Regional Economic Development Research Articles

Gender Role Dynamics in Economic Development: Challenges and Opportunities for Women's Empowerment

The role of gender in economic development has become a major concern in the context of women's empowerment. This article investigates those dynamics with a focus on the challenges and opportunities faced in women's economic empowerment efforts. Through a comprehensive review of the literature, we explore the role of gender in economic development, explain the various challenges women face in access and control of economic resources, and identify opportunities to increase their empowerment. We also discuss the impact of gender roles in the context of global and regional economic development.

Big data analysis technology in regional economic market planning and enterprise market value prediction

Abstract Market planning for regional economic development is a crucial task connected to stability and systematicness and influences the unique outcomes of regional economic growth. As a result, market planning for regional economic development must be given more weight. There are several issues with regional economies currently developing in many parts of our country. Lack of focus on market planning for regional economic growth results in several flaws in market planning, making it challenging to support sustainable development. The accurate analysis of diverse massive economic datasets has significant research value. The aim of this study is to provide an overview of market planning and regional economic and industrial development, analyze the effects of market planning on regional economic and industrial development, identify issues with market planning and regional economic and industrial development, and suggest solutions. This article employs big data analysis technology to forecast corporate market value and develop regional economic markets. The system is employed to conduct experimental big data analysis within a specific field for an extended period. According to test analysis results, the system’s data analysis accuracy can reach up to 95.8%, which has a promising future for use.

Research of multimodal transport potential of major cities in China based on the satellite remote sensing

Abstract. By two or more modes of transportation to connect with each other and complete the transport process, multimodal transport could significantly improve transport efficiency, reduce costs, while promote energy conservation and emission reduction, compared with the traditional single mode of transport. Therefore, the multimodal transport development reflects the level of national or regional economic development to some extent. In this study, multimodal transport potential index was built to evaluate the possibility of multimodal transport. Remote sensing images from satellites were used to extract roads, railway stations and airports. A method was proposed to derive the road-rail transport potential index and road-air transport potential index, and then for the analysis of multimodal transport potential in 36 cities. Results show that there is a big gap among 36 cities on the development potential of road-rail and road-air transport. Compared with the road-rail transport potential index, the distribution of road-air transport potential index is more consistent among and within the seven regions. Index values of megacity and super cities are much higher than type I and II big cities. Moreover, in the 36 cities, there is a positive correlation between the multimodal transport potential index and GDP. The research results could be used to quantitatively evaluate the development of transport infrastructure, consequently provide more solid and reliable basic information for the planning, design and scheme adjustment of multimodal transport, thus comprehensively improve the efficiency and quality of multimodal transport, serve the territorial spatial planning.

The Influence of Natural Resources, Energy Consumption, and Renewable Energy on Economic Growth in ASEAN Region Countries

This research aims to identify and analyze the role of natural resources, CO2 emissions, and renewable energy on the economic growth of countries in the ASEAN region. In this study, we tested whether a dynamic process occurred based on a dynamic panel data model while comparing it with static panel data. The dataset used is ASEAN region countries with time series data from 2000-2021. The analysis tools used are static and dynamic panel data. The research results found that natural resources, FDI, and renewable energy significantly positively affect economic growth in the ASEAN region. Conversely, CO2 has a negative and insignificant effect. These results prove that the ASEAN region's economic development has been clean energy-oriented.

Integrated Supervision Center of Huaihua International Inland Port: The Feasibility and Essentiality

Building an integrated supervision center in Huaihua is feasible and essential because Huaihua City is at the center of the border regions of Hunan, Hubei, Chongqing, Guizhou, and Guangxi. In addition, it is a national transportation hub in China because of its distinctive geographic location, abundant resources and labor force. Due to the development of Huaihua International Inland Port, Huaihua has an excellent opportunity to be a logistics and trade center for inland areas in Central China. Given considerations in national strategies, food security, economic development and other factors, an integrated supervision center can be built in Huaihua, as it can promote the connectivity of the Wuling Mountain area and the neighboring provinces, contribute to regional economic development, and enhance China’s national security and supervisory capacity. The development of Huaihua as an integrated supervision center facilitates the processing, bonded warehousing and logistics distribution of high-quality imported commodities from neighboring countries, especially ASEAN countries.

Research on Green Process Innovation Enabling the Synergistic Effect of Pollution Reduction and Carbon Reduction

Achieving the objective of "peak carbon dioxide emissions and carbon neutrality" in the new stage of development will require the synergistic effect of pollution reduction and carbon reduction. In the new stage of development, achieving the goal of "peak carbon dioxide emissions and carbon neutrality" will necessitate the synergistic effect of pollution reduction and carbon reduction. This study assesses the degree to which pollution reduction and carbon reduction have a synergistic effect using the coupling coordination model, and uses the fixed effect model, the dynamic panel GMM model, the OLS model and the threshold effect model to examine how green process innovation affects pollutant reduction and carbon reduction synergistically, including direct, heterogeneous, and nonlinear effects. The results show that: firstly, green process innovation has a direct promoting effect on synergistic effect of pollution reduction and carbon reduction; Secondly, due to the differences in the economic development of different regions in China, the impact of green process innovation on the synergistic effect of pollution reduction and carbon reduction is heterogeneous in different regions, and presents a gradient distribution of "east > west > middle". Finally, there is a threshold effect in the impact of green process innovation on regional synergistic effect of pollution reduction and carbon reduction. This paper provides some reference value for promoting green process innovation and enhancing the collaborative impact of mitigating pollution and decreasing carbon emissions.

Research on Training Model of English Talents under the Background of New Liberal Arts

Under the background of the construction of the new liberal arts, local application-oriented universities should explore the inter-disciplinarity of foreign language courses and application-oriented professional courses in combination with school-based characteristics and talent training objectives, and establish interdisciplinary curriculum groups. The model proposed in this paper combines the instrumental goal of improving students' language foundation and cross-cultural ability with the humanistic goal of cultivating students' independent learning ability, critical thinking ability and cultural accomplishment, so as to enable regional economic and social development.

Spatial Spillover Effects of Urbanization on Ecosystem Services under Altitude Gradient

Rapid urbanization has made mountain development an important means to alleviate the shortages of construction land on plains, which has significantly affected regional ecosystem services. In-depth research on the impact of urbanization on ecosystem services under altitude gradients is of great significance to clarify the relationship between the two. Based on data from 2000, 2010 and 2020, the urbanization level and ecosystem services of the study area were evaluated. The spatial correlation of ecosystem services was analyzed by Moran’s I. A spatial Durbin model (SDM) was selected to fit the regression. The results show that (1) from 2000 to 2020, the ecosystem services in the study area displayed obvious regional characteristics and aggregation characteristics; (2) in plain areas, the indirect effects of economic, population and land urbanization have a greater negative impact, and compared with shallow mountain areas, deep mountain areas are more negatively affected by economic urbanization and land urbanization; and (3) the significant difference in regression results reflects the rationality of using the spatial Durbin model, as in this paper, and proves the scientific nature of regional coordinated development. The research results provide a reference for the future coordinated development of regional economies and environments.

Impact of green technology innovation on the quality of regional economic development

This study examines the effects of green technology innovation on regional economic development and its heterogeneity by using Chinese interprovincial panel data (2010–2020), and analyses the impacts of spatial effect and mediating effect. Green technology innovation can significantly contribute to regional economic development. From a spatial perspective, green technology innovation in surrounding provinces can inhibit regional economic development. Based on intermediary effects, green technology innovation can aid regional economic development by promoting industrial structural transformation, optimizing the energy consumption structure, and enhancing green total factor productivity.

Exploring the dynamics of urban energy efficiency in China: A double machine learning analysis of green finance influence

Analysing the impact of green finance policies on urban energy efficiency contributes to finding solutions to promote the development of China's low-carbon energy system and the global reduction of greenhouse gas emissions. Utilizing Chinese urban data from 2006 to 2021, the study employs an enhanced non-radial distance function (NDDF) model to evaluate the energy efficiency of 282 prefecture-level cities. It examines the 'Green Finance Reform and Innovation Pilot Zone' policy as a quasi-natural experiment. It uses a double machine learning model to analyze its effect on urban energy efficiency and its mechanisms. The research demonstrates that green finance policies significantly improve energy efficiency, mainly through strengthening environmental regulation, fostering green technology innovation, and optimizing industrial structure. Additionally, an in-depth analysis of regional heterogeneity reveals variations in the policy's effectiveness across eastern, central, and western regions and between resource-rich and resource-poor cities. The findings suggest that the efficacy of green finance policies, while generally positive, is influenced by regional economic development and resource endowment differences. The study suggests targeted strategies to improve the green finance system, customize policies according to regional specifics, incentivize corporate green innovation, and foster cross-sectoral collaboration. By offering novel insights into sustainable development and providing actionable policy recommendations, this research contributes to advancing Chinese urban centres' economic and environmental sustainability through the strategic application of green finance.

Assessing the Economic Impact of Coffee Farming on Rural Communities in Colombia

Purpose: The aim of the study was assessing the economic impact of coffee farming on rural communities in Colombia Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Assessing the economic impact of coffee farming on rural communities in Colombia reveals significant findings. Coffee farming is a major source of employment and a primary contributor to household income in these areas, supporting the economic stability of numerous families. Moreover, the coffee industry’s demand for labor not only boosts local employment rates but also contributes to regional economic development through the generation of export revenues. Unique Contribution to Theory, Practice and Policy: Dependency theory, livelihoods approach & dual economy model may be used to anchor future studies on assessing the economic impact of coffee farming on rural communities in Colombia. Implement CBPR methods to involve coffee farmers in the research process, ensuring that their firsthand experiences and insights inform the study. Advocate for policies that support fair trade practices.

Differences in tourism economic development and its influencing factors among three major city clusters along the middle reaches of the Yangtze River.

An in-depth study of the mechanisms governing the generation, evolution, and regulation of differences in tourism economics holds significant value for the rational utilization of tourism resources and the promotion of synergistic tourism economic development. This study utilizes mathematical statistical analysis and GIS spatial analysis to construct a single indicator measure and a comprehensive indicator measure to analyze tourism-related data in the research area from 2004 to 2019. The main factors influencing the spatial and temporal differences in the tourism economy are analyzed using two methods, namely, multiple linear regression and geodetector. The temporal evolution, overall differences and differences within each city group fluctuate downwards, while the differences between groups fluctuate upwards. Domestic tourism economic differences contribute to over 90% of the overall tourism economic differences. Spatial divergence, the proportion of the tourism economy accounted for by spatial differences is obvious, the comprehensive level of the tourism economy can be divided into five levels. The dominant factors in the formation of the pattern of spatial and temporal differences in the tourism economy are the conditions of tourism resources based on class-A tourist attractions and the level of tourism industry and services based on star hotels and travel agencies. This study addresses the regional imbalance of tourism economic development in city clusters and with the intent of promoting balanced and high-quality development of regional tourism economies.

Analisis Rasio Biaya Dana Pada (Studi Kasus) Laporan Keuangan PT BPD Jawa Timur

The role of banking currently has enormous power in the financial system, and has even become a key element in driving a country's economic progress. Banking institutions are business entities that operate in the financial sector or provide financial services. One form is the Regional Development Bank (BPD), which is owned by the provincial or district/city government of Indonesia. Fundamental role as a supporter of regional economic development by providing financial and banking services. BPD East Java is an example of a Regional Development Bank owned by the East Java Provincial Government. This research focuses on analyzing the financial reports of BPD East Java from 2020 to 2021

Labor Mobility Networks and Green Total Factor Productivity

Population migration continues to reshape the spatial pattern of China’s population and regional economic development. During this internal migration process, production and consumption patterns often change, ultimately leading to changes in green total factor productivity. This paper, based on the Chinese population census data and 1% sampling survey data from 2005 to 2015, utilizes social network analysis methods to measure the labor mobility network indicators of 284 prefecture-level cities. Further, this paper analyzes the impact and mechanisms of regional network status on green total factor productivity using a panel fixed effects model. We find that as network density increases, the interpersonal connections between regions become closer, and the network exhibits a clear pattern of “concentrated inflows” and “dispersed outflows”, with the trend of forming strong alliances becoming increasingly apparent. Regions positioned centrally either in terms of network in-degree or out-degree exhibit higher green total factor productivity. Among these, the labor mobility network plays a crucial role in enhancing green total factor productivity through the channel of technology diffusion effects, which improve investment efficiency via knowledge exchange and material capital accumulation. The promotive effect of labor network status on green total factor productivity is more pronounced in the eastern regions, where talent quality is higher, and in areas with fewer restrictions from the household registration system.

Evolution of rates, patterns, and driving forces of green eco-spaces in a subtropical hilly region

Monitoring ecological resource change in mountainous and hilly areas (MHAs) is vital for theoretical and practical advancements of ecological resource utilization and management in complex ecosystems. The factors driving structural and functional changes in green eco-spaces (GES) in these areas are complex and uncertain, with notable spatial scale effects. However, analyzing the multi-scale driving mechanisms of ecological and socioeconomic factors at a fine spatiotemporal scale presents significant challenges. To address these challenges, we analyzed dynamic changes in GES and eco-socio-economic development in Shanghang County, a typical mountainous region in southern China. We used multiple linear regression and multi-scale geographically weighted regression model to identify key factors driving GES changes and their multi-scale effects at both global and local levels. Over the past two decades, the GES area in the study area has exhibited a consistent pattern of decline, characterized by phases of gradual decline (2000–2005), sharp decline (2005–2009), slow decline (2009–2019). Key global factors driving GES changes included elevation (ELE), slope (SLOPE), population density (PD), distance to settlements (SETTLE), and distance to administrative centers (ADMIN). These factors exhibited significant spatial heterogeneity and multi-scale effects on GES changes. Specifically, SETTLE, PD, SLOPE, and ELE consistently drove GES changes at the local level, while ADMIN only showed significant localized effects during 2005–2009. The synergy between SETTLE and SLOPE had a considerable impact on GES changes, increasing over time, whereas ELE and PD demonstrated a consistent trade-off effect. These findings provide detailed spatiotemporal insights into the driving mechanisms of natural ecological resources, offering crucial guidance for environmental management, land source management, regional economic development, and biodiversity conservation in Shanghang and analogous subtropical hilly regions worldwide.

Research on the Coordinated Relationship between Sewage Resource Utilization and Economic Research on the Coordinated Relationship between "Dual-cycle" Wastewater Resource Utilization and Economic Development

Dual-cycle wastewater resource utilization is aimed at improving the utilization rate of water resources and reducing the discharge of urban wastewater in order to increase the utilization rate of natural resources and achieve the circular utilization of water resources during urban development. Based on the dual-cycle concept, this study aims to explore the coordination between wastewater resource utilization and economic development in China, and understand the impact between the two. Literature research and data analysis are mainly used to analyze data from different provinces in China, making the research practically valuable. Through the analysis of data from five different provinces, it is found that the better the economic development of a province, the higher the importance attached to wastewater resource utilization. However, due to the impact of rapid economic development, the efficiency of wastewater resource utilization shows a slow trend. Conversely, inland provinces that attach importance to wastewater resource utilization, despite some shortcomings in economic development, have strong potential for economic development, which reflects the coordination between the two. The overall coupling degree between wastewater resource utilization and economic development in China is in a stable growth trend, showing a primary level of coordination. To achieve advanced or even superior coordination, further research on the coordination between wastewater resource utilization and economic development based on the dual-cycle concept is needed. This research aims to provide reference value for improving the coordination between wastewater resource utilization and economic development and discover the relationship between the two under different economic development conditions, where regions with higher economic development efficiency have higher wastewater resource utilization rates, but there is no obvious coordination. Therefore, the research focuses on studying the coordination between wastewater resource utilization rates and economic development in different economic development regions, innovating the content of coordination research.

Hot spots, evolutionary trends, and future prospects for the sustainable development of the marine economy in the past 30 years: a comparative bibliometric analysis based on CiteSpace

How to assess the quality of sustainable development is an important issue for the marine economy. This study examined studies on sustainable development of marine economy over the past 30 years using core databases from China National Knowledge Infrastructure and Web of Science. This study introduced bibliometric analysis methods and CiteSpace software to track and comparatively analyze the hotspots of studies from 1994 to 2023. This study showed that (1) the research on sustainable development of the marine economy has achieved extensive results. Researchers have already collaborated with those in China. (2) Hotspots for Chinese research are mainly focused on building an indicator system of marine economy's sustainable development, realizing the path of sustainable development of regional marine economy, and planning the sustainable development goals of specific marine industries. In contrast, other countries focus on protecting marine ecology and identifying the path of sustainable development of the marine industry. (3) Strengthening exchange and cooperation between institutions and scholars from various countries, and further studies on the micro-paths of blue carbon sinks, marine ecological civilization and high-quality development, low-carbon development of marine industries will become new hotspots for research.

Investigating the impact of artificial intelligence development on water pollution in China

Analysing the impacts of AI development on water pollution is of great significance for improving water environment management measures and promoting global sustainable development. In this study, macro and micro panel data of China from 2008 to 2019 were used to measure the development level of AI at the industry and provincial levels in China, and a panel data regression model was constructed to analyse the effects of AI development on water pollution and regional heterogeneity. The measurement results show that the development level of AI is increasing. Among the six industries, the intelligence level of the manufacturing industry has developed the fastest, by approximately 48.74 times compared with the baseline. At the provincial level, Guangdong Province made the greatest progress in intelligence level, increasing by approximately 23.6 times. The regression results show that AI technology is helpful in reducing the level of water pollution, and this conclusion remains valid after the regression of instrumental variables and robustness testing. In terms of regional heterogeneity, AI technology can significantly reduce the degree of water pollution in eastern and western China. However, the development of AI technology in the central region has no significant impact on water pollution, and a risk of increasing the degree of water pollution exists. The reasons may be that the eastern region has high levels of economic vitality and technological innovation and a strong ability to transform AI achievements, which can significantly improve the water environment. Industrial support policies in the western region are strong, and the application of AI can quickly improve production methods and significantly reduce water pollution levels. In comparison, the levels of economic development, technological innovation, and policy support in the central region need to be strengthened, so the environmental effect of AI is not significant.

Dynamic and spatial approaches to assess the impact of geographical indications on rural areas

The paper explores the role of Geographical Indications (GIs) in promoting the economic development of European regions. We consider all NUTS3 regions of Italy, France, and Spain between 1993 and 2014, and 728 GIs.. Our research aims to empirically assess the impacts of GIs on labor productivity and employment, for the agricultural and industrial sectors. We rely on a dynamic panel model and considere the spatial variation of the data. The main results show that GIs generate a positive impact on employment, both in the short and the long-run. Moreover, we find that the impact of GIs is not limited to the province where they are produced, but also triggers sizable spillover effects. Our results have important policy implications for further economic research.

Modelling and assessing new SME digital business status for visualising virtual economics and sustainability economic indicators: Empirical evidence from poultry business

SMEs are generally recognised as financial contributors to regional economic development. Despite the enormous contributions of digital SMEs to sustainable economic growth and regional development have not yet been reported. This paper assesses and models SME businesses to gain a digital business status and model. These days, visualising economic growth is challenging and powerful to identify business performance and realise sustainable regional development. This research analyses empirical data obtained from a poultry business to form a standard model for implementing a new SME digital business model and status. This standard model is a guideline to measure the other SME businesses and productions. Localisation of the SDGs was analysed using thematic analysis. Mathematical computation is used to visualise virtual economic growth geographically. Hence, our digital business model and status demonstrated business performance, management, and economic growth.