Search

The Chinese government is constantly pursuing a green transformation of its industry under the United Nations Sustainable Development Goals (SDGs). At the same time, the booming digital economy has brought new opportunities and challenges to the Chinese government, and it is relevant to discuss the contribution of the digital economy to China's green development. In this study, we use panel data for 247 cities in China from 2011-2019. The impact of the digital economy on green total factor productivity is examined, and the mechanism of green technological innovation in this process is verified. It has been found that the digital economy can promote GTFP and that green technological innovation has a positive moderating role in this process. We also verify the threshold effect of green technological innovation, and the role of the digital economy can be inflated when green technological innovation reaches the corresponding threshold. Of course, these findings pass a series of robustness tests, and they are plausible. Accordingly, we put forward some policy recommendations to mitigate the possible problems in reality in order to promote green production in China. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xinyang Normal University Natural Science Edition is the property of Journal of Xinyang Normal University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The superefficiency SBM-DEA model and DEA-Malmquist index were used to measure the water resource use efficiency in Anhui Province from 2011 to 2020, and the Tobit model was used to analyze the influencing factors. The result showed that water resource use efficiency in Anhui Province has not reached the effective level, and the average value of water resource use efficiency fluctuates from 0. 931 to 0. 873,among the 16 cities, only Hefei, Huaibei and Huangshan achieve DEA efficiency in water use,and the remaining 13 cities, the water resource use efficiency is below the production frontier. The average Malmquist index of water resource use efficiency in Anhui Province is 0. 981, which is generally in a declining stage,the change of technical efficiency and the change of technological progress have hindered the increase of water resources utilization efficiency in Anhui Province. The average Malmquist index of water resource use efficiency in Hefei, Huaibei, Wuhu, Tongling, Anqing and Huangshan are on the rise, showing a good growth trend, the remaining 10 cities are in the declining stage. The per capita GDP, the proportion of primary industry and the proportion of agricultural water use all have significant positive promoting effects on the improvement of water use efficiency in Anhui Province,both per capita water consumption and per capita sewage discharge have significant negative effects on water resources utilization efficiency. [ABSTRACT FROM AUTHOR]

The process of digitizing businesses involves ongoing investments and additional costs, leading to the inevitable inquiry into the economic impact of digital transformation. Specifically, it's important to evaluate how this process contributes to the economic growth of nations. The article introduces a method for creating a ranking of European countries according to the economic benefits derived from digitalizing businesses of different scales. To achieve this, DEA models were developed to measure the effectiveness of digital adoption by small and medium-sized enterprises and larger corporations. For input variables, we selected metrics that reflect the extent of business digitalization, specifically, the proportion of SMEs (small and medium-sized enterprises) with a high digital intensity index (DII), the percentage of SMEs utilizing cloud technologies, and the contribution of SME turnover to the overall e-commerce turnover. The output variables chosen were metrics indicative of a country's economic health: GDP per capita, the ratio of exports to GDP, and the international investment position. The evidence demonstrates that due to significant differences in size, economic advancement, and digitalization levels among EU countries, the VRS model more adeptly accommodates these disparities. This approach permits the evaluation of each country's performance based on its unique situation and potential for development, without consideration of its economic magnitude. In 2022, Denmark, the Netherlands, Sweden, Finland, Malta, and Belgium emerged as the frontrunners in digital intensity among SMEs, with nearly 40% of businesses exhibiting a high degree of digital engagement. Among these leaders, only Malta and the Netherlands achieved the highest efficiency in leveraging digitalization for economic growth, as determined by the VRS model that considers variable returns to scale. It was shown, that the economic effect of digital transformation on large enterprises in EU countries is more substantial than on small and medium-sized enterprises [ABSTRACT FROM AUTHOR]

This study presented a radically different approach to efficiency evaluation based on the impact of the Socioeconomic and Behavioral health determinants framework on health outcomes for the countries of Middle-East region. The level of education, employment, and the percentage of the population living in the rural area constitutes the socioeconomic framework. The prevalence of tobacco smoking and alcohol consumption formed the behavioral framework. The model considers life expectancy at birth and mortality rate from non-communicable diseases as health outcomes. The econometric models of the PLS-SEM, the DEA, and the Malmquist TFP index are used to analyze the data. The DEA results highlight differences in the impact of socioeconomic and behavioral health determinants on health outcomes across the countries of the Middle-East region. Finally, evidence from the Malmquist TFP index shows an improvement in health production between the periods 2006–2017. Moreover, a substantial gap in efficiency is observed between economically prosperous countries and others who are less well-off. Furthermore, socioeconomic and behavioral frameworks positively impact life expectancy at birth. Similarly, the two frameworks have a negative impact on the mortality rate from chronic non-communicable diseases. A higher impact on health outcomes is observed in the socioeconomic as a behavioral framework in the model. The study's results have contributed to the policymakers, citizens, and the country's government to compare the health system efficiencies across the middle-east region, which would help achieve the health outcome more efficiently. [ABSTRACT FROM AUTHOR]

Abstract Background In China, enhancing the pooling levels of basic health insurance has consistently been regarded as a pivotal measure to promote the refinement of the healthcare insurance system. From 2020 to 2022, the widespread outbreak of COVID-19 posed new challenges to China’s basic health insurance. Methods The research utilizes Data Envelopment Analysis (DEA), Malmquist index assessment, and fixed-effects panel Tobit models to analyze panel data from 2020 to 2022, assessing the efficiency of basic health insurance in Gansu Province. Results From 2020 to 2022, the average overall efficiency of the municipal pooling of Basic Medical Insurance for Urban and Rural Residents was 0.941, demonstrating a stable trend with a modest increase. The efficiency frontier regions have expanded from 5 (35.71%) to 7 (50%). Operational efficiency exhibited a negative correlation with per capita hospitalization expenses and per capita fund balance but a positive correlation with per capita accumulated fund balance and reimbursement rates for hospitalized patients. In 2021, compared to 2020, the county-pooling Basic Medical Insurance for Urban Employees saw a decline of 0.126 in overall efficiency, reducing the efficiency frontier regions from 8 to 3. However, from 2021 to 2022, the municipal-coordinated Basic Medical Insurance for Urban Employees experienced a 0.069 increase in overall efficiency, with the efficiency frontier regions expanding from 3 to 5. Throughout 2020 to 2022, the operational efficiency of the Urban Employee Basic Medical Insurance showed a consistent negative correlation with per capita fund balance. Conclusion From 2020 to 2022, the overall operational performance of basic health insurance in Gansu Province was satisfactory, and enhancing the pooling level is beneficial in addressing the impact of unforeseen events on the health insurance system.

Abstract By integrating land use and transportation systems, transit-oriented development (TOD) focuses on transit and land development, development potential, and the balance between transportation and land use. The TOD level assessment not only helps optimize existing TODs but also guides TOD planning. Based on previous literature, methods for assessing TOD around rail transit stations can be roughly divided into three categories: TOD index, the node-place model, and the data envelopment analysis (DEA) model. The TOD index aggregates indicators from different dimensions into a single value for evaluation. The node-place model emphasizes transportation, land use, and the balance between them, as well as expansion factors. And the DEA model is suitable for situations without input indicator weights or consideration of different units of measurement. TOD indicators are the basis of the evaluation, and in both the TOD index and node-place models, indicator weights are mostly determined by using subjective methods. Furthermore, a limited number of studies to date have pre-evaluated the implementation of TOD at rail stations under construction or in planning. This paper aims to assess the level of TOD areas at the rail transit station level, which can help in constructing the evaluation index system, selecting TOD stations, and optimizing them.

Sugar, an important commodity, is strategic for almost all countries in the world. The present study analyzed the operational data of seven sugar companies listed on the stock market in China using data envelopment analysis and panel data regression models. Results showed that Chinese sugar industry had an overall poor performance in 2012, and five of these seven companies did not achieve optimal efficiency. Considering that pure technical efficiency regarding human, physical, and financial inputs had already reached the optimum level, the main factor affecting technical efficiency was scale efficiency. Besides, after continuous adjustment and optimization of company size, all listed sugar companies in China achieved optimal efficiency in 2022, resulting in steady industry growth. An analysis on the factors affecting the stability, financial condition, operational capability, and profitability of these companies suggested that concentrated equity concentration, liabilities and owner's equity, and enterprise listing time positively influenced the improvement of comprehensive efficiency in the sugar industry. Interestingly, owing to the substantial subsidies provided by the government, the total asset turnover ratio and net profit were not significant interfering factors. Furthermore, sugar companies should continue to update equipment and technology, diversify business operations, improve their operational scale, and use endogenous development dynamics to enhance the capacity and competitiveness for sustainable development. These above results should provide valuable insights and feasible recommendations for the development of sugar industry around the world. [ABSTRACT FROM AUTHOR]

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a "high in the northeast and low in the southwest" pattern, transitioning post-2010 to a smoother "core-periphery" pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region. [ABSTRACT FROM AUTHOR]

By integrating land use and transportation systems, transit-oriented development (TOD) focuses on transit and land development, development potential, and the balance between transportation and land use. The TOD level assessment not only helps optimize existing TODs but also guides TOD planning. Based on previous literature, methods for assessing TOD around rail transit stations can be roughly divided into three categories: TOD index, the node-place model, and the data envelopment analysis (DEA) model. The TOD index aggregates indicators from different dimensions into a single value for evaluation. The node-place model emphasizes transportation, land use, and the balance between them, as well as expansion factors. And the DEA model is suitable for situations without input indicator weights or consideration of different units of measurement. TOD indicators are the basis of the evaluation, and in both the TOD index and node-place models, indicator weights are mostly determined by using subjective methods. Furthermore, a limited number of studies to date have pre-evaluated the implementation of TOD at rail stations under construction or in planning. This paper aims to assess the level of TOD areas at the rail transit station level, which can help in constructing the evaluation index system, selecting TOD stations, and optimizing them. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Reservoir immigrants have made significant contributions to the national economic construction, and proper resettlement and support for reservoir immigrants are the keys to social harmony and stability. In order to objectively, accurately, and scientifically evaluate the efficiency of the use of post resettlement funds for reservoir immigrants in Ningxia from 2019 to 2021, a three-stage DEA model is used to analyze and study the efficiency of post resettlement funds in 14 typical districts and counties of Ningxia. The SFA method is used to eliminate the impact of environmental factors and random interference on the efficiency of fund use. The analysis results indicate that: 1 It is reasonable for this paper to use the three-stage DEA model to evaluate the efficiency of the use of post resettlement funds for reservoirs in Ningxia. 2 After removing the influence of environmental factors and random interference, the utilization efficiency of the support fund in the third stage increased by 55.1%, 87.8%, and 32.4% compared with the first stage, respectively, which improves the accuracy of the evaluation of the utilization efficiency of the support fund and can provide a reference for the development of subsequent projects. 3 Among the three environmental factors studied in this article, improving education level has gradually become an effective way to improve the efficiency of using support funds. 4 Through DEA Malmquist dynamic analysis, the total factor production efficiency of six districts and counties, including ZN County, PL County, and LT District, is relatively low. The main factors are low efficiency in fund management and improper scale allocation. Based on the analytic results, we will continuously improve the quality of life of immigrants by strengthening management, optimizing project scale and types, implementing classified policies, and providing precise support. [ABSTRACT FROM AUTHOR]

The process of digitizing businesses involves ongoing investments and additional costs, leading to the inevitable inquiry into the economic impact of digital transformation. Specifically, it's important to evaluate how this process contributes to the economic growth of nations. The article introduces a method for creating a ranking of European countries according to the economic benefits derived from digitalizing businesses of different scales. To achieve this, DEA models were developed to measure the effectiveness of digital adoption by small and medium-sized enterprises and larger corporations. For input variables, we selected metrics that reflect the extent of business digitalization, specifically, the proportion of SMEs (small and medium-sized enterprises) with a high digital intensity index (DII), the percentage of SMEs utilizing cloud technologies, and the contribution of SME turnover to the overall e-commerce turnover. The output variables chosen were metrics indicative of a country's economic health: GDP per capita, the ratio of exports to GDP, and the international investment position. The evidence demonstrates that due to significant differences in size, economic advancement, and digitalization levels among EU countries, the VRS model more adeptly accommodates these disparities. This approach permits the evaluation of each country's performance based on its unique situation and potential for development, without consideration of its economic magnitude. In 2022, Denmark, the Netherlands, Sweden, Finland, Malta, and Belgium emerged as the frontrunners in digital intensity among SMEs, with nearly 40% of businesses exhibiting a high degree of digital engagement. Among these leaders, only Malta and the Netherlands achieved the highest efficiency in leveraging digitalization for economic growth, as determined by the VRS model that considers variable returns to scale. It was shown, that the economic effect of digital transformation on large enterprises in EU countries is more substantial than on small and medium-sized enterprises.

【Objective】The research aims to explore the contemporaneous causal relationship between environmental regulation, technological innovation, and agricultural energy efficiency, and to investigate their long-term and short-term linkage effects.【Method】Provincial panel data of China from 1998 to 2017 was utilized and the DEA model was employed to measure the agricultural energy efficiency indicators. Additionally, the DAG-SVAR model was used to study the interplay between environmental regulation, technological innovation, and agricultural energy efficiency.【Result】The results revealed significant regional disparities in average agricultural energy use efficiency, with values of 0.86, 0.72, and 0.65 in the eastern, central, and western regions, respectively. By analyzing the causal relationship through directed acyclic graphs, it was observed that both environmental regulation and technological innovation had a positive impact on agricultural energy efficiency, while it was also influenced by the agricultural disaster rate. Further SVAR analysis and variance decomposition showed that: in the short term, there was no obvious causal relationship between the agricultural disaster rate and agricultural energy efficiency, while environmental regulation and technological innovation had relatively low contribution rates to agricultural energy efficiency, which were 1.16% and 2.13%, respectively. However, in the long run, their contribution rates increased significantly to 7.11% and 8.24%, respectively. Moreover, agricultural technological innovation was not only influenced by itself but also by environmental regulation. As the extension of predictive period, environmental regulation promoted technological innovation progressively.【Conclusion】Based on the research results, we propose the following recommendations: first, differentiated improvement measures should be implemented to address regional disparities in agricultural energy efficiency; second, environmental regulation should be strengthened to foster agricultural energy efficiency; finally, agricultural energy-saving and emission-reduction technologies should be enhanced to achieve related technological innovations.

This research dynamically evaluates the innovation efficiency of China's high-tech industry and explores the efficiency differences in basic innovation, application innovation, and income innovation of this industry for different regions. Based on panel data of 30 provinces from 2015 to 2019, we construct a three-stage dynamic DDF (Directional Distance Function) model, divide the high-tech industry into three stages and measure the efficiency of the three stages. From 2015 to 2019, most of the total efficiency of China's high-tech industries showed an upward trend, with the western region having the highest total efficiency value and the central region the lowest. Most of the 30 provinces present basic innovation efficiency < applied innovation efficiency < profitable innovation efficiency. The conclusions from the article's empirical analysis can help developing countries concerned find out key links to improve the efficiency of high-tech entrepreneurship and innovation and then formulate relevant industrial policies. [ABSTRACT FROM AUTHOR]

Conventional mining enterprises, particularly coal-related ones, exhibit substantial environmental pollution and high energy consumption, while those involved in new energy resources, such as lithium and cobalt, face severe resource shortages. Consequently, the economic efficiency of China's mining enterprises is significantly constrained. This study examines data from nine representative listed enterprises in China spanning 2016 to 2021. Employing the DEA model--i.e., BCC (VRS) model, we analyze the economic efficiency of mining enterprises with a focus on stakeholders. The paper provides static and dynamic analyses, offering insights and recommendations for enhancing technology, reducing costs, and fortifying social relationships. [ABSTRACT FROM AUTHOR]

【Objective】The research aims to explore the contemporaneous causal relationship between environmental regulation, technological innovation, and agricultural energy efficiency, and to investigate their long-term and shortterm linkage effects.【Method】Provincial panel data of China from 1998 to 2017 was utilized and the DEA model was employed to measure the agricultural energy efficiency indicators. Additionally, the DAG-SVAR model was used to study the interplay between environmental regulation, technological innovation, and agricultural energy efficiency.【Result】 The results revealed significant regional disparities in average agricultural energy use efficiency, with values of 0.86, 0.72, and 0.65 in the eastern, central, and western regions, respectively. By analyzing the causal relationship through directed acyclic graphs, it was observed that both environmental regulation and technological innovation had a positive impact on agricultural energy efficiency, while it was also influenced by the agricultural disaster rate. Further SVAR analysis and variance decomposition showed that: in the short term, there was no obvious causal relationship between the agricultural disaster rate and agricultural energy efficiency, while environmental regulation and technological innovation had relatively low contribution rates to agricultural energy efficiency, which were 1.16% and 2.13%, respectively. However, in the long run, their contribution rates increased significantly to 7.11% and 8.24%, respectively. Moreover, agricultural technological innovation was not only influenced by itself but also by environmental regulation. As the extension of predictive period, environmental regulation promoted technological innovation progressively.【Conclusion】Based on the research results, we propose the following recommendations: first, differentiated improvement measures should be implemented to address regional disparities in agricultural energy efficiency; second, environmental regulation should be strengthened to foster agricultural energy efficiency; finally, agricultural energy-saving and emission-reduction technologies should be enhanced to achieve related technological innovations. [ABSTRACT FROM AUTHOR]

Aquatic product e-commerce is an important component of fresh e-commerce. At present, there is a lack of research on the efficiency of aquatic product e-commerce both domestically and internationally, especially when it comes to research on the efficiency and influencing factors of aquatic product e-commerce. The paper selected the input-output data of 25 coastal port cities in China's "Taobao" aquatic product e-commerce in 2019, and used the DEA model to construct the input-output index system for aquatic products e-commerce from the perspectives of human capital, informatization, logistics operation and aquatic products transaction scale. It comprehensively evaluated the efficiency of aquatic products e-commerce in coastal port cities in China. The results showed that the efficiency of aquatic products e-commerce in five coastal port cities including Dalian, Rizhao, Lianyungang, Nanjing and Zhoushan was effective, and the efficiency of aquatic products e-commerce in other cities was invalid. Suggestions were proposed as follows: strengthen interregional cooperation and optimize the resource allocation, reasonably arrange the input factors, build a cold chain logistics system and improve cold storage facilities, emphasize talent cultivation and improve talent quality.

Understanding members’ psychological needs, improving members’ satisfaction, and enhancing clubs’ operational efficiency are key factors in the development of sports clubs. Taking the customer satisfaction model and the balanced scorecard of operational performance as the starting point, this paper analyzes the factors related to member satisfaction of sports clubs by using multiple linear regression models with provincial sports clubs in 31 provinces (municipalities/autonomous regions) of China as the research objects. After selecting 16 provincial sports clubs, the DEA model was built by utilizing staff salary as the input indicator and club winning rate and operating income as the output indicators. The overall satisfaction of sports club members is 3.94. The regression results show that each independent variable has achieved 75.3% of the explanatory strength of the overall satisfaction of members.4 of the 16 sports clubs reach the optimal operational efficiency in 2023. The comprehensive technical efficiency and scale efficiency of sports clubs were only 0.697 and 0.659, respectively, in 2019. By analyzing the changes in the membership satisfaction and operational efficiency of sports clubs, the DEA model is constructed. The analysis of factors that influence satisfaction and operational efficiency trends can help sports clubs choose inputs rationally and provide new perspectives for improving member satisfaction and operational efficiency.

The effective allocation of educational resources has significant practical value and importance in ensuring the fairness of education. The study examines the efficiency of educational resource allocation for 30 schools in City Z from 2020 to 2023 using the DEA model. Reasonable data are screened out based on the DEA model, and then the MLP model is used to construct a model of educational resource allocation efficiency, and the sample data are comprehensively evaluated, so as to screen out the optimal program. Then, according to the results of the MLP model, we determine the importance of each input parameter to obtain the reference basis for adjusting each investment factor to improve the efficiency of educational resources. The method for improving the dynamic allocation efficiency of educational resources is summarized at the end. The allocation efficiency of educational resources in the sample schools is above the medium level, and the comprehensive technical efficiency is 0.61~0.67, which fails to maximize the use of educational resources. The MLP model has a good predictive effect on output variables, and the teaching area (0.319), paper books (0.281), and fixed investment (0.269) are the most important input factors. It is recommended that the DEA-MLP model be used to optimize and optimize the resource management system, improve the scientific evaluation and supervision system, and enhance the management capacity of teachers, so as to further promote the efficiency of the dynamic allocation of educational resources.

Urban renewal now dominates the strategic stage of urbanization, shifting from the previous focus on “whether there is” to the pursuit of “good.” In the context of urban renewal, the transformation of old neighborhoods should be carried out reasonably. In this regard, this study focuses on exploring design ideas for the transformation of old neighborhoods in the context of sustainable community economic development, with the aim of proposing a set of comprehensive transformation programs. Then, based on the three perspectives of residents, community, and city, the evaluation indexes for the transformation of old neighborhoods are selected from two perspectives of input-output, and the transformation efficiency evaluation model is constructed by combining the model of DEA-BCC and the model of DEA-Malmquist index. Finally, taking 19 old neighborhoods in QD city as samples, we analyze the citizens’ satisfaction with the transformation effect of the neighborhoods, analyze the efficiency of the transformation investment in the old neighborhoods from the two perspectives of comprehensive efficiency value and scale efficiency value, and analyze the problems and the direction of improvement of the transformation of the old neighborhoods from the redundancy of the slack variables. The results show that the average investment efficiency of the old neighborhood transformation is 0.9185, and the pure technical efficiency and scale efficiency are 0.9239 and 0.9651, respectively.

The revitalization of rural culture is an important part of the comprehensive revitalization of the countryside in the new era and is of great strategic significance to the realization of the development goal of agricultural modernization. Guided by the value orientation of rural cultural revitalization, the article analyzes the characteristics of multimedia communication and the application strategy in rural cultural communication. Using Oracle as the data storage module and combining the B/S structure, a rural culture digital resource library was established, rural culture images were digitally converted through deep features, end-to-end detection was introduced to extract rural music audio, and a three-dimensional model was also established for rural cultural landscape. The DEA model was also combined with the Malmquist index to explore the utilization efficiency of rural cultural resources. The data on rural cultural revitalization in Province S were used to analyze the efficiency and change trends of its rural cultural revitalization, and the application of the digital resource library of rural culture was studied. The overall efficiency index of rural cultural revitalization practice increased by 7.21% between 2013 and 2023, the average value of the change in the Malmquist index was 1.037, the audience’s satisfaction with the rural cultural services was 3.48 points, and the experience assessment of digital resource library is 83.35 points. The revitalization of rural culture needs to focus on accessing multimedia platforms and relying on digital resource libraries to achieve the deepening of the scope of rural cultural communication.

The rapid development of the digital economy makes the center of gravity of enterprise development accelerate from the consumer field to the production and manufacturing field, penetrating all aspects of the daily operation and management of an enterprise. This paper presents relevant management strategies by exploring the impact of the ecosystem model of enterprise management innovation on the impact of enterprise management in the digital context. In order to measure the comprehensive efficiency value, the efficiency value of capital absorption, and the efficiency value of investment after enterprise management, the theory of antagonistic cross-efficiency is introduced, the antagonistic cross-DEA model is constructed, and the evaluation steps of enterprise management effect are given. Using this model to empirically analyze the management effectiveness of China’s construction industry, enterprise performance=4.563+0.352*digital innovation ecosystem index+0.236* periodic cost+0.362*number of R&D personnel, and the digital innovation ecosystem is significantly related to enterprise performance. Finally, this paper designs a corporate management strategy for the digital innovation ecosystem in the context of the digital economy from three perspectives.

This paper uses the DEA model and the Malmquist index model to look at how well building a geographical indication brand for an agricultural product works in prefecture-level cities in Jilin Province. It also looks at how the performance of building a geographical indication brand for an agricultural product changes over time in prefecture-level cities in Jilin Province. Then, a brand competitiveness evaluation system was made up of regional elements, brand elements, industrial elements, and support elements. The level of development of agricultural product brand competitiveness in Jilin Province was looked at using fuzzy comprehensive evaluation and hierarchical analysis. The results of the evaluation were used to find the factors that affect the improvement of its brand competitiveness, which helped to map out the next steps for reshaping agricultural product brands in Jilin Province. The comprehensive evaluation of the brand competitiveness of agricultural products in Jilin Province has a specific score of 81.4, and the regional element, brand element, product element, and support element have specific scores of 82.01, 83.2, 81.66, and 80.7, respectively. This study provides references to promote the development of agricultural products’ geographical indications and to enhance the competitiveness of the corresponding brands, and it enriches and improves theoretical research on the competitiveness of the brands of agricultural products’ geographical indications.

With the development of the economy and society, people pay more and more attention to physical health. In order to make the big health enterprises in the long term at the level of smooth development, it is necessary to carry out an in-depth study on the investment efficiency and potential risk of the big health industry. This study constructs an investment efficiency evaluation method based on the DEA model. Firstly, the comprehensive efficiency is decomposed through the CCR model to further obtain the output results. Then, the effectiveness of enterprise investment is evaluated. The changes in the investment efficiency of the big health industry and other sample decision-making units are analyzed through the DEA-Malmquist model to output the trend of the overall investment efficiency. Logistic regression, support vector machine, and random forest models are used to assess the risk of the large health industry, respectively, and several classifiers are trained. When predicting the final sample, the voting or mean value method is used to count the effect of classification. The overall mean value of big health enterprises hovered between 0.96 and 0.98 in five years, indicating that the comprehensive investment efficiency of the big health industry is relatively stable. The average AUC value of the random forest model is 0.635, which is 0.028 higher than the average AUC value of the support vector machine; thus, it is concluded that there is no great fluctuation in the investment efficiency of the big health industry under the background of the digital economy, and the random forest model is more suitable for the risk assessment of the big health industry.

The essential role of basic public services is to mitigate income disparities across regions, between urban and rural areas, and among societal members, thereby fostering social equity and ensuring the harmonious progression of society. This article delves into the theoretical foundations of public services within ethnic regions and proposes an evaluation index system grounded in the principle of public service equity. To quantify the provision of public services in ethnic areas, the study employs a comprehensive scoring model and the Thiel index, enhancing the analytical framework with the Data Envelopment Analysis (DEA) model to assess the efficiency of public service delivery. Additionally, the Malmquist index is utilized to trace the dynamic evolution of public service levels over time. The research focuses on five ethnic autonomous regions, evaluating their public service levels and operational efficiency. Findings indicate a relatively low Thiel index in these regions, ranging between 0.36 and 0.39, suggesting modest disparities in public service provision. The variance between the highest and lowest average technical efficiencies in public services across these regions from 2015 to 2019 was a mere 3.33%, with an overall efficiency increase of 24.20% during this period. The data underscore a critical need for enhanced investment in public services within ethnic regions to satisfy the escalating demand and effectively foster a service-oriented governmental framework.

Cultural and creative industries are increasingly recognized as vital sectors in today’s global economy, and the advent of digital media has ushered in new avenues for enhanced development. This study explores the relationship between digital media technology and the progression of cultural and creative industries, with a specific focus on Shanxi. Utilizing the scale reward invariant BCC model within the DEA framework, this research assesses the developmental efficiency of Shanxi’s cultural and creative sectors. It identifies various decision-making units as benchmarks for the industry’s development, evaluating their comprehensive efficiency, pure technical efficiency, and scale efficiency, and proposes strategies for optimizing input and output metrics. Furthermore, the integration of the Tobit regression model with digital media technology allows for an analysis of the latter’s impact on the developmental efficiency of these industries in Shanxi. The findings reveal that the comprehensive efficiency of cultural and creative industry development in Shanxi is currently at 0.572. To achieve an effectively comprehensive level, there is a need to increase digital media technology input by 31.73% and reduce economic input and employment by 13.97% and 18.18%, respectively. The study demonstrates that a 1% increase in digital media technology usage correlates with a 0.315 percentage point rise in the development efficiency of Shanxi’s cultural and creative industries. Consequently, Shanxi Province is urged to fully leverage its cultural resources, actively recalibrate the industry scale through enhanced use of digital media technology, and strive for a comprehensive efficiency that meets effective benchmarks.

With the successful bidding for the 2022 Beijing Winter Olympics, the ice and snow sports tourism industry has received extensive attention from society. In this paper, under the background of the integration of sports and tourism, we construct an efficiency assessment system for the ice and snow sports tourism industry and then use the entropy value method and coefficient of variation method to improve the DEA model and construct a combination-weighted SE-SBM model to explore the operational and developmental efficiency value of the ice and snow sports tourism industry. In addition, considering the changes in regional industrial productivity over time, the Malmquist index model is utilized to respond to the dynamic development efficiency of the ice and snow sports tourism industry. Finally, the development efficiency of the ice and snow sports tourism industry is analyzed based on the panel data of some regions in China from 2014-2023, in which the mean value of the development efficiency of Jilin and Heilongjiang reaches 1.22778. Among the influencing factors, the value of weight gained from expanding consumption is 0.5426, which is greater than that of the other three factors. This study proposes that expanding consumption is the key to promoting the development of the ice and snow sports tourism industry.

Innovation and entrepreneurship are essential for higher vocational students to escape low-end employment and are vital for vocational education to provide diverse products and services, fulfilling the people’s demand for a better life. This study builds on the theory of innovation and entrepreneurship education, integrating information technology to devise the “Four-Drive-One-Guide” model for vocational colleges. Utilizing Province A as a case study, a survey was conducted to gather data on the effectiveness of this education model, analyzed using ANOVA, Pearson’s correlation coefficient, and multiple linear regression. Furthermore, the operational efficiency of innovation and entrepreneurship education across 30 Chinese regions was assessed using the CCR model within the DEA framework. Findings reveal that the “Four-Drive-One-Guide” model significantly boosts students’ innovative and entrepreneurial capabilities, with an average rating of 4.06. The most influential factor in its effectiveness is students’ attitudes, with a coefficient of 0.238. Moreover, vocational colleges in the eastern region exhibit the highest comprehensive efficiency at 0.875. The study suggests that integrating industry teaching and optimizing the curriculum can further enhance students’ innovative and entrepreneurial thinking.

As far as the current situation of children’s English picture book translation and reading teaching is concerned, there exists the phenomenon that teachers pay little attention to translation and reading teaching, and the teaching effectiveness is low. This paper evaluates the translation and teaching of English picture books to children using the theory of multiple intelligences. The problem of data input and output is solved through the decision-making unit (DMU) as well as the C2 R model composed of the DEA model. Based on the fuzzy comprehensive evaluation method and the target classification method to evaluate the students’ English learning quality and design the evaluation module, we construct the children’s picture book English teaching model under the combination of the DEA model and the multiple intelligences theory, and at the same time, we take the eight domains of the multiple intelligences theory as the evaluation indexes, combine the fuzzy comprehensive evaluation and the principle of the target classification method to evaluate the student’s learning quality of the English picture book translation and reading to analyze The status quo of children’s English picture book teaching under the theory of multiple intelligences as well as the teaching results, comparing the results of the students in the two classes and analyzing the data results statistically. Students are most interested in reading children’s English picture books when they are between 0 and 2.4. The experimental class has a higher translation skill score than the control class, with an increase of 2.79875, 2.225, and 1.975, and the translation part of the improvement is more effective.

With the continuous development of blockchain technology and the capital market, asset management introduced by blockchain has become the focus of enterprises, and this paper studies the enterprise asset management accounting system based on blockchain technology. By using blockchain technology, an asset management accounting system can be built by combining the cost control and responsibility system. Even though the enterprise asset management mode is designed to be efficient, the evaluation index of blockchain is not accurate. The blockchain enterprise asset management mode is analyzed using the DEA effectiveness model combined with the entropy weight method. Combined with the measured data of blockchain technology, the election phase, throughput, and transaction delay are compared, in which the blockchain technology BFT-Raft has a significant improvement in the election phase, the throughput is increased by 101.2TPS, and the transaction delay is reduced by 200~250ms.Through the analysis of the enterprise asset management and the analysis of blockchain de-also asset management efficacy, in which the coverage rate of blockchain technology and the asset yield increase year by year from 2018 to 2021, and reach the highest value of 0.5785 and 0.3612 in 2021, respectively, indicating that M’s overall asset management efficiency of the company has gradually improved with the coverage application of blockchain technology. In summary, the enterprise asset management accounting system based on blockchain technology in this paper can effectively improve the efficiency of enterprise asset management and is of practical significance for the development of enterprise asset management.

Accelerating the rational allocation and optimal integration of urban public resources plays an extremely important role in national and regional development. Based on the public resource allocation model of BP optimization and the analysis method of public resource allocation efficiency, this paper, on the basis of constructing the indicators of the public resource allocation model, calculates and analyzes the data of each indicator from 2012 to 2020 of four cities A, B, C and D in Z, to test the validity of the constructed model and to derive the efficiency of public resource allocation of these four cities. Lastly, the Tobit regression model is employed to explore the factors that influence public resource allocation. In terms of public resource allocation efficiency, 2017, 2018 and 2019 are the concentrated years in which the public resource allocation of the four cities reaches the effective value of 1. The average value of the public resource allocation efficiency of the four cities from 2012 to 2020 is around 0.9, which does not reach the effective value of 1, and the overall allocation efficiency is low. Among the 24 selected influencing factors, 20 influencing factors have a positive effect on public resource allocation efficiency, accounting for 83.3%, of which 11 factors have a significant effect, satisfying P < 0.1.

As a special form of cultural tourism, rural festival activities have a significant driving effect on regional development. Based on the DEA model, this paper constructs a three-stage DEA model by adjusting the decision-making unit and combines the Malmquist index method at each stage to establish a three-stage DEA-Malmquist’s efficiency assessment model to launch the research on the efficiency of rural festival activities. On this basis, the efficiency evaluation index system of rural festival activities was constructed, and 15 rural festivals in place M from 2015 to 2020 were selected as research objects, and the model was applied to analyze their static efficiency and dynamic total factor productivity. The study shows that in the first stage, there are 8 rural festival activities with a comprehensive efficiency greater than 1 (53.33%), and the comprehensive efficiency of the eastern and central parts of Land M is greater than 1, and the overall rural festival activities in this land are at a higher level. Seven rural festivals in Stage 1 had combined efficiencies greater than 1 (46.67%), with both East and Central having combined efficiencies greater than 1. Seven festivals (46.67%) in Stage 3 had combined efficiencies that were DEA effective, and the regional rankings of combined efficiencies for all four years between 2015 and 2020 were East>Central>West. The Malmquist Index mean before adjustment was 1.103, which was a 10.3% improvement, while the mean after adjustment was 1.091, which was a 9.1% improvement. Changes in technical efficiency and the rate of technological progress have a combined impact on the efficiency of rural festivals.