Regional Allocation Research Articles

Analysis of regional water resources spatial pattern and allocation equity

Water scarcity is a worldwide concern, and with the impact of climate change and human activities, the imbalance in the distribution of water resources has further intensified. The equitable allocation of water resources has become a thorny issue for water resources management authorities. It is challenging to find a relatively equitable method of water resources allocation. This study aims to propose a method for evaluating the fairness of water resources allocation, which can be used both to evaluate the fairness of water resources allocation and as a basis for water resources allocation decisions. The specific approach is to first analyze the spatial pattern of regional water resources by using water resources abundance and water resources intensity, and then to conduct a comprehensive analysis of regional water resources allocation fairness by combining Lorenz curve, Gini coefficient and Theil index to form an index system that can systematically analyze the spatial pattern of water resources, allocation fairness and its changes. A real-world example study was conducted in the Yangtze River Delta region of China, and the results showed that the index system can well reflect the allocation of water resources among regions and cities within the region. The results obtained using this method can provide some reference for promoting coordinated regional development.

Provincial inequality of China's progress towards universal health coverage: An empirical analysis in 2016-21.

Achieving universal health coverage (UHC) is a crucial target shared by the Sustainable Development Goals (SDGs). As UHC levels are influenced by factors such as the regional economy and resource allocation, subnational evidence in China is urgently needed. This study aimed to monitor provincial progress from 2016 to 2021, thereby informing the development of region-specific strategies. Based on the UHC monitoring framework proposed by the World Health Organization, a UHC index was constructed comprising the service coverage dimension (16 indicators) and financial protection dimension (four indicators). In this observational study, routinely collected health data from 25 provinces (autonomous regions and municipalities) in mainland China were obtained from statistical yearbooks, relevant literature, and nationally representative surveys. The indices were calculated using geometric means. Socioeconomic inequalities among provinces were quantified using the slope index of inequality (SII) and relative index of inequality (RII). From 2016 to 2021, China made laudable progress towards achieving UHC, with the index rising from 56.94 in 2016 to 63.03 in 2021. Most provinces demonstrated better performance in service coverage. Western provinces generally presented faster rates of progress, which were attributed to more substantial increases in financial protection. Despite significant disparities, with the UHC index ranging from 77.94 in Shanghai to 54.61 in Fujian in 2021, the overall equity of UHC has improved across the 25 provinces. SII decreased from 17.78 (95% confidence interval (CI) = 11.64, 23.93) to 12.25 (95% CI = 5.86, 18.63) and RII from 1.38 (95% CI = 1.29, 1.46) to 1.22 (95% CI = 1.16, 1.29). However, the non-communicable disease (NCD) domain experienced a drop in both index score and equity, underscoring the need for prioritised attention. In the context of SDGs and the 'Healthy China 2030' initiative, China has made commendable progress towards UHC, and inter-provincial equity has improved. However, substantial differences persisted. The equitable realisation of UHC necessitates prioritising the enhancement of service capacity and financial protection in less developed regions, particularly by addressing shortages in the general practitioner workforce and mitigating catastrophic payments. Developed regions should focus on preventing NCDs through effective interventions targeting key risk factors. This study provides insights for other countries to adopt comprehensive monitoring frameworks, identify subnational disparities, and introduce targeted policy initiatives.

Joint optimal allocation of regional water and land resources considering their mutual feed relationship

Water and land resources are indispensable prerequisites for the sustenance and advancement of human civilization. In recent decades, China has faced significant challenges in managing its water and land resources due to the intensifying competition resulting from rapid urbanization, industrialization, and population growth. The joint optimal allocation of water and land resources can effectively address these issues. However, there have been limited accomplishments in investigating the integrated water and land resources allocation system’s interaction with social, economic, and environmental development. This paper develops a novel joint optimal allocation model of regional water and land resources (JOAMRWLS). The model integrates water and land resources for integrated allocation, taking into account the mutual feed relationship between them, and thereby achieving comprehensive utilization and coordination of water and land resources within the region. Then a two-layer nesting algorithm based on successive approximation and nonlinear programming (SA-NLP) is proposed to solve the model, obtaining the regional optimal land use pattern and optimal water allocation scheme. Subsequently, this paper uses Luoyang City in Henan Province, China, as a case study to verify the proposed JOAMRWLS. The results indicate that the water volume and area of each land use type tend to stabilize after the fifth iteration of the calculation with a consistent water volume of 18.65 × 108 m3. Compared with the conventional optimization model of water resources (COMWR), the JOAMRWLS encompasses five cities experiencing water scarcity, whereas the latter includes twelve such cities. Furthermore, the economic benefit of the JOAMRWLS is 2.65 × 1011 CNY, surpassing that of the former at 2.56 × 1011 CNY, highlighting its superiority.

Towards a Comprehensive Framework for Regional Transportation Land Demand Forecasting: Empirical Study from Yangtze River Economic Belt, China

China is currently experiencing rapid expansion in its transportation land. To promote sustainable land use, accurately estimating transportation land demand is crucial. This study aims to develop a comprehensive framework for urban transportation land forecasting within the Yangtze River Economic Belt (YREB), providing support for optimizing regional land allocation. Employing methods such as meta-analysis, statistical analysis, and BP neural network analysis, this study forecasts the transportation land demand of 127 cities in the YREB. The study findings indicate that cities with high transportation land demand are mainly distributed in the middle and upper reaches of the Yangtze River. Moreover, the growth rate of transportation land in the upper reaches significantly outstrips that in the middle and lower reaches, suggesting a focus shift in transportation infrastructure construction toward the upper regions. Additionally, some cities within the YREB face a mismatch between the supply and demand of transportation land, necessitating proactive adjustments to their land supply plans to achieve a balance between supply and demand. The main contribution of this study is the development of a comprehensive and adaptable framework that guides the development of future strategies for optimal land allocation by forecasting transportation land demand at a regional level.

The Influence of Fiscal Balance Funds and Regional Own-Source Revenues on Regional Expenditures

The purpose of this study is to examine the relationship between regional original income and general allocation funds as well as the spending patterns of regency and municipal administrations in West Sumatra Province from 2018 to 2022. Twenty regencies/cities and West Sumatra Province were selected for the sample using a comprehensive sampling technique within the allotted period. A t-test result of 7.788 and a significance level of 0.000 demonstrate that the General Allocation Fund does, in fact, have an effect on Regional Expenditures. There is a discrepancy between the calculated t-value (7.788) and the t-table value (1.987), which means that the significance value (0.000) is less than 0.05. There is no statistically significant relationship between regional original income and regional expenditures, as shown by the calculated t-test result of 1.389 and a significance value of 0.168. The comparison reveals that the calculated t-value (1.389) is lower than the t-table value (1.987), and that the significance value (0.168) is more than 0.05. However, Regional Expenditures are affected by both the General Allocation Fund and Regional Original Income, as shown by the F-test result of 51.233. This number is much lower than the 0.05 cutoff and higher than the 3.10 F-table value at the 0.000 level of significance.

Analysis of the coupling coordination between traditional Chinese medicine medical services and economy and its influencing factors in China.

The coordinative relationship between medical treatment and the economy is an important part of promoting the sustainable and healthy development of a social economy, and it is conducive to promoting the coordinated development of the two systems. Based on constructing a comprehensive evaluation index system for the relationship between traditional Chinese medicine medical services and economic development, the entropy method, coupling coordination model, and Tobit model are used to calculate the comprehensive development level, coupling coordination degree, and influencing factors of the two systems in 31 provinces of China from 2015 to 2021. Suggestions are proposed for the coordinated development of traditional Chinese medicine medical services, and economy. The results showed that the development level of traditional Chinese medicine was higher than that of social and economic development, the relative development gap between the two systems was gradually narrowed, and the coupling coordination degree increased steadily; however, the regional differences were large. The relative development level and coupling coordination degree of each region show a development pattern of eastern > central > western > northeast; the coupling coordination degree of the two systems in the spatial region was positively correlated and was enhanced year by year. From the perspective of influencing factors, the level of economic development is the decisive factor in the coupling and coordination between traditional Chinese medicine medical treatment and the social economy. Factors such as human capital and health level in traditional Chinese medicine have an inhibitory effect on the coordinated development of the two systems. So, China should focus on optimizing the regional allocation of traditional Chinese medicine medical personnel, improving the quality of medical services, and enhancing the health level of medical personnel.

The impact of human capital misallocation on green economy efficiency: Empirical analysis of Chinese urban agglomerations

This paper uses panel data of 260 prefecture-level cities from 2000 to 2019 to explore spatial characteristics such as spatiotemporal divergence and dynamic convergence based on measuring the level of human capital misallocation in Chinese cities and empirically tests the green development effect of human capital misallocation. The study finds that: ① the human capital misallocation levels of the country and the eight major urban agglomerations show a fluctuating downward trend. ② Divergences in human capital misallocation continue to narrow across the country and urban agglomerations, and the difference between inter-urban agglomerations is the primary source of regional difference. ③ The YRD, PRD, MYR, HC, and CP have significant σ-convergence characteristics of human capital misallocation. Meanwhile, the country and each urban agglomeration show significant spatial absolute β-convergence and conditional β-convergence trends. ④ Human capital misallocation significantly negatively affects green economic efficiency, inhibiting green economy efficiency. Therefore, in the future, it is necessary to improve the match between regional industrial structure and human capital allocation through a combination of targeted policy guidance and market mechanisms tailored to local conditions to enhance the efficiency of the green economy. The significance of the study lies in accelerating the accumulation of human capital while realizing the appropriate matching of human capital, releasing the human capital dividend to the maximum extent, and boosting the structural reform of the labor market to realize the transformation of the green economy.

Promoting the Achievement of Carbon Neutrality Targets: Systematic Review of Research Dimensions and Measure Methods on Carbon Equity in China.

Carbon equity is the balance between carbon reduction responsibilities and development rights. The review of carbon equity in China can help it achieve carbon neutrality targets and provide valuable insights to other emerging countries. This study aimed to systematically sort, classify, compare, and prospect the research dimensions and measure methods for carbon equity. The research dimensions were first classified into intergenerational, regional, trade, and income carbon equity by literature analysis. Intergenerational carbon equity explores the balance of carbon emission rights among generations using integrated assessment models (IAM). Regional carbon equity analyzes the socioeconomic effect of regional carbon emission rights allocation by IAM or regional differences under a specific allocation assumption by the Theil index. Trade carbon equity studies the relationship between carbon emissions and economic benefit transfer embodied in inter-regional trade, which is more suitable for calculating by methods with comparable results, such as the optimized regional environmental inequality index. Income carbon equity investigates the carbon footprint heterogeneity among income groups by the carbon Gini coefficient. This paper further discusses potential research directions for each dimension. Notably, all research dimensions did not consider promoted strategies for carbon equity, which should be a priority for future studies.

Spatial-Temporal Variations and Driving Factors of the Coupling and Coordination Level of the Digital Economy and Sustainable Rural Development: A Case Study of China

Sustainable rural development forms a robust foundation for economic and social sustainability. Moreover, the digital economy acts as a catalyst for advancing rural sustainable development by altering the distribution of production factors. Thus, this study concentrates on 30 provinces in China, constructing an evaluation index system for both the digital economy and rural sustainable development. The study employs various methods and models to analyze the spatiotemporal changes and driving factors affecting the coupling and coordination between these two aspects. The research findings are as follows: the coupling and coordination levels among provinces in China have been on the rise year by year. By 2022, the coupling and coordination levels of most provinces range between 0.5 and 0.6. Regional disparities are the primary determinant of the poor overall coupling and coordination level in China. In 2022, the coupling and coordination level in the eastern region is 0.6663, compared to 0.5420 in the central region and 0.5087 in the western region. Factors such as urbanization, industrial structure transformation, technological innovation, higher education, economic development, and government support significantly influence the coupling and coordination level. Nevertheless, their effects vary across regions, with a more pronounced impact in the eastern region than in the central and western regions. Therefore, this paper proposes policy recommendations, including infrastructure optimization, rural digitization promotion, regional resource allocation enhancement, cross-regional development mechanism exploration, and differentiated development strategy implementation.

Research on the impact of regional integration policy on carbon emissions--Taking the Yangtze River Economic Belt as an example.

The Yangtze River Economic Belt serves as a paradigm of ecological integration and high-quality development within China. Under the constraints of the "Dual Carbon" goal, how does the integrative policy of the Yangtze River Economic Belt, aimed at reinforcing inter-regional industrial cooperation, impact carbon emissions across various provinces within the region? Leveraging panel data from 30 Chinese provinces spanning 2009-2019 and treating the 2016 promulgation of the "Yangtze River Economic Belt Development Planning Outline" as a quasi-natural experiment, this study employs a Difference-in-Differences (DID) model for discerning the effects of regional integration policies on carbon emissions, intensity, and efficiency in the 11 provinces of the Yangtze River Economic Belt. The research further delves into the underlying mechanisms through which policy interventions modulate provincial carbon emissions. Key findings include: (1) The policy's enactment has significantly attenuated provincial carbon emissions and intensity, albeit somewhat hampering the enhancement of carbon efficiency-conclusions robust to parallel trend and placebo tests; (2) Heterogeneity analyses reveal disparities in the policy's carbon emission effects, contingent on varying economic development levels and geographical loci; (3) Mechanistically, while the integration bolsters regional environmental governance and strengthens economic ties-thereby curtailing provincial emissions-it is evident that local governments have been somewhat inept in effectively channeling the influx of substantial short-term capital, hence stifling provincial carbon efficiency. In light of these insights, it is posited that local governments within the Yangtze River Economic Belt should ardently endeavor to refine and elevate regional industrial structures, champion the construction of an integrated regional market, intensify capital oversight and coordinated utilization, and enhance the efficiency of regional capital allocation, all in the quest to augment regional carbon emission reduction performance.

PENGARUH PERTUMBUHAN EKONOMI, PENDAPATAN ASLI DAERAH, DAN DANA ALOKASI UMUM TERHADAP PENGALOKASIAN ANGGARAN BELANJA MODAL PADA KABUPATEN DI PROVINSI SUMATERA UTARA

This study aims to determine the effect of economic growth, regional original income and general allocation funds on the allocation of the capital expenditure budget in North Sumatra Regency in 2018-2020. Several previous studies on the capital expenditure budget showed different results. Therefore this research, this research needs to be done to retest the theory of capital expenditure budget. The sample of this study is the entire population consisting of 3 years. The research method used is qualitative by using secondary data sourced from APBD budget reports obtained from the official website of the directorate general of financial balance at the Ministry of Finance and from the Central Statistics Agency. The data analysis technique used is descriptive statistical analysis and multiple linear regression analysis. The analysis process used first is descriptive statistics, classical assumption test, then hypothesis testing. The results of this study partially show that economic growth, local revenue and general allocation funds have a significant effect on the capital expenditure budget. And the simultaneous results of economic growth, regional original income and general allocation funds have a simultaneous effect on the capital expenditure budget

The Impact of Regional Expenditures on the Quality of Human Development in South Sumatra

The quality of human development depends on the level of fulfillment of their needs in the fields of health, education, and per capita spending. The government as a driver of development activities has a vital role in human development, especially after the pandemic era which previously had a negative impact on people’s quality of life. Through an effective regional budget allocation, the government can continue to improve the quality of human development toward the expected goals of prosperity. This study seeks to describe the effect of regional spending on the quality of human development in South Sumatra Province. The data used is time series data for 2006–2022. The analysis used is simple linear regression. The results obtained are that regional spending has a positive and significant effect on the Human Development Index (HDI). This means that the quality of human development in South Sumatra depends on regional expenditure activities in sectors that support the HDI component. Keywords: regional expenditures, HDI

Research on the Impact and Opportunities of the Digital Economy Promoting the Development of Real Economy

The digital economy has infused vitality into the transformation and development of the real economy, urging enterprises to break through core technological barriers, address bottleneck issues, and improve their core competitiveness. It fosters the comprehensive digital transformation of agriculture, manufacturing, and service sectors, improving the dynamism of the real economy and fostering more consumption hotspots. Efforts are underway to enhance industrial supply chains and innovation chains, optimize regional resource allocation, and promote a virtuous cycle within the real economy. Initiatives are being undertaken to standardize the development of digital economic platforms, promote the high-quality development of regional economies, and leverage the advantages of the socialist market economy with Chinese characteristics.

The spatio-temporal pattern and its influencing factors of production efficiency of health resources in China.

There is always a contradiction between the limited health resources and the unlimited demand of the population for health services, and only by improving the productivity of health resources can the health level of the population be improved as much as possible. Using prefecture-level administrative regions as spatial units, the paper analyzes the spatial pattern and changes of health productivity of health resources in China from 2000 to 2010, and uses a spatial panel Tobit model to examine the effects of factors such as technical level of health institutions, health service accessibility, public health policies and ecological environment quality on health productivity of health resources. The results show that with the Hu Huanyong line as the dividing line, the spatial heterogeneity of "high in the southeast and low in the northwest" in the health productivity of China's health resources is clear; as the regional differences narrow, the spatial correlation increases, and the spatial pattern of "overall dispersion and partial agglomeration" becomes more obvious. The fitting results of the spatial Durbin model reveal the direction and degree of influence of local and adjacent factors on the production efficiency of health resources. The positive influence of technical level of local health institutions and the accessibility of health services, the literacy level and the ability to pay for health services of residents in adjacent areas, the degree of urbanization of regional health resource allocation, climate suitability and the quality of the atmospheric environment are significant. And the negative influence of local residents' literacy and ability to pay for health services, the technical level of health institutions in adjacent areas and the degree of medicalization of health resource allocation are also significant. The influence of the degree of medicalization of local health resource allocation and the accessibility of health services in adjacent areas are significantly spatial-heterogeneous.

How can green finance promote the transformation of China's economic growth momentum? A perspective from internal structures of green total-factor productivity

Green financing is a crucial tool for promoting China's economic growth and helping to achieve carbon neutrality, but its implications on the internal dynamics of green economy remain uncertain. This study examines the impacts of green finance on China’s Green Total Factor Productivity (GTFP) and its internal factors, including technical innovation, industrial structure, balanced regional growth, scale, and resource allocation efficiency, by using a three-hierarchy meta-frontier Data Envelopment Analysis (DEA) and provincial panel data from 2008 to 2020. The findings show that: (1) regional green finance development may greatly boost the growth of GTFP, and the findings remain reliable after applying a series of robustness tests; (2) further research finds that green finance enhances GTFP by promoting technological innovation, facilitating the optimization of industrial structure, and improving resource allocation efficiency; and (3) there are significant spatial heterogeneities in this effect. The effect of green finance on GTFP is more pronounced in developed and market-oriented regions. This study helps to understand the pathways of green finance affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

Research on China’s regional carbon quota allocation based on the entropy weight-TOPSIS method and CRITIC-VIKOR model

Research on China’s regional carbon quota allocation based on the entropy weight-TOPSIS method and CRITIC-VIKOR model

A Sustainable Development Study on Innovation Factor Allocation Efficiency and Spatial Correlation Based on Regions along the Belt and Road in China

The level of development of the innovation factor plays a crucial role in supporting the high-quality sustainable development of China’s economy. In order to advance the sustainable development of regional innovation factor allocation efficiency along the Belt and Road this study introduces the super-efficient slacks-based measure (SBM)-data envelopment analysis (DEA)-Malmquist model for static and dynamic analyses of innovation factor allocation efficiency in 17 provinces along the Belt and Road from 2012 to 2021. This study used the Moran index model to analyze spatial correlation. The results show the following: (1) The overall innovation factor allocation efficiency along the Belt and Road is not high, and there are obvious differences among different regions. The eastern region’s efficiency is the highest compared to other regions. (2) According to the efficiency decomposition results, pure technical efficiency (PTE) is the main reason for the low innovation factor allocation efficiency. (3) Through the Malmquist index and decomposition index, it was found that pure technical efficiency (PECH) and scale efficiency (SECH) are key factors in improving technical efficiency (TECH). (4) The analysis of spatial correlation revealed a strong spatial agglomeration feature among the provinces along the Belt and Road. Innovation factor allocation efficiency is mainly manifested in the third quadrant. Finally, drawing on the results of the analysis, suggestions and policies are put forward to improve innovation factor allocation efficiency in the regions along the Belt and Road. This study is of great significance for promoting the sustainable development of the regional innovation level along the Belt and Road in China.

Optimal allocation planning of regional water resources with multiple objectives using improved firefly algorithm

Abstract Population growth and economic development, coupled with water pollution and the frequent occurrence of extreme weather, have led to a growing contradiction between water supply and demand in some regions. To address this challenge, rational and optimal allocation of regional water resources has emerged as a crucial approach. This study focuses on creating a comprehensive model for optimizing regional water resource allocation, taking into account social, economic, and ecological factors. In addition, three innovative modifications are introduced to the firefly algorithm (FA), resulting in the development of the improved firefly algorithm (IFA). The effectiveness of IFA is validated through experiments involving nine benchmark functions. The results highlight the improved search efficiency and convergence achieved by IFA compared to other intelligent algorithms. Moreover, the application of IFA in solving the water resource allocation challenge in Shannxi Province, China, for 2020 and 2021 demonstrates a reduction in the overall water shortage rate to 4.69 and 1.72%, at a 75% guarantee rate. This reduction in water shortages contributes to addressing future scarcities. The proposed allocation scheme offers comprehensive benefits and provides crucial technical support for water resource management. Ultimately, this study offers valuable insights and guidance for addressing the issue of water supply–demand disparities.

COMPARATIVE STUDY OF PRIMARY SCHOOL ADMINISTRATORS' PERSPECTIVES ON INCLUSIVE EDUCATION OF DIFFERENTLY ABLED CHILDREN IN INDIA AND UZBEKISTAN

The purpose of this study is to examine the current state of attitudes and practices of primary school administrators concerning inclusive education in two different countries Delhi, India and Tashkent, Uzbekistan with a comparative cross-sectional research design. The study seeks to establish the perception that the administrators have towards children with disabilities in regular schools as well as the factors that influence the perception. The purpose of the study is therefore to establish similarities and/or differences in the perceptions and practices of administrators from the two culturally and educationally distinct cities with regard to inclusive education. The participants were primary school administrators from public and government schools in Delhi and Tashkent to target the key persons responsible for supporting and coordinating inclusion in the schools. The sample was chosen with 677 male and 453 female administrators and 780 participants from Delhi, and 350 from Tashkent which provides a good mix of the participants’ views from different regions. The data were collected through survey; the questionnaire included questions on attitudes towards inclusion, training received, knowledge of policies in relation to inclusion, support and barriers. When the data was analyzed using SPSS software, it was found that there was a statistically significant difference in attitudes between the administrators in Delhi and those in Tashkent. Even with the similar training frequency in both the cities, the total training results are still unsatisfactory, which shows the requirement for more effective professional development. It also revealed that there were significant differences in the perceived availability of support systems and the challenges that were faced, which show that the regional policies and resource allocation have a big influence on the success of inclusive education. There was a difference in the perception among male and female administrators with the female administrators perceiving a higher impact of inclusive education and identifying more areas of need. These findings underscore the value of the contextualized approaches that take into consideration the particularities of various geographical and population settings.

Surface Water Resource Accessibility Assessment of Rural Settlements in the Yellow River Basin

Analyzing the spatial relationship between humans and water is crucial for regional development and water allocation schemes, particularly in the face of extreme water scarcity in the Yellow River Basin. A quantitative evaluation model of surface water resource accessibility (SWRA) has been developed, with rural settlements serving as the research unit. This model is built upon three key dimensions: topography, distance, and surface water resources within the Yellow River Basin. The results show that: (1) The SWRA range spans from 0.13 to 0.88, with an average value of 0.47 and a standard deviation of 0.05. Higher SWRA values are concentrated in the eastern and western regions, while lower values are predominantly found in the central area. (2) The gradient of SWRA across the 12 catchments, from low to high, is as follows: Sanmenxia station, Lanzhou station, Shizuishan station, Longmen station, Tongguan station, Toudaoguai station, Xiaolangdi station, Huayuankou station, Lijin station, Gaocun station, Ai Shan station, and Tangnaihai station. (3) At the city scale, the SWRA values are generally higher in the eastern areas of 10 cities, with one exception being higher in the west. Conversely, in the western areas of nine cities, the SWRA values are lower. The remaining cities exhibit SWRA values at a medium level. The correlation coefficient between primary industry gross domestic product (GDP) and SWRA is 0.271 (N = 56, Sig = 0.043, in 0.05 level, the correlation is significant), which confirms that SWRA serves as a factor influencing GDP and is appropriately designed for assessing water accessibility. Consequently, managers can utilize SWRA results to make informed decisions regarding regional development and water allocation.