Industrial Economic Development Research Articles

Preface for special issue on Microbial Chemical Factories

Microbial chemical factories utilize engineering design principles to re-build natural production pathways, enabling the precise, quantitative, and efficient synthesis of chemicals. This is achieved through the optimization of synthetic pathways, the reconstruction of biochemical networks, the development of novel components, and the integration of pathways with cellular and environmental contexts. As a transformative approach to chemical production, microbial chemical factories play a critical role in establishing renewable raw material pathways for industrial economic development and advancing sustainable growth. This innovative model has become a strategic priority for technological advancement and industrial competitiveness in developed nations. This industry has expanded into diverse sectors, including pharmaceuticals, food production, chemicals, and energy. To showcase the most recent scientific advancements in the field of microbial chemical production and to promote the evolution of the bio-manufacturing industry, we organized a special issue entitled "Microbial Chemical Factories". This edition features the latest research conducted by domestic scientists, focusing on areas such as the synthesis of material monomers, pharmaceutical intermediates, functional food ingredients, organic acid biosynthesis, and the development and utilization of non-food feedstock. It provides reference and guidance for the further development of microbial chemical factories.

Preface: 4th International Conference on Management Science and Industrial Economy Development (MSIED 2024)

Preface: 4th International Conference on Management Science and Industrial Economy Development (MSIED 2024)

Analysis of the integrated role of the Yangtze River Delta based on the industrial economic resilience of cities during COVID-19

The enhancement of regional comprehensive development ability is significantly impacted by the study on the implementation effect of regional integration strategies. The integration strategy’s impact on urban development during COVID-19 in the Yangtze River Delta(YRD) is unclear. According to prior industrial transfer theory, Hefei, Anhui’s capital, is difficult to transfer industries, and other YRD cities push industry integration in Anhui. This study employs the theory of economic and land resource use to examine the resilience of the industrial economy during an epidemic by using industrial land as a representation of industrial economic development. The three cities in Anhui—Wuhu, Maanshan, and Chuzhou (Wu-ma-Chu) were selected as the research area. The study employed the UNet deep learning method to detect the land use types in Wu-ma-Chu. The land transfer matrix and the standard deviation ellipse were utilised to research the alterations in industrial land use and the spatial distribution of industrial output value, respectively. The results showed that the industrial land in Machu continued to grow during the outbreak, highlighting the resilience of the region’s industrial economy. During 2019–2022, the elliptical ring of industrial output value is distributed in Nanjing, revealing the radiating role of Nanjing in integrating into the integration of the YRD. This confirms China’s YRD integration strategy, strengthens regional economic resilience, and encourages coordinated regional economic development.

Research on the Geographical Pattern, Evolution Model, and Driving Mechanism of Carbon Emission Density from Urban Industrial Land in the Yangtze River Economic Belt of China

To achieve the goals of “carbon peaking and carbon neutrality”, this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the “dual carbon” goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of “dual carbon”, the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation.

House price prediction using machine learning

The role of the real estate industry in economic development and social progress reflects the economic well-being of individuals and regions. With the increase of people's income level, the demand for housing is also increasing. Therefore, making a more accurate house price forecast will help people make the most correct strategy to buy a house when they need it. This study focuses on house price prediction in King County, Washington, a diverse real estate market. Leveraging machine learning models such as linear regression, random forest, neural networks and XGBoost, these supervised learning models are used to delve into house price forecasting. This research includes random forest and XGBoost, are implemented using Scikit-Learn tools. Besides, the Feedforward Neural Network is introduced with the drop out layer in order to reduce the occurrence of model fitting situations. The findings reveal that XGBoost achieves the highest accuracy, making it well-suited for precise price predictions. Additionally, the research identifies grade, sqft_living, and latitude as the three most influential features significantly affecting house prices within the dataset.

Influence of Artificial intelligent in Industrial Economic sustainability development problems and Countermeasures

Economic Sustainability Development (ESD) helps improve the sustainable values needed to conserve resources via optimum use, recovery, and recycling. There should be a direct relationship between countermeasures and the cause of economic losses due to improper design of ESD. Therefore, combining big data and cutting-edge technology may facilitate real-time monitoring, encourage consumers to engage in more sustainable practices and foster the development of industry sustainability. However, countermeasures have unforeseen consequences and tradeoffs that are difficult to predict in ESD. In this research, ESD uses big data to enhance their operations and customer service, develop targeted marketing strategies, and boost sales and profitability. In ESD, Data analytics is being used by human resources to improve decision-making throughout the recruiting process and in evaluating employee performance. In the long run, Artificial Intelligence (AI) adoption may boost productivity and produce new goods, creating jobs and boosting the economy. AI may have a net beneficial impact on ESD. Therefore, ESD-AI helps to overcome the problems by minimizing costs and boosting the economy. AI-integrated ESD helps analyze vast amounts of data, which may increase the speed at which things are done and substantially enhance decision-making. Hence, a balanced approach is essential to guarantee that AI systems can tackle sustainability challenges without adversely compromising other aims to boost the economy.

Exploring Sustainable Supply Chain Management Practice and Environmental Performance: A Systematic Review Perspective

Weather conditions transformation has exacerbated humanity challenges as nations continue to struggle between carbon reduction and rapid industrial economic development. Although, both developed and developing countries reaffirmed their solemn promise to mitigate existing carbon emission, research on sustainable development, eco-friendly, and low-carbon supply chain links remain unstudied. As a result, the study responds to the research interrogation: "Why and in what way are businesses adopting to sustainable strategies to promote sustainable supply chain management (SSCM) in their production?" In response, the researchers obtain and synthesis 19 literature papers for constructive analysis and interpretation from the Scopus database which has the reputation of housing peer-reviewed articles in a broader range of study disciplines. The findings indicate, it is imperative for organization to enhances their SSCM activities such as waste management and re-manufacturing, eco-friendly manufacturing and remanufacturing, logistics in reversal and networking plan, green manufacturing, green purchasing, green operation and low-carbon supply chains. Moreover, to maintain the supply chain operations for the global benefit, businesses must evaluate and acknowledge their primary sustainable risk activities from the previous through to the present, and the forthcoming structural plan.

A Social Network Analysis Approach to Explore the Dualistic Interaction between the Digital Economy and Industrial Economics

Abstract In recent years, the digital economy has continuously innovated the traditional industrial economy and brought about the continuous optimization of economic structure. In recent years, the digital economy has continuously innovated the traditional industrial economy and brought about continuous optimization of economic structure. By combining the AP clustering algorithm, this paper creates a representative viewpoint extraction model that extracts the relevant features of relevant variables and generates a more representative economic viewpoint. The social network structure between the digital economy and industrial economics is analyzed using the social relationship graph. Using the information gain calculation formula, the correlation calculation is carried out on the characteristics of variables with stronger relationships and larger information gain. Meanwhile, the correlation coefficient between variables with larger information gain is calculated by Spearman’s coefficient. The influencing factors of industrial economic development under the digital economy are analyzed through three dimensions, and the theoretical model of group effect analysis is constructed to analyze the binary interaction between the two. Through the method of empirical analysis, the interaction between the digital economy and the industrial economy is tested in terms of smoothness and cointegration. HP filtering, as well as impulse response analysis, are carried out to analyze the interaction between the two in A. After 9 groups of experiments, the cointegration number of the original hypothesis is 0 or ≥1, the original hypothesis is rejected at a significance level of 1%, and the eigenvalues range from 67.4566 to 69.7445, and there is a correlation between the two. The impulse response value of the industrial economy improves from 0.0002 to 0.001. The development of the digital economy will lead to the development of the industrial economy.

Research on the Integration of Artificial Intelligence-driven Industrial Economics and Technology Industry Incubation

Abstract The development mode relying on the traditional factor dividend has become unsustainable, and the integration and application of artificial intelligence technology can promote the high-quality development of science and technology industry incubation, and it brings more space for the development of the science and technology industry economy. This paper firstly discusses how artificial intelligence predicts economic trends, optimizes the production process, and automates decision support systems through machine learning models. By analyzing how AI processes large amounts of economic data, identifying market patterns, and evaluating the value of investment projects in future markets, it is able to assess the value of investment projects in future markets. Aiming at the shortcomings of the original K-Means clustering algorithm, the method of determining the initial clustering center and the method of automatically determining the K-value are investigated so as to realize the automatic clustering of industrial economic development data. From the empirical analysis, it can be seen that the regression coefficients of the interaction term Treatit × Yearit in columns (1) and (2) are all significantly positive at the 1% level. The cluster analysis also visualizes both the types and levels of enterprises in the economic development in a more intuitive way, which shows that the AI model can drive the development of the industrial economy and has an irreplaceable position in the process of technology industry incubation.

Research on the Construction of Public Cultural Space of Changxindian Historical and Cultural Town under the Background of Urban Renewal

As a famous town located in the west of Beijing with a long history of thousands of years, Changxindian is currently facing a host of difficulties such as backward industrial economic development, a chaotic living environment, and a sharp decline in urban vitality. In addition, public cultural space, serving as an important place for residents to conduct leisure activities, is indispensable in improving residents’ quality of life, stimulating urban vitality, and other aspects. In this regard, by combining the protection and renewal of the old town with the redevelopment of the public cultural space, this research deeply investigates the problems exposed by the constructed public cultural space within the old town, the characteristics of spatial evolution as well as relevant influencing factors through field research and statistical analysis. Meanwhile, combined with residents’ vision and master plan, this research puts forward corresponding promotion strategies and recommendations for diverse types of public cultural spaces, with a view to providing a valuable decision-making basis for further exploring how to effectively utilize the existing urban cultural resources in old towns and to mend and promote urban public cultural spaces with regional characteristics..

Research on Industrial Economic Development and Electricity Price Adjustment Strategy Based on Multi-Agent Game

With the deepening of the electricity market reform and the accelerating transformation of the new power system, the number of new electricity customers in the market with local development characteristics has increased. The local industrial and economic development have been affected by the ability to guide electricity prices. In this paper, using the multi-agent game based on exploring the impact of electricity price on the industrial economy, the specific optimization scheme of electricity price adjustment is proposed with the aim of improving the overall efficiency of the power grid and reducing the cost of electricity for industrial users. After the game, the overall efficiency of the electricity supplier will be increased by about 3.06 percent, and the cost of electricity used by various special industries will be reduced by about 6.86 percent to 4.48 percent. The win-win situation of the electricity suppliers’ income and the featured industries’ development can be achieved by the optimization results. As well as the cost of electricity consumption in featured industries can be reduced, and the comprehensive benefits of electricity suppliers can be improved by using the electricity price adjustment scheme after game interaction, which promotes the rational use of energy and meets the current social requirements for the green and sustainable development of the electricity industry.

Economic development of the Russian manufacturing industry under sanctions

The article presents a study to assess main indicators of efficiency of production process development in the manufacturing industry of the Russian Federation in recent years, related to the negative impact of the COVID-19 pandemic on industrial production and on manufacturing in general. The purpose of the study is to examine the level of manufacturing industrial production development in the Russian Federation under the conditions of sanctions. To achieve this goal, international and domestic experience of manufacturing industry economic development has been studied, which in general terms characterizes the level of competencies required for manufacturing industries effective development. A comparative assessment of such approaches has been carried out. The study used the summary and grouping methods, tabular and graphical methods of information presentation, dynamics analysis methods. The information base of the study was microdata of sample surveys of the Federal State Statistics Service. The indicators have been presented in annual periodicity for 2016–2022 for Russia. As a result of studying economic development of manufacturing industry types, their pros and cons have been established. On the basis of statistical data and sample surveys for 2022, their systematization and evaluation have been carried out. The changes that occurred in main economic indicators characterizing the manufacturing industry sphere development have been studied. The study pays attention to the indicators characterizing industry development in Russia. The article concludes that in the future it will be necessary to continue the manufacturing industry transformation on an innovative basis.

Role of Construction Industry in Economic Development: Issues and Challenges

India as one of developing economy is thriving hard across sector to have all round development. With several economic sector that are grouped under primary, secondary and tertiary – giving their best efforts to increase productivity efficiently and effectively which in turn increase employment and contribute towards GPD. However, of various economic sector construction sector is one of most active industry that provide employment to the major population. As it is more of labor intensive work, it attracts several migrant workers, labors (skilled and unskilled) towards it – making it very second after agriculture sector in providing employment. However, construction sector encounters lot of challenges, as it involves the element of Human work, Heavy Machinery, Huge Investment followed by confrontation of lot legalities on its way of completing the construction projects. Construction sector falls under unorganized sector makes it difficult to follow a systematic way of functioning and operating.The purpose of this paper is to understand the issues and challenges faced by Construction Industry and suggest possible measure to overcome or prevent the same. The paper is based completely on secondary data and conceptual in nature. It tries to highlight the hindrances confronted in this industry and analyze the situation that may have impact for the growth of construction sector.

Analysis of Factors Influencing the Development of China's Insurance Industry

The insurance industry is closely linked to individual interests and the overall economy of the country. Nowadays, in the context of Covid-9, the stable development of the insurance industry is particularly important. However, much of the literature focuses on the role of the insurance industry in economic development, but there are few studies that focus on the industry in general and analyze the impact factors of the insurance industry itself from multiple perspectives. To fill the academic gap in the overview of the insurance industry and better promote its future development, this paper explores the role of seven factors such as economic growth, inflation, disposable income of the population, and the scale of social security on the development of the insurance industry from three aspects: macro, micro, and China-specific social background conditions. Through a comprehensive analysis of relevant domestic and international literature in recent years, this paper concludes that: economic growth, higher individual disposable income and better legal system and regulation have a positive effect on the development of the insurance industry; inflation inhibits the insurance industry development. The effects of demographics, social security size and residents' education level on Chinas insurance industry are somewhat complicated.

Совершенствование инструментов муниципального контроля в системе управления развитием экономики промышленности города

The article serves an introduction to the improvement of municipal control tools in relation to the problems of industrial economic development at the city level. A diagnostic is proposed that determines the need for inten-sive improvement of municipal control tools in the city’s industrial management system. Improved tools include control of legal employment registration, control of the budget process, procurement financing and debt man-agement of the municipality’s budget, control of natural, man-made, biological-social and other risks, control of passenger transportation safety, control of accessibility of vital and socially important objects of the city, transport control. On the example of the cities of the Southern Federal District of Russia, the need for the im-plementation of industrial policy to combine the observance of the principles of municipal and public partner-ship with the systematic modernization of public utilities and the entire life support infrastructure is substantiat-ed.

Study on fuzzy comprehensive competitiveness evaluation of urban exhibition industry with hesitant fuzzy information

With the development of socialist market economy, the exhibition industry has emerged as the tertiary industry matures in a globalized economic environment. As a new economic form, the exhibition economy presents new opportunities for economic development. The research on the exhibition industry at home and abroad has been relatively mature, and there has been a scientific analysis of the industrial linkage effect of the exhibition industry. The strong industrial linkage effect has made the exhibition industry occupy a very important position in the economic development of cities. However, in the development of China’s urban exhibition industry today, it is no longer a simple question of developing and enhancing the strategic position of the exhibition industry in economic development, but rather a question of how to enhance the competitiveness of China’s urban exhibition industry. Only when the level of competitiveness is improved can the economic and social benefits brought by the exhibition industry be brought into full play. The fuzzy comprehensive competitiveness evaluation of urban exhibition industry is a classical multiple attribute decision making (MADM) problems. Recently, the TODIM and VIKOR method has been used to cope with MAGDM issues. The hesitant fuzzy sets (HFSs) are used as a tool for characterizing uncertain information during the fuzzy comprehensive competitiveness evaluation of urban exhibition industry. In this manuscript, the hesitant fuzzy TODIM-VIKOR (HF-TODIM-VIKOR) method is built to solve the MADM under HFSs. In the end, a numerical case study for fuzzy comprehensive competitiveness evaluation of urban exhibition industry is given to validate the proposed method.

On Strategic Emerging Industry Cluster Development in Anhui based on the Perspective of Global Value Chain

With the development of economic globalization, the role of strategic emerging industries embedded in global value chains (GVCs) as clusters to actively participate in the global industrial division of labor has become increasingly significant. The present situation and problems of strategic emerging industry clusters in Anhui are analyzed qualitatively from three aspects: dynamic mechanism, development mode and governance mode, and their status in GVC is inferred quantitatively by using GVC index. Secondly, Bengbu silicon-based new materials industry is used as an example for empirical research, and the GEM model and multiple linear regression model are used to build a data evaluation system and analyze the factors affecting the competitiveness of industrial clusters. Finally, we propose a scientific and reasonable upgrading path and policy suggestions based on GVC perspective, which can provide guidance and reference significance for promoting regional industrial economic development.

Wind energy, industrial-economic development and CO2 emissions nexus: Do droughts matter?

This study empirically explored the nexus of wind energy (with regards to the effect of the drought), industrial-economic development, and emitted CO2 in 41 World's top countries in wind energy consumption from 1997 to 2018. Cross-sectional augmented distributed lag estimators (CS-DL, CS-ARDL, CCE-P) and newly updated estimation packages to effectively assess the relationships between variables. Our results are the following: First, severe droughts were not a significant matter in wind energy, and consuming wind energy reasonably contributes to reducing emitted CO2, while industrial and economic development positively promotes CO2 emissions in sampled countries. Second, industrial development significantly promotes economic growth, while wind energy use has an insignificant positive effect on economic growth. Moreover, wind energy negatively affects industrial development. Third, two-way directional causal relationships were noted between CO2 and other covariates, this hypothesis was also noted between industrial development and economic growth and wind energy use. We, therefore, suggested policy implications to reduce CO2 across the globe and country-specific and consider the positive effect of wind energy on growth.

Analysis of Inequality Levels of Industrial Development in Rural Areas through Inequality Indices and Spatial Autocorrelation

To achieve a balanced and sustainable rural development pattern, this study used the Theil index, Gini coefficient, and Spatial Autocorrelation method to analyze the inequality of industrial economic development between rural areas in South Korea. The results showed that considering the whole of South Korea, the inequality in industrial economic development level among rural areas was reasonably balanced, and the inequality level showed a trend of narrowing. Considering the first-level regions, the levels of inequality varied. The economic development level of the rural areas around the Capital Area and Metropolitan Cities was higher than that of other rural areas, and policies should be established to support the economic development of other rural areas.

Wildlife resource conservation and utilization for achieving sustainable development in China: main barriers and problem identification

The rapid growth of the industrial economy has affected the survival of wildlife, and the decline in wildlife resources will in turn have some negative impact on the industrial economy. For the sustainable development of the industrial economy, human beings began to reflect on traditional development thinking and strive to find a development strategy that harmonizes industrial economic development and resource protection, and wildlife protection gradually attracted people's attention. "Protecting wild animals, maintaining ecological balance, and promoting economic development" has become a hot topic in the new century. Wildlife resources are valuable natural resources and play an important role in the ecosystem, which is related to the well-being and future of human beings. In recent years, China has made great progress in wildlife protection, while protecting and expanding wildlife habitats, introducing relevant laws and regulations, and other measures which have been implemented recently. However, there are still shortcomings in the protection of wildlife in China. Over-utilization, habitat loss and degradation, environmental pollution, climate change, weak legal awareness, and indiscriminate hunting all pose serious threats to wildlife in China. In this regard, this paper summarizes the main problems and barriers to wildlife resource conservation and utilization in China. Based on the analytic hierarchy process (AHP), the main technology factors influencing wildlife resource conservation and utilization in China are identified. Finally, the future research development direction of wildlife conservation is discussed based on the critical factors. This can provide some guidance for developing wildlife resource conservation and utilization for a sustainable ecosystem in China.