Level Of Industrial Development Research Articles

Формирование трудового потенциала и его компонентов с позиции цифровой трансформации и технологического суверенитета в Арктической зоне РФ

One of the key challenges in achieving sustainable regional development is the effective utilization of labor potential within a territory. Major disparities in labor potential are observed across regions, driven by factors such as natural and climatic conditions, demographic trends, varying levels of industrial and transport infrastructure development, and government benefits. This issue is particularly pronounced in the Russian Arctic, a region of strategic importance to Russia. In the context of digital transformation, technological sovereignty, depopulation, and migration outflows, there exists a strong correlation between labor potential and workforce availability in these territories. The development of this macro-region necessitates a well-structured human resource strategy. This study aims to develop and test a methodology for forecasting labor potential levels in the context of digitalization and technological sovereignty, using data from regions within the Russian Arctic. The methodology comprises three stages: (1) identifying determinants and collecting relevant statistical data, (2) compiling a forecast data set based on dynamic series and calculating indices, and (3) utilizing a matrix framework to evaluate and rank territorial performance based on specified criteria. The study employs methods such as comparison, grouping, forecasting, visualization, and matrix techniques, as well as correlation and cluster analysis. Its scientific novelty lies in redefining the concept of "labor potential" within the framework of digitalization and technological sovereignty, and in creating a new typology of regions based on labor potential levels.

The spatial differentiation mechanism of intangible cultural heritage and its integration with tourism development based on explainable machine learning and coupled coordination models: a case study of the Jiang-Zhe-Hu in China

As a vital carrier of traditional culture, Intangible Cultural Heritage (ICH) not only preserves historical value but also fosters cultural identity and confidence. This study utilizes explainable machine learning and coupled coordination models to analyze the spatial distribution and formation mechanisms of ICH resources in the Jiangsu-Zhejiang-Shanghai (Jiang-Zhe-Hu). The results indicate that (1) ICH resources in the Jiang-Zhe-Hu exhibit a clustered distribution pattern characterized by “three primary cores and two secondary cores.” The primary core areas are Shanghai, Hangzhou, and Suzhou, while the secondary core areas are Yangzhou and Nanjing. (2) Population, number of religious places, and GDP have a significant positive impact on the distribution of ICH in the Jiang-Zhe-Hu. NDVI and road mileage have relatively minor effects on ICH distribution. (3) In terms of ICH resources, Zhejiang Province overall has a higher level than Jiangsu Province, with Lishui having the highest evaluation value and the most abundant resources. Regarding the level of tourism industry development, Shanghai has the highest comprehensive evaluation value, followed by Suzhou, Nanjing, Hangzhou, Wuxi, and Changzhou, all of which have relatively high levels of tourism development. (4) According to the coupled coordination model analysis, Shanghai demonstrates the best coupling degree between ICH resources and the tourism industry, achieving a good coordination level. In Jiangsu Province, the integration of ICH resources and the tourism industry is relatively better in the southern (e.g., Nanjing, Suzhou), but there are still imbalances in development in the northern. Zhejiang Province has an overall higher degree of integration between ICH and the tourism industry compared to Jiangsu, with more balanced development. However, there is still room for improvement in the deep integration of ICH resources with the tourism industry.

The impact of sanctions on the structure of foreign trade in medical devices: Evidence from the medical consumables market

Subject. The article investigates the level of health care and medical industry development in Russia. Objectives. The aim is to assess the impact of sanctions on the structure of foreign trade in medical devices, analysis of import, export and production of medical syringes in Russia for the period 2013–2023. Methods. The study employs the content analysis, comparative analysis. Results. The study found that the volume of consumption of disposable syringes changed slightly, but the sanctions had an impact on the structure of imports. China increased its market share by 32% due to a decrease in supplies from Germany, other European countries, and the United States. The cost structure of imports differs from the structure in physical terms: only three largest manufacturers in Germany import 80 % of needles to Russia. Negative balance of foreign trade is observed - the volume of syringe exports from Russia is only 2% of imports. The volume of disposable syringe production in Russia in 2023 decreased by 26% (to 724 million units). Conclusions. The development of foreign trade in medical devices is hindered by such factors as the raw material problem and imbalance of tax benefits and support measures. To increase the sustainability of the Russian medical industry, it is necessary to localize raw materials and create a register of medical polymers.

Energy transition policy, technology innovation and sustainable manufacturing

This study examines the impact of China's New Energy Pilot City Policy (REPCP) on green development in the manufacturing sector, focusing on the role of technological innovation. Using a Difference-in-Differences (DID) approach with firm-level data from 30 Chinese provinces and cities (2000–2021), the research analyzes how the policy affects firms' adoption of sustainable manufacturing practices. The findings reveal that the REPCP significantly promotes green development, particularly in regions with moderate levels of industrial development. Moreover, technological innovation amplifies the policy's positive impact, indicating a synergistic relationship. The analysis also finds that state-owned enterprises are more responsive to the policy than non-SOEs. This study contributes to the understanding of energy transition policies by providing empirical evidence of their efficacy in China's manufacturing sector, highlighting the importance of technological innovation, regional variations, and ownership structures in achieving sustainable manufacturing.

A Novel Centralized Allocation Data Envelopment Analysis Model for Carbon Emission Allocation Under a Heterogeneous Abatement Cost: Application Within the Chinese Industrial Sector

This paper presents a mathematical approach to analyzing carbon abatement costs and the allocation of carbon emission allowances in China’s industrial sectors. We utilize input–output data from 30 Chinese provinces between 2009 and 2018 to estimate carbon abatement costs by applying the slack-based measure (SBM) efficiency model and its dual form. The SBM model captures inefficiencies and offers a rigorous framework for measuring abatement costs. Using these costs, we develop a centralized allocation data envelopment analysis (DEA) model, which maximizes sectoral benefits through optimal reallocation. This DEA model is formalized as a linear programming problem, with the aim of determining the efficient allocations of carbon allowances while maintaining the system’s economic productivity. Furthermore, we construct intertemporal, interregional, and spatiotemporal allocation DEA models to examine the dynamics of carbon emission allowance allocation over time, space, and combined spatiotemporal dimensions. These models offer insights into the efficiency of carbon markets under varying conditions. Our proposed new mathematical formulations reveal optimal allocation strategies that can balance emission reductions with industrial productivity. This study also provides novel mathematical frameworks for analyzing the carbon allowance distribution and contributions to both the theory and application of mathematical optimization in environmental policy design. Our findings reveal that China’s industrial carbon abatement costs exhibit significant interprovincial and regional differences. Developed provinces with higher levels of industrial development have higher carbon abatement costs, while provinces with less-developed industrial sectors have lower costs. Under the interregional allocation scenario of carbon emission allowances that consider abatement costs, developed provinces have smaller industrial carbon emission reductions, whereas less-developed provinces have larger reductions. In the intertemporal allocation scenario, provinces with larger industrial economies face greater emission reduction tasks. Under the combined interregional and intertemporal allocation scenario, industrial sectors in coastal developed provinces have lower carbon emission reductions, while those in inland less-developed provinces have higher reductions, mirroring the spatial allocation results of carbon emission allowances.

National Forest City Policy and Urban Ecological Resilience: Evidence from 292 Cities in China

The process of sustainable urban development faces complex and severe environmental problems. Therefore, enhancing urban ecological resilience (UER) has become an urgent and critical goal. In this study, the establishment of national forest cities (NFCs) in China is regarded as an exogenous shock event, and the impact of NFCs on UER and its mechanisms are investigated based on data from 292 cities spanning 2003 to 2021 using a difference-in-difference method. It is found that NFCs can significantly enhance UER, and this conclusion holds after a series of robustness tests. Mechanism analysis shows that NFCs can effectively strengthen environmental regulations, upgrade industrial structures, promote green innovation, and thus enhance UER. Heterogeneity analysis indicates that the effect of NFC on UER is more significant in low-carbon non-pilot cities, cities with higher levels of industrial development, and cities in central and western China. Spatial spillover analysis shows that NFCs can effectively improve the ecological resilience of neighboring cities. Therefore, NFCs should be continuously implemented and optimized to establish a long-term mechanism for urban forests to enhance ecological resilience.

Can the National Public Cultural Service System Demonstration Zone Promote the Sustainable Development of Urban Culture?

The public cultural service system is a crucial component of urban culture and a key driver of cultural vitality and sustainable cultural development. This study leverages the “quasi-natural experiment” created by the establishment of National Public Cultural Service System Demonstration Zones to evaluate their impact on the sustainable development of urban culture. Using panel data from 295 prefecture-level cities between 2008 and 2019 and employing the difference-in-differences method, the study assesses how these zones influence cultural vitality. The findings reveal that the creation of these demonstration zones significantly boosts cultural investment and support, enhances cultural vitality, and promotes sustainable urban cultural development. Over time, this positive impact strengthens, particularly through increased cultural input driven by residents’ consumption patterns and urban economic growth. Additionally, the policy effects vary across regions and cities, depending on the level of tertiary industry development.

The Driving Factors and Path Selection for the Development Level of China’s Mariculture—A Dynamic Analysis Based on the TOE Framework

Mariculture is a key practice to promote the supply-side reform of fishery, and it is of strategic significance to explore the causes and paths of its high-level development. Based on the TOE (Technology-Organization-Environment) theoretical framework and the configuration methodology, this paper adopts the dynamic qualitative comparative analysis (QCA) method and panel data from 10 coastal provinces and cities in China from 2013 to 2021 to explore the configuration effects of six antecedents, namely, the intensity of technology promotion, investment in scientific research, personnel specialization, industry intensification, nearshore water quality, and offshore pollution discharge, along temporal and spatial dimensions, on the level of mariculture development. The results show that (1) individual driving factors do not constitute the necessary conditions for a high level of mariculture industry development, but the necessity of the three conditions—research funding, industry intensification and nearshore seawater quality—shows a general increasing trend; and (2) the results of the path analysis show that a total of seven configuration paths for a high level of development are generated, which can be further classified into “organization-led and technology synergistic”, “technology-organization-environment multiple-driven type”, and “technology-environment dual-driven type”. Based on the panel data, this study explores the impact of spatial and temporal changes in factor combinations on the development level of mariculture and provides a theoretical basis and practical insights for the development of locally adapted execution pathways.

Репрезентативность показателей и объективность оценок в компаративистике: экономика Российской империи второй половины XIX столетия в современных зарубежных исследованиях

The relevance of comparative studies of the level of industrial and economic development of the Russian Empire in the second half of the XIX century is determined by the fact that their results in some cases are used to substantiate theoretical ideas about the national characteristics of the Russian economy and society in comparison with the leading countries of Industrial Revolution. In economic literature, assertions about the “catastrophic” backwardness of Russia during this period are often encountered. Modern foreign historical-economic research allows for a more objective assessment of the gap between the level of industrial and economic development of the Russian Empire and the “advanced” states. However, the authors of these studies do not always succeed in consistently applying the principle of uniform criteria for comparing different economies. In particular, it is hardly justified: in some cases, to take into account, and in others, not to take into account the population and economic potential of territorial isolated peripheral regions of the respective economies. For example, the value of historical and economic comparisons is reduced by the confusion in research between the actual territory of the Russian Empire in the middle and second half of the XIX century, its territory within the conditional “borders of 1913” and the territory within “former USSR” borders. In this regard the article notes that conclusions drawn on the basis of fragmentary and arbitrarily interpreted information can’t be considered as fully correct. According to the author, in a comparative analysis of the economies-leaders of the Industrial Revolution, it is necessary to use assessment methods that take into account the population and indicators of economic development of peripheral territories were included in trade and financial exchanges with these economies, because this inclusion strongly spired the development of economies-leaders.

Can New Infrastructure Become a New Driving Force for High-Quality Industrial Development in the Yellow River Basin?

Ecological protection and high-quality development in the Yellow River Basin have become a major national strategy in China. This paper explores the impact and mechanisms of new infrastructure on high-quality industrial development in the Yellow River Basin, considering the current context of vigorous development of new infrastructure and the industrial development status of the region. This study finds that new infrastructure promotes high-quality industrial development in the Yellow River Basin, and the enhancement of digital literacy strengthens this positive impact. New infrastructure facilitates high-quality industrial development in the Yellow River Basin by driving labor transfer from the supply side and consumption upgrading from the demand side. This positive influence is particularly pronounced in the upstream cities, central cities, and urbanized areas of the Yellow River Basin. Further research indicates that there is a “pain period” in promoting the construction of new infrastructure, and only when the level of high-quality industrial development exceeds a certain threshold can its efficiency be further improved. The conclusions of this paper provide theoretical references and policy inspiration for the coordinated promotion of new infrastructure construction to empower high-quality industrial development in the Yellow River Basin.

Application of KNN algorithm incorporating Gaussian functions in green and high-quality development of cities empowered by circular economy

A growing number of industries have started to adapt to the circular economy since the concept's introduction. Therefore, in order to accurately evaluate the development level of circular economy, the circular economy prediction model based on support vector machine-Gaussian K-nearest neighbor is proposed. This model first uses the improved K-nearest neighbor algorithm based on Gaussian function to classify the index data of various levels, and then uses Support Vector Machine to make predictions based on relevant data. According to the experimental findings, the model's average prediction accuracy for each level of indicator was approximately 98.1%, 98.8%, 94.9%, and 95.9% for the levels of industrial development, resource consumption, ecological protection, and resource recycling and reuse, respectively. This prediction accuracy was higher than that of the multi-vector autoregressive model and the grey prediction model. The average prediction accuracy of the multi-vector autoregressive model, the grey prediction model, and the support vector machine-Gaussian K-nearest neighbor-based model in predicting the overall development level of the circular economy were about 94.3%, 96.2%, and 99.3%, respectively, with average recalls of about 86.6%, 87.7%, and 89.1%, and the average F1-measure was about 0.88, 0.89, and 0.92. Moreover, the average relative error based on the support vector machine-Gaussian K-nearest neighbour model was only approximately 0.6%, which was lower than the 3.7% and 2.8% for the multi-vector autoregressive model and the grey prediction model, respectively. Meanwhile, compared with the existing time series analysis techniques, the proposed SVM-Gaussian K nearest neighbor model fitted up to 0.95, which achieved good prediction performance. According to the above data, the support vector machine-Gaussian K-nearest neighbour model has the highest accuracy in predicting the amount of development of the circular economy.

Evaluation of the Coupling and Coordination Degree of the Wellness Tourism Industry in Panxi Area

The party's 20th report points out that green and healthy development is an extremely important part of the China's modernization drive, an important guarantee for the sustainable development of the country, and a basic means to realize that "clear waters and green mountains are gold and silver mountains". Sichuan province actively promotes the construction of a strong wellness industry, and strives to build Panxi region into an international sunshine wellness tourism destination. In recent years, the mass tourism market demand escalating, promote the tourism market emerging industry development, wellness industry, in response to the mass tourism market development status, this paper built covers two evaluation dimensions eight elements 16 evaluation index wellness brigade industry coupling coordinated development index system, using the entropy method and coupling coordination model in panxi area wellness industry and tourism industry coupling coordinated development level, based on the evaluation results. The study results show that: (1) with good coupling development degree and strong interaction; (2) the coordinated development level of wellness tourism industry in Panzhihua is low, Panzhihua is in moderate imbalance, Liangshan Prefecture is on the verge of imbalance, with large development space; (3) from 2017 to 2021 is wellness lag type, Liangshan Prefecture is tourism lag type in 2020 alone. Through the research and analysis of the coordinated development of wellness tourism in Panxi region, the comprehensive level of coordinated development of wellness tourism in Panzhihua is revealed, and then three suggestions are put forward: (1) improve the construction of wellness facilities and enhance the coordinated development level of wellness tourism; (2) build the integrated development mechanism of wellness tourism and tourism and promote the coordinated development of wellness tourism industry; (3) optimize the wellness tourism environment and promote the sustainable development of wellness tourism.

Digital Inclusive Finance Helps Green Industry in Fujian Province Development

Aims: Digital inclusive finance, as a combination of modern technology and financial services, has developed rapidly in recent years. This new financial model has not only changed the traditional way of providing financial services, but also profoundly affected all aspects of economic and social development. The report of the 18th CPC National Congress made the important decision of "vigorously promoting the construction of ecological civilization " from the strategic height of the sustainable development of the Chinese nation. China's green industry has ushered in a new phase of rapid development. As an important province on the southeast coast of China, Fujian Province, with rich natural resources and vast rural areas, is an important region to promote the development of green industry. Methodology: In this paper, the green industry index of nine prefecture-level cities in Fujian Province from 2011 to 2021 is selected as the explanatory variable, and the development level of digital inclusive finance is taken as the core explanatory variable to explore the impact of digital inclusive finance on the development of green industry in Fujian Province. Results: According to the multiple linear regression, it is found that the level of green industry development is positively correlated with the level of digital inclusive finance development at the 1% significant level, i.e., digital inclusive finance helps to promote the development of green industry in Fujian Province. Conclusion: Based on the findings of the study, the paper puts forward the following recommendations: through the provision of low-cost financing, innovative financial products, digitalized payments and settlements, popularisation of financial education, and the promotion of cooperation, digital inclusive finance can effectively support the development of the green industry. This not only helps to achieve the goal of environmentally sustainable development, but also promotes economic growth, creates employment opportunities and enhances social well-being.

A novel data-characteristic-driven modeling approach for imputing missing value in industrial statistics: A case study of China electricity statistics

As a direct reference tool to reflect the operational status and development level of national industry, industrial statistics hold significant value for numerous systematic studies. Nevertheless, it is crucial to recognize that the quality of these statistics can be compromised by the common occurrence of missing value. This issue poses a substantial challenge for analyzing and utilizing industrial statistics, impeding progress in tasks reliant upon them. Given the severity of the missing value problem in industrial statistical databases and the limitations of existing literatures on missing value imputation in terms of research objects and modeling approaches, this paper proposes a novel missing value imputation modeling approach for single-indicator panels of industrial statistics based on the idea of data-characteristic-driven (DCD). Accordingly, taking the inter-provincial “monthly power generation” data from China as an example, the imputation model was constructed and its validity was tested under different imputed objects (Jiangsu and Jilin), different missing types (continuous and discrete), and different missing rates (5%, 10% and 20%) respectively. The results indicate that the proposed DCD modeling approach in this paper exhibits excellent efficacy. The imputation model, constructed based on the data characteristic of the imputed object, demonstrates clear advantages in handling missing value with different missing types and rates. This is evident in its superior consideration of numerical accuracy, directional accuracy, and imputation stability, resulting in an outstanding comprehensive imputation effect.

Research on the Coupled and Coordinated Development of Tourism and Transport in Chengdu City

Based on a total of 16 indicators selected from the tourism and transport industries, an evaluation index system of the coupling and coordination development level of tourism and transport is constructed. The entropy value method and the coupling coordination degree model are used to conduct an empirical study on the development level and coupling coordination level of the transport and tourism industries in Chengdu City from 2011 to 2020. The results show that, on the whole, the coupling coordination degree of transport and tourism in Chengdu is poor and has been in a state of mild to moderate dysfunction. The development level of tourism lagged behind the development of transport from 2011 to 2012, and the two were in a state of mild dysfunction. However, from 2013 onwards, the development level of tourism was prioritized over the development level of transport. This shift caused the coupling coordination degree of the two industries to decline sharply to 0.23305 in 2013. The development level of the tourism industry increased again, reaching 0.34206 in 2019, which marked an improvement. Consequently, the coordination degree of the transport and tourism industries evolved from moderate dislocation to mild dislocation. Finally, the results of the empirical research are analyzed, and corresponding suggestions are put forward to promote the sustainable growth of the transport and tourism industries in Chengdu City. These suggestions aim to improve the coupled and coordinated development level of the two industries.

Research on Landscape Complexes in the Context of Rural Revitalization

Agriculture is the foundation of a country and the foundation of a strong country. In 2024, the No. 1 document of the Central Committee proposes that "to promote the comprehensive revitalization of the countryside, it is necessary to ensure national food security, ensure that there is no large-scale return to poverty, improve the level of rural industry development, improve the level of rural construction, improve the level of rural governance, and strengthen the party's overall leadership over the "three rural" work". Based on the strategy of rural revitalization, the construction of landscape complex is of positive significance for creating a unique rural landscape and promoting the rapid development of rural areas in the new era. Based on the case study of "Pastoral Lujia" in Anji County, Zhejiang Province, this paper deeply explores the landscape complex from the perspective of rural revitalization, and summarizes the design strategies of the landscape complex. This provides theoretical support and specific case reference for the future construction of rural areas, and has far-reaching practical significance for rural revitalization.

What were the spatiotemporal evolution characteristics and influencing factors of global land use carbon emission efficiency? A case study of the 136 countries

Nations worldwide must collaborate to tackle the challenge of improving carbon emission efficiency and optimizing land use effectively. This study extends the study area from provinces and cities, regional city clusters, and countries to 136 major countries in the world, and shows the differences between countries. The paper analyzed the spatiotemporal evolution characteristics and influencing factors of land use carbon emission efficiency (LCEE) in these 136 countries from 2000 to 2019 using the super-efficiency slacks-based measure data envelopment analysis (Super-SBM DEA) model, global malmquist index, spatial autocorrelation measurement tools and Spatial Durbin model. It can help to promote low-carbon and green development while simultaneously improving the global LCEE. The findings indicate that: (1) Over the study period, there is a trend toward a decline in the LCEE worldwide. (2) The primary cause of the worldwide LCEE’s declining trend during the study period is the reduction in technical efficiency. (3) The low-low cluster type accounts for more, while the high-high agglomeration type accounts for less and exhibits a sluggish growth pattern. On the whole, there is a phenomenon of non-aggregation and non-uniformity. It is necessary to increase the driving effect of high-high cluster radiation. (4) Economic development level, investment level, population size, public service level and environmental sustainability level all have a significant impact on LCEE, while industrial development level has no significant impact on LCEE. From a global perspective, the radiation driving role of countries with high LCEE should be increased. Improve the efficiency and technological level of land use emission in light of local conditions, and promote independent innovation in green and low-carbon technologies. This is conducive to the establishment of long-term low-carbon growth.

Difference in regional logistics development level in China based on entropy weight TOPSIS and Dagum models

The high-quality development of the logistics industry, which is an essential and strategic industry supporting the national economic operation and a fundamental component of modern industrial system construction, is not only a key component of the high-quality development of the national economy but also the main driving force for the high-quality growth of the national economy. As the supporting industry of the national economy, the logistics industry will also face spatial disequilibrium during development. Therefore, to achieve the coordinated development of the logistics industry, the high-quality development and the spatial-temporal unbalanced development status of the logistics industry in each province must be figured out first. This research established a comprehensive evaluation system for the logistics industry development, which included 14 basic indexes based on the provincial-level panel data of 30 provinces in China during 2009–2020. Then, the regional logistics development level score in China was measured using the entropy weight TOPSIS method, and the differences in the regional logistics development level in China and the dynamic evolution law of their distribution were deeply explored through the Dagum Gini coefficient model. The research results revealed that the evaluation index system (14 basic indexes) for the regional logistics industry development level in China was relatively scientific and reasonable; the regional logistics industry development level in China was increasing year by year, showing a steady upward trend, and the imbalance in the eastern, central, and western regions regarding the regional logistics development was shrinking year by year; the average intergroup contribution rate was 36.33%, the intragroup contribution rate was 31.49%, and the contribution rate of intensity of trans variation was 32.19%, proving that the regional differences exerted a most extraordinary influence on the spatial differences in the regional logistics industry development level in China. The research results have important reference value for summarizing the meaning of high-quality logistics industry development, constructing the evaluation index system for logistics industry development, and exploring the reasons for the temporal and spatial differences in logistics industry development in China.

Research of China's New Energy Vehicle Market Based on TOPSIS and LSTM Models

This research paper provides an in-depth analysis of the development trajectory of China's New Energy Vehicle (NEV) market, utilizing both the TOPSIS and LSTM models. The TOPSIS model is ingeniously applied to assess the development level of the NEV industry, identifying key factors such as government policies, charging infrastructure, public acceptance, technological progress, and economic indicators. Subsequently, the paper delves into the LSTM model, a specialized form of Recurrent Neural Network (RNN) designed for handling time-series data with long-term dependencies. The LSTM architecture, equipped with forget, input, and output gates, is trained to minimize Mean Square Error (MSE) and Root Mean Square Error (RMSE), thereby optimizing model performance and preventing overfitting. The predictive capabilities of the LSTM model are demonstrated through a forecast of NEV sales in China for the next decade, showcasing the model's effectiveness in capturing market dynamics and growth trends. The integration of TOPSIS for evaluative analysis and LSTM for predictive forecasting offers a robust framework for understanding and anticipating the complexities of the NEV market.

Analysis of dynamic relationship between agricultural products circulation service industry and circulation efficiency in less developed regions: based on data from Western China

The market circulation system for agricultural products in less-developed regions lags behind; it fails to meet the requirements for efficient circulation. Therefore, it is crucial to explore the dynamic relationship between the Agricultural Products Circulation (APC) service industry and circulation efficiency. Using panel data from 29 regions in China, the entropy method measured the Development Level (DL) of the APC service industry, while the non-oriented super-efficiency Slacks-Based Measure (SBM) model was employed to assess the APC efficiency. A Panel Vector Autoregressive (PVAR) model was built for estimation. The impulse response function and variance decomposition were utilized to analyze the differences in the DL of the APC service industry, circulation efficiency, and their interaction mechanism across the Western, Central, and Eastern regions of China. The findings indicate that the DL of the APC service industry and APC efficiency in the less-developed regions of the West have a positive driving effect on each other. However, the magnitude of this effect was asymmetric and transient. The APC service industry’s DL and APC efficiency are more dependent on their inertia, and no efficient two-way feedback mechanism has been formed. This study provides a reference for the construction and sustainable development of modernized APC systems in less-developed regions.