (2) to investigate how this relationship varies across different economic regions. Using a cross-sectional design, we analyzed data from 31 provinces, autonomous regions and municipalities across China. The dataset encompassed information on biodiversity (animals, plants, and fungi), subjective health, and mental health. We employed a two-stage least squares analysis, designating the proportion of part-time rangers and the completion of investments in wild fauna and flora per unit area as instrumental variables. Subsequently, we examined the moderating effect of the average Per Capita Disposable Income on the relationship between biodiversity and mental health. Additionally, we conducted grouped regression analyses for three regions with varying levels of economic development. The regression model incorporated macroecological, macroeconomic, and sociodemographic data as control variables. The results indicated a correlation between bird, plant species richness, biological richness (the total number of plants, animals, and fungi), and mental health. However, these biodiversity measures were significantly associated with poor subjective health. Additionally, the contribution of biological richness to mental health declines as the average Per Capita Disposable Income rises. The relationship between biodiversity and mental health was significantly negative in regions with low economic development, significantly positive in medium economic development regions, and not significant in high economic development regions. The analysis indicates that as the economy grows, there may exist a lower and upper threshold at which biodiversity exerts a positive impact on mental health. These thresholds merit further investigation. This observed gap might be attributed to the diminishing natural experiences in regions undergoing rapid economic development. The findings of this study offer insights that could guide policy decisions in developing countries, balancing biodiversity preservation, economic growth, and public health.

Evaluation of the Quality of the Age-Friendly Environment in Liaoning Province

The age friendliness of an environment is significant for improving the quality of life of the elderly. This metric is an important measure used by the international community to address the challenges of population aging. In order to explore effective ways to improve the quality of an age-friendly environment, this study considers the theoretical framework of the World Health Organization and combines China’s demographic and policy conditions to develop an urban-scale indicator system for the evaluation of the age-friendly environment (AFE) by including the dimensions of social and physical environments and municipal services. The entropy method and multiple linear regression were used to study the changes and influencing factors of the quality of AFE in 14 prefecture-level cities in Liaoning Province. The research results are as follows. First, temporally, the comprehensive quality of AFE in the cities in Liaoning Province was at a relatively low level, and the overall trend was decreasing. During the evaluation period, the level of age friendliness in various cities was generally low, with a relatively small number of cities scoring higher. Second, spatially, significant regional differences in the age friendliness of the environment existed, which showed spatial patterns of “high in the middle and low on both sides” and “strong in the south and weak in the north”. Third, the dimensions were in the order of physical environment > municipal services > social environment. The social environment was weak for the construction of AFEs in Liaoning Province, and efforts are required to strengthen it in the future. Fourth, aging rate was negatively correlated with the level of AFE. The positively correlated factors were in the order of expenditure for urban and rural community affairs > per capita GDP > per capita disposable income of urban residents. This study provides insights for cities to improve the quality of AFEs, actively respond to population aging, and help promote WHO initiatives in developing countries.

The Research on the Influence of Swarovski Brand Image on Chinese College Students Purchase Intention

With the gradual improvement of China's overall economic level, the per capita disposable income of Chinese families has also increased. This article hopes to take the luxury brand Swarovski as an entry point, and study its influence on Chinese college students' purchase intentions from the perspective of its brand image. And this paper results of the elements of "luxury brand", in order to summarize the influence of the elements of luxury brand on consumers, and provide theoretical guidance for the future research direction of luxury goods. This article is based on the use of a questionnaire survey, the authors found that 68% students positioned Swarovski as a luxury brand, and nearly half of students believe that Swarovski`s strength lies in the variety of styles. This article believes that Swarovski's brand image has a positive correlation with the consumption behavior of university students, that is, the higher the brand image, the more consumption behavior of university students. However, due to the limited economic strength of university students, the premise of the above conclusion is that Swarovski still maintains relatively low prices for the public. At the same time, as a brand, Swarovski should have a reasonable and effective product marketing strategy, but while establishing a brand image, it should also control the quality of its products and let consumers know whether the products they purchase are truly what they want.

Enhancing sustainable livelihoods in the Three Rivers Headwater Region: A geospatial and obstacles context

Applying novel approaches to assess the sustainable livelihood potentially contribute to learning and managing social-ecological systems. This research demonstrates the trajectory of sustainable livelihoods in the Three Rivers Headwater Region (TRHR) of Western China for a period of 2003 to 2017, utilizing a bespoke Sustainable Livelihood Index (SLI). Devised through a top-down data collation method, the SLI integrates comprehensive official statistics, encompassing socio-economic metrics alongside climatic and other environmental conditions. We employed spatial visualization and cold hotspot analysis to discern the spatio-temporal nuances of the SLI. Furthermore, the Obstacle Factor Analysis (OFA) was implemented to identify salient barriers impacting the SLI. Results indicated a steady rise in the SLI over the examined period, indicating progressive enhancements in the livelihood sustainability. However, marked disparities were observed across the TRHR counties, reflecting heterogeneity in socioeconomic progress and resource allocation. While Yushu county displayed commendable growth, Jiuzhi county stood out as a significant cold spot. Notably, natural and financial resources surfaced as paramount stresses to SLI progression, emphasizing the necessity for robust resource management and economic support. Key challenges, such as the grassland carrying pressure index, deteriorated grassland territories, and per capita disposable income were identified as critical obstacles to the sustainable livelihood of pastoral communities. These factors collectively influence economic viability, grassland resource stewardship, and human capital development, which are intertwined with local economic gains and future potentials. In nutshell, this study highlights the multifaceted challenges faced by the TRHR in charting sustainable livelihood pathways and champions recalibrated policies to protect natural assets, amplify economic support, reinforce human capital, and nurture regional synergies for sustainable evolution. The key insights suggest the pressing need for innovative, nature-based solutions that amplify regional-scale livelihood resilience, especially considering the challenges related to natural assets, financial support, and human capital development.

Discriminating the default risk of small enterprises: Stacking model with different optimal feature combinations

Small enterprise default discrimination establishes a risk discriminant model based on financial data, non-financial data, and external macro conditions of small enterprises to obtain their default discriminant. This study constructs the final default discriminant model, taking the predicted default probability vectors from the first modelling as independent variables. From the 2e feature combinations composed of e features, it maximises the default discriminant precision of the same training sample. Accordingly, the study inversely infers three optimal feature combinations corresponding to three models, including logistic regression, support vector machine, and linear discriminant analysis, ensuring the discrimination accuracy of the first modelling by the stacking method. Moreover, five features—industry prosperity index, EBITDA margin, current assets turnover ratio, net profit, and per capita disposable income of urban residents—account for 11% of the features in the optimal feature combination, but their importance accounts for 63%; thus, they are critical to the default risk of small enterprises. Further, the macro features significantly influence the default risk of small enterprises. For example, the importance of four macro features—industry prosperity index, consumer price index, per capita disposable income of urban residents, and Engel coefficient—accounts for 26.26% of the features in the optimal feature combination. Notably, the importance of the ‘industry prosperity index’, which is the greatest influencing factor in the feature combination, accounts for 17.63%. Ultimately, the discrimination accuracy of the proposed model is better than that of the seven classical default discriminant models.

Research on the Factors Influencing Tourism Revenue of Shandong Province in China Based on Uncertain Regression Analysis

According to the analysis of historical tourism data, it was found that tourism revenue is influenced by multiple factors, and there exists a linear relationship between these factors and tourism revenue. Therefore, this paper employs a linear regression model to investigate the factors influencing tourism revenue. However, research on tourism data has found that the disturbance term of the linear regression model is not frequency-stable. This indicates that the disturbance term should be an uncertain variable rather than a random variable. Therefore, this paper adopts an uncertain linear regression analysis model and employs the tourism data of Shandong Province in China from 2011 to 2020 as the sample to investigate the factors influencing tourism revenue. The study provides parameter estimation and residual analysis of the model, as well as predictions and confidence intervals of tourism revenue. Additionally, through an uncertain hypothesis test, it was verified that the adopted model fitted the relevant tourism data well. The results show that factors such as the number of travel agencies, railway length, domestic tourist numbers, and per capita disposable income of urban residents have a significant impact on tourism revenue. Based on the study, recommendations and measures for improving tourism revenue of Shandong Province are proposed.

Impact of regional accessibility on urban residents' income in China: A bidirectional-fixed panel model.

The income gap between regions and its expansion are the main manifestations of the imbalanced and inadequate economic development in China. High-speed railway (HSR) construction is regarded as an important method to drive domestic demand, drive the pulse of the economy, and promote the coordinated development of regions. Based on the opening of HSR and the acceleration of ordinary railways, we used the weighted average travel time model and accessibility coefficient to estimate the changes on accessibility in 286 cities at prefecture-level and above from 2000 to 2018. Then, the influence mechanisms of improving regional accessibility on urban residents' income were estimated by using the bidirectional-fixed effects panel model and the recursive model respectively. We found that: (1) The accessibility of urban areas has been greatly improved due to the opening of HSR and the acceleration of ordinary railway, among which the improvement of HSR cities is greater. (2) The improvement of regional accessibility significantly promoted the income growth of urban residents, and the increase of the regional accessibility coefficient by 1 unit led to an average increase of 2140 yuan in the per capita disposable income of urban residents. (3) There is regional heterogeneity in the impact of improving regional accessibility on urban residents' income, and it has a significant effect on the eastern and northeastern regions. It has a greater positive effect on improving the income of residents in central cities compared with peripheral cities. (4) Regional accessibility can promote urban income growth through regional employment and fixed asset investment. In the future, the transportation network should be further improved to facilitate the regional economic cycle, strengthen the coordination and complementarity of regional economies, and promote regional economic integration so as to promote the improvement of resident income level and the common prosperity of the people.

Analysis of the Grey Correlation Between Higher Education and Economic Development

Regional higher education and economic development are inseparable, so it is of great significance to study the correlation degree between higher education and economic development. This paper integrates the relevant evaluation indexes, and uses the grey correlation analysis method to explore the degree of mutual influence between higher education and economic development in Guangxi. The results show that the gross product of primary industry, per capita disposable income of urban residents and urbanization rate are the key factors affecting the level of higher education; the Di-Clark theorem is not applicable to the industrialization development of Guangxi; the increase of institutions and full-time teachers and the investment of education funds are the main driving force for higher education to promote economic development. Finally, to provide policy suggestions for the high-quality development of higher education and economy in Guangxi.

Environmental factors affecting the risk of generalization for ocular-onset myasthenia gravis: a nationwide cohort study.

The environmental effects on the prognosis of ocular myasthenia gravis (OMG) remain largely unexplored. To investigate the association between specific environmental factors and the generalization of OMG. The cohort study was conducted in China based on a nationwide multicenter database. Adult patients with OMG at onset, who were followed up for at least 2 years until May 2022, were included. We collected data on demographic and clinical factors, as well as environmental factors, including latitude, socioeconomic status (per capita disposable income [PDI] at provincial level and education) and smoking. The study outcome was the time to the development of generalized myasthenia gravis (GMG). Cox models were employed to examine the association between environmental exposures and generalization. Restricted cubic spline was used to model the association of latitude with generalization risk. A total of 1396 participants were included. During a median follow-up of 5.15 (interquartile range [IQR] 3.37-9.03) years, 735 patients developed GMG within a median of 5.69 (IQR 1.10-15.66) years. Latitude of 20-50°N showed a U-shaped relation with generalization risk, with the lowest risk at around 30°N; both higher and lower latitudes were associated with the increased risk (P for non-linearity <0.001). Living in areas with lower PDI had 1.28-2.11 times higher risk of generalization. No significant association was observed with education or smoking. Latitude and provincial-level PDI were associated with the generalization of OMG in China. Further studies are warranted to validate our findings and investigate their potential applications in clinical practice and health policy.

Province-level distribution and drivers of infant mortality in mainland China: a Geodetector-based analysis of data from 2020

ObjectiveThe present study investigated the province-level distribution and drivers of infant mortality rate (IMR) in mainland China.DesignEcological analysis based on publicly available data for all 31 provinces in mainland China.Data...

The dynamic patterns and driving factors of land use conflict in the Yellow River basin of China.

Land use conflict, as the spatial manifestation of conflicting human-land relationship, has a profound impact on sustainable use of regional land resources. Taking the Yellow River Basin (YRB) as an example, a land use conflict assessment model was constructed based on landscape pattern indices. The dynamic patterns and driving factors of land use conflict in the YRB and the corresponding driving factors were then assessed from 2000 to 2020 based on spatial autocorrelation analysis and the geodetector method. Significant spatial and temporal differences in land use conflict were observed in the YRB from 2000 to 2020. During this period, the area of stable controllable decreased by 3465 km2, whereas the areas of strong and extreme conflict increased by 34,964 and 13,057 km2, respectively. The expansion of areas with extreme and strong conflict mostly occurred in regions with high urbanization and human activity, including northern Shaanxi, Hetao Plain, and the Yellow River Delta. The distribution of land use conflict in the YRB from 2000 to 2020 was characterized by significant spatial agglomeration; high-value cluster conflict mainly extended from the midstream area to the upstream area, whereas low-value clusters tended to be concentrated in the upstream area of the Qinghai and Qilian Mountains. The spatial and temporal differentiation in land use conflict from 2000 to 2020 was influenced by factors related to the natural environment, geographic location, social economy, and regional policy in the YRB. The effects of elevation, distance to the nearest major river, population, economic density, and per capita disposable income of residents increased continuously during the study period, whereas the influences of mean annual precipitation and ecological retreat weakened. Analysis of the interactions between driving factors showed significant dual-factor and non-liner enhancement effects on the spatial and temporal differentiation in land use conflict. The findings provide a scientific reference for the comprehensive management of national land and ecological construction in the YRB.

Sustainable development strategies in multi-scenario of rural production space system: A case from mountainous and hilly countryside in southwest China

The spatial system of rural production is a continuum, and the production and management behaviors of different stakeholders interfere with the operation of rural production space system. It has important theoretical value and practical significance for promoting agricultural system sustainable development and realizing sustainable development goals. This study uses statistical data from 2015 to 2021 to construct a system dynamics model of the rural production spatial system and design a multi-scenario simulation scheme to simulate the operation of the rural production space system in Guangnan County. The results show: (1) The logic of correlation between the operation of rural production space system and rural sustainable development is constructed, and five scenarios are designed: the baseline scenario, the scenario of promoting scientific and technological innovation, the scenario of optimizing planting structure, the scenario of strengthening pollution control and the scenario of comprehensive adjustment. (2) The roles of technological inputs, cropping structure and pollution control on the operation of rural production spatial systems vary, with technological inputs contributing the most to increased food production, optimized cropping structure contributing the most to gross agricultural product and rural per capita disposable income, and enhanced pollution control significantly reducing carbon emissions from agricultural production. (3) Based on the simulation results of the operation of rural production space system in mountainous and hilly areas, the sustainable development strategy was proposed from three aspects: increasing technical investment, optimizing planting structure and strengthening pollution control.