Level Evaluation Index Research Articles

Spatio-temporal patterns and driving factors of green development level in alpine meadow regions: A case study in Gannan Tibetan Autonomous Prefecture

Green development is an approach that harmonizes human beings with nature and leads to sustainable social and economic development. However, the factors influencing the level of green development are uncertain due to regional differences, especially in the alpine meadow regions. To explore the factors affecting green development in the alpine meadow region, we took the Gannan Tibetan Autonomous Prefecture as an example. Through a green development level evaluation index system, the DPSIR (Driver, Pressure, State, Impact, and Response) was constructed to comprehensively evaluate and analyze the green development level of the study area from 1990 to 2020. On this basis, the key influencing factors of the green development level was analyzed based on the GeoDetector. The findings indicate that the total level of green development in Gannan has an upward trend within the range of 0.044–0.535, moving towards high quality and sustainable development. Except for 2005, the spatial clustering characteristics of the green development level did not display obvious high values of spatial autocorrelation. The green development space is concentrated and stable, and the centre of gravity is in Zhuoni. The impact and response dimensions make the greatest contribution to green development. Different evaluation indicators have different impacts on green development during the study period. Specifically, people’s productive lives, the impact of social production and positive policy responses are the main factors contributing to green development. The findings will provide theoretical basis and case support for ecological security and green sustainable development in the alpine meadow regions.

Evaluation of the Development Level of Green Transportation in National Central Cities

Green transportation is the core embodiment of ecological civilization and the concept of green development within the field of transportation, and it is an important strategic choice for sustainable urban development. National central cities represent the highest level in China’s urban system planning. This paper aims to evaluate the level of green transportation development in national central cities. It established a set of 29 specific evaluation indicators from five dimensions: basic indicators, green transportation infrastructure, traffic environmental protection, traffic travel, and traffic safety. It constructed an evaluation index system for the development level of green transportation. The entropy weight TOPSIS method was utilized to evaluate the development levels of green transportation in nine national central cities from 2020 to 2022. An obstacle degree model was constructed to identify key obstacle factors at both the criterion and indicator layers of the green transportation development level evaluation index system for national central cities. Suggestions were proposed from five aspects: establishing a comprehensive policy framework, promoting regional collaborative development, accelerating infrastructure construction, improving transportation service quality, and fostering the green upgrading of industries. The results showed that the comprehensive ranking of green transportation development levels among the national central cities from high to low for the years 2020–2022 was as follows: Shanghai, Chongqing, Chengdu, Beijing, Guangzhou, Tianjin, Wuhan, Xi’an, Zhengzhou. In terms of the regional spatial layout, the green transportation development levels of the nine national central cities generally exhibited a “high on the periphery, low in the center” distribution characteristic. The comprehensive ranking of the obstacle degree in the criterion layer was as follows: basic indicators, traffic travel, green transportation infrastructure, traffic environmental protection, traffic safety. After screening the criteria level where the obstacle degree calculation results are above 15%, traffic safety is eliminated. The nine cities, which were located in different regions, generally maintained consistent internal obstacle factors and their order. The top five indicators with the highest frequency of obstacle degrees at the indicator layer were as follows: total passenger transport volume, number of taxis, new energy vehicle production, expenditure for transportation, and total freight transport volume. The specific key obstacle factors at the indicator level were different in the nine cities.

Regional differences, distributional dynamics and convergence of multidimensional food security levels in China.

Food security is one of the important issues in the current world development process. The article takes 31 provinces (districts and cities) in China as the research object and constructs a multidimensional food security level evaluation index system from four dimensions: quantitative security, nutritional security, ecological security, and capacity security. Using the entropy method, China's food security index was calculated for the ten-year period from 2013 to 2022. Overall, China's food security level showed an upward trend during the decade, with the provinces of Shandong, Heilongjiang, and Henan having the highest level of security. The distribution dynamics of food security and its spatiotemporal evolution in the seven regions were examined using the Dagum Gini coefficient and its decomposition, and the absolute and conditional convergence of food security in the different areas was verified. The results of the study show that the provinces within East China have the largest gap in food security levels between them, and there is absolute β-convergence. Looking at China as a whole, the development of its food security level is characterized by significant convergence, which means that provinces with a low level of food security will have a faster rate of growth than those with a high level of food security, resulting in a gradual narrowing of the gap in food security levels between provinces.

The impact of digital economy on green total factor productivity considering the labor-technology-pollution factors

The digital economy provides new impetus for the high-quality development of manufacturing industry. Through the DEA-Malmquist model and panel regression model, this paper confirmed that there is a positive and significant relationship between the development of digital economy and the green total factor productivity (GTFP) of manufacturing industry. The research result is as follows: (1) the development of digital economy can enhance the overall GTFP of manufacturing industry. (2) The green technology progress brought by the development of digital economy is the main path to promote the GTFP of manufacturing industry. (3) The heterogeneity analysis shows that the impact of digital economy on GTFP of high pollution manufacturing industry is significantly positive, the impact of labor-intensive manufacturing industry is significantly negative, and the impact of technology intensive manufacturing industry is not obvious. The contributions of this study are as follow. In terms of theory, this study theoretically continues Solow’s classical theory, demonstrating the scientific nature of digital technology progress in promoting GTFP growth. In empirical analysis, this study build a new digital economy development level evaluation index system based on the perspective of manufacturing industry. In addition, this study also add a labor-technology-pollution perspective for the development of relevant policies.

Carbon Emission Reduction Effects of the Digital Economy: Mechanisms and Evidence from 282 Cities in China

The digital economy has great potential to boost innovation and social productivity, and it plays an important role in helping to achieve carbon peak and carbon neutrality. This study focuses on analyzing and testing the role of the digital economy in promoting carbon reduction in Chinese cities. Based on panel data of 282 cities in China from 2011 to 2019, this study measured the development level of the digital economy and carbon emission intensity by constructing a digital economy development level evaluation index system and a carbon emission inversion model, respectively. It was found that the digital economy can significantly reduce urban carbon emissions by promoting industrial structure upgrading and green innovation, and the digital economy will have a more obvious promotion effect on urban carbon emission reduction over time. This conclusion was found to be valid after we performed robustness tests such as the instrumental variable method, quasi-experimental analysis, and placebo test. Furthermore, heterogeneity analysis showed that eastern, regenerative, and provincial capital cities are better able to promote carbon emission reduction under the development of the digital economy. This study provides new empirical evidence at the city level for developing the digital economy to reduce urban carbon emissions and acts as a useful reference for developing countries to realize “smart carbon emission reduction”.

A preliminary study on the evaluation index system of low carbon city development level

Based on the clarification of the DPSIR model and the development history and specific connotation of low carbon cities, this paper proposes the design basis, design principles and design steps of the low carbon city development level evaluation index system based on the DPSIR model by analysing the application of the DPSIR model in the evaluation of the development level of low carbon cities, and forms the low carbon city development level evaluation index system.

Study of the spatial divergence features and motivating factors of energy green consumption levels in "2+26" cities.

The level of energy green consumption is an essential factor influencing China's economy's high-quality development. In this paper, we select relevant panel data from 2010 to 2019 for 28 cities in Beijing-Tianjin-Hebei and surrounding areas, and use the DPSIR model and spatial econometric model to analyze the spatial divergence characteristics and driving factors of the energy green consumption index based on the construction of the energy green consumption level evaluation index system and index measurement. The results of this research are as follows: (1) The energy green consumption index has a distribution pattern of "high in the east and low in the west, high in the north, and low in the south," and the driving force (D) and response force (I) are the key factors influencing the spatial variation of the energy green consumption index. (2) The measurement results show that GDP per capita and built-up green coverage have a considerable positive effect on the energy green consumption index, whereas non-domestic energy structure has a significant inhibitory effect. (3) In terms of spatial spillover effects, greening coverage of built-up areas, industrial structure, and domestic energy structure, all have positive effects on neighboring regions' energy green consumption indexes, with positive spatial spillover effects, whereas GDP per capita, urbanization level, and non-domestic energy structure, all have negative spatial spillover effects. In light of the issues at hand, this paper suggests making good efforts to create and put into practice laws and policy norms, cultivate green energy-saving markets, vigorously promote the use and promotion of energy-saving technologies, and lower energy consumption in secondary industry and domestic consumption. The study's findings can help advance the modernization of the region's industrial structure and the growth of a green economy by providing the local government with a reference point for timely policy adjustments.

Study on the Evolution of the Spatial-Temporal Pattern and the Influencing Mechanism of the Green Development Level of the Shandong Peninsula Urban Agglomeration

Improving the level of green development is an inevitable requirement for promoting the construction of an ecological civilization. In this paper, through a green development level evaluation index system, the CRITIC weight method is used to comprehensively evaluate and analyze the green development level of the Shandong Peninsula Urban Agglomeration from 2007 to 2019. On this basis, a panel data model was constructed to analyze the key influencing factors of the green development level of the Shandong Peninsula Urban Agglomeration. Studies have shown that (1) the level of green development in the Shandong Peninsula Urban Agglomeration from 2007 to 2019 has been steadily improved, but the overall level is still at a low level, with significant differences among the cities. (2) Qingdao and Jinan are the two growth poles of the green development level of Shandong Peninsula Urban Agglomeration. The dual-core leading effect is obvious, forming a spatial pattern in which the green development level of the eastern and central regions is higher than that of other regions’ green development level. (3) Weihai, Dongying, and Qingdao are high-level cities of green development, while Jinan, Yantai, Zibo, Tai’an, and Linyi are medium-level cities of green development. The green development level of other cities is relatively low, and the high-level cities of green development are mostly the Jiaodong economic circle and provincial capital economic circle. (4) Industrial structure, scientific and technological innovation, and government policies are the critical factors in promoting the green development of the Shandong Peninsula Urban Agglomeration.

Research on Reservoir Operation Rules Extraction Based on Decision Tree and Its Ensemble Model

Reservoir operation rules, as an important tool to guide reservoir operation, are not only the decision-making reference in the period of reservoir planning and design, but also one of the key technologies affecting the comprehensive benefits of the reservoir in the stage of operation and management. Therefore, the reservoir operation rules extraction method based on decision tree and its ensemble model was proposed in this paper. The time index, early water level, inflow, outflow and current inflow were selected to form the input factor set with the reservoir scheduling principle. Comprehensively considering the characteristics of operation data and the principle of decision tree, reservoir water level at the end of period was determined as the model output and then the corresponding simulated water level evaluation index was proposed based on the reservoir regulation capacity. Furthermore, in view of the difficulties in selecting input factors and calibrating the hyperparameters of models, the F test method and mutual information were used as the correlation evaluation index of model input factors, and the Tree-structured Parzen Estimator was introduced. Finally, the proposed methods were applied in Ahai and Ertan Reservoirs, the results showed that the extracted operation rules have high precision, which demonstrated the proposed methods is practicable and effective in the reservoir operation rule extraction.

Evaluation research on the regional green development——take Liuzhou, Guangxi Zhuang autonomous region as an example

The Green Economy Development is an inevitable way for cities to develop with high quality. Based on the theoretical connotation of green development and the actual development of Liuzhou in Guangxi Zhuang Autonomous Region, this paper constructed a regional green development level evaluation index system from three aspects: economic development, sustainability and green development capabilities. Criteria Importance Through Inter-criteria Correlation (CRITIC) method was applied to measure and analyze the level of green development of Liuzhou City. From 2011 to 2018, the total level of green development of Liuzhou showed a fluctuated upward trend. Among them, the total level from 2011 to 2012 showed an upward trend, and it fell back from 2012 to 2013, then the total level increased greatly from 2013 to 2017 and decreased slightly from 2017 to 2018, and the peak of 0.572 appeared in 2017. The following suggestions were put forward based on the analysis. First, Liuzhou should promote the high-quality development of the tertiary industry, accelerate the transformation of the industrial structure, and set the appropriate fixed asset investment target. Second, Liuzhou should promote energy conservation and emission reduction, increase environmental protection, and focus on the concentration of atmospheric particulate matter and the comprehensive utilization rate of industrial solid waste. Finally, Liuzhou should increase funding for scientific and technological research and pay attention to talent introduction and training.

Evaluation of automobile parts design scheme for intelligent manufacturing

Aiming at the selection of modern auto parts design schemes, an evaluation method of automobile parts design scheme for intelligent manufacturing is proposed. Considered the environment-friendly factors and traditional manufacturing factors, the evaluation index system of automobile parts design scheme was established, which taken technology, environment, economy and quality reliability as the first level evaluation index, and 12 second level indexes under the first level index. The game theory method was used to comprehensively consider the proportion of subjective and objective weights to determine the composite weight of each index. Aimed at the certainty and uncertainty of the evaluation index, the set pair analysis relative closeness method was used to calculate the composite weight and established the model. Three sets of automobile panel design schemes of a company were selected, and the mathematical model was used to calculate them. With the help of C language program, the advantages and disadvantages of the three design schemes were evaluated, and the optimal scheme was obtained. The calculation example proves that the method is true and effective, conforms to the background of modern intelligent manufacturing, and the calculation is simple, and has good feasibility and practicability.

Application of Data Mining in Effect Evaluation of Lean Management

Quantitative evaluation is an important part of enterprise diagnosis, which promotes the scientific and modern management of enterprises. At present, the existing enterprise management evaluation methods cannot complete the mining of enterprise index data, which leads to large error and low significance coefficient in enterprise management evaluation. Therefore, the application of data mining in enterprise lean management effect evaluation is put forward. The process and main functions of data mining are analyzed; data mining algorithm is used to establish the evaluation index system of lean management effect and calculate the index weight. Using the association rules method in data mining, according to the parameters of enterprise lean management level evaluation index and weight value, through the fuzzy set transformation idea, the fuzzy boundary of each index and factor is described by the membership degree, the fuzzy judgment matrix is constructed, and the final evaluation result is obtained by multilayer compound calculation. Experimental results show that this study has a high significance coefficient, and the proposed evaluation method of enterprise lean management effect has ideal accuracy and short time consumption. In practical application, the cumulative contribution rate is higher and has higher stability.

Resources and Environment Carrying Capacity, Social Development and Their Decoupling Relationship: A Case Study of Hubei Province, China.

With the rapid urbanization in recent decades, resource shortage and environmental damage have hindered the process of urban sustainable development (SD). As a yardstick of sustainable development, the evaluation of resources and environment carrying capacity (RECC) and its decoupling relationship with social comprehensive development index (SCDI) are of great significance. In this paper, RECC and SCDI are taken as research objects to establish resource and environment system evaluation index system and social comprehensive development level evaluation index system, respectively. Then, the RECC and SCDI of 17 cities in Hubei province during 2009–2018 are calculated by the projection pursuit model based on genetic algorithm, and their spatial-temporal variance characteristics are analyzed. On this basis, the RECC-SCDI Tapio decoupling model is constructed to explore the decoupling relationship between RECC and SCDI. The result shows that: (1) The RECC of Hubei shows a V-shaped development trend during 2009–2018. The SCDI of Hubei rose steadily during 2009–2018. (2) RECC in western and eastern Hubei Province is higher than that in central Hubei Province. SCDI in eastern and central Hubei Province is higher than that in the west. (3) 11 of the 17 cities in Hubei Province have got rid of excessive dependence on resources environment for social development. The study could contribute to scientific and effective policies be formulated by government to promote urban sustainable development.

Constructing an Evaluation Index System for China’s Low-Carbon Tourism Region—An Example from the Daxinganling Region

With the intensification of global warming, the development of low-carbon tourism is not only an inevitable requirement for human development, but also an important way to enhance tourism, improve the quality of tourism, and obtain greater economic and social benefits from tourism. Scientifically and effectively constructing a low-carbon tourism development level evaluation index system is conducive to the healthy and sustainable development of the tourism industry. However, the current evaluation of the development level of low-carbon tourism mainly focuses on low-carbon development, energy conservation, and emission reduction. There are few studies and a lack of specific empirical research evaluating the development of low-carbon tourism. In this research, the Delphi method and analytic hierarchy process were used for data collection and corresponding weight analysis. This research refers to the results of existing studies on low-carbon tourism evaluation index systems, and constructs an objective and quantitative evaluation model. It establishes a low-carbon tourism development evaluation model with 34 specific indicators from the three dimensions of the tourism economic support level, the tourism low-carbon development level, and the tourism policy support level. The research results were applied to the Daxinganling region for verification. The results show that the development of tourism in the Daxinganling region has changed from a mode dominated by economic interests to a mode in which tourism-related parties begin to seek effective low-carbon methods to maintain low-carbon tourism activities. In addition, the Daxinganling region has the lowest level of low-carbon tourism development and the highest level of financial support. Based on the research conclusions, corresponding suggestions for the development of low-carbon tourism in the Daxinganling region are provided. The results are also intended to provide a reference point in the optimization of low-carbon tourism development models in this and other regions.

A Study on the Effect of Organizational Safety and Health Management Activities on Safety and Health Performance : Focusing on the Case of Public Organizations Safety Activity Level Evaluation

The purpose of this study is to investigate the effect of organizational safety and health management activities on safety and health performance by using the results of safety activity level evaluation of public organizations. To this end, a research model was established by using three fields as independent variables among the four areas of the safety activity level evaluation index: safety and health system, safety and health activity plan, and safety and health activity level, and the safety and health activity performance field as a dependent variable. Correlation analysis and regression analysis between major variables were performed. As a result of the correlation analysis, the safety and health activity performance had a significant positive (+) correlation with all of the safety and health system, safety and health activity plan, and safety and health activity level. The safety and health system had a significant positive (+) correlation with the safety and health activity plan and safety and health activity level, and the safety and health activity plan had a significant positive (+) correlation with the safety and health activity level. And as a result of the regression analysis, it was found that the organization’s safety and health system, safety and health activity plan, and safety and health activity level all had a significant positive (+) effect on safety and health activity performance.

Future Development Trend of “New Retail” and E-Commerce Based on Big Data

In recent years, my country’s “new retail” and E-Commerce (EC) have developed vigorously and have become the world’s largest offline shopping market on the Internet. At the same time, with the development of information technologies such as cloud computing and the Internet of Things, rapidly expanding data has brought mankind into the era of big data(BD). It has become possible to use BD technology to analyze the development of regional “new retail” and future EC and provide corresponding guidance. The purpose of this article is to study the future development trend of “new retail” and EC based on BD technology. Based on the development status of “new retail” and EC in Anhui Province, this paper selects Hefei and Huangshan as the research objects. After referring to numerous theoretical studies, this article has determined the factors affecting the development of regional EC, such as informatization infrastructure, logistics services, etc. At the same time, it uses the range of standardization method and selects representative indicators to construct a regional “new retail” and EC development level evaluation index system. Finally, combining the evaluation results and the development status of various regions, taking Hefei and Huangshan as examples, proposed the concept of building a regional third-party “new retail” and EC trading platform and creating regional product integration services. This article combines BD to deeply analyze the influencing factors that traditional trade and circulation companies face in the process of strategic transformation in the development of “new retail”. This article explores the strategic transformation paths and measures for traditional trade and circulation enterprises to develop the “new retail” business model Draw on. Investigation and research show that, through the evaluation model, this article concludes that Hefei’s online retail sales are higher than Huangshan’s, with an annual growth rate of more than 3%, which is also high relative to the province’s growth rate.

Three-dimensional evaluation method for asphalt pavement texture characteristics

To supplement the research on the evaluation method of asphalt pavement texture, novel three-dimensional (3D) methods are proposed. First, 18 different pavement textures were measured in laboratory from asphalt mixture specimens using laser texture scanner (LTS), and the macro-texture and micro-texture were extracted based on spectrum analysis techniques. Then, macro-texture level evaluation indices f8mac and f9mac together with micro-texture level evaluation indices f8mic and f9mic were proposed based on the gray level co-occurrence matrix (GLCM) method, and the determination of hyperparameters angle θ, pixel distance d and vertical resolution v were discussed. Through the correlation analysis and compared with existing conventional evaluation indices, the optimum pavement texture level evaluation index was selected and verified. Additionally, the evaluation index σ of distribution uniformity of pavement texture (DUPT) was proposed based on the uniformity of deviations between sub-surfaces and the average surface of pavement texture. Finally, the correlations of σ with texture profiles were studied. The results show that f8mac and f8mic are determined as the optimum indices for pavement texture level. Mean texture depth has significant correlation with f8mac, and the correlation coefficient R is 0.9611; friction coefficient μ has significant correlation with f8mic, and the R is 0.9422. θ is recommended to be 90°; d and v are set to 52 pixels (0.4953 mm) and 0.01 mm respectively for macro-texture level evaluation; d and v are set to 1 pixel (0.0095 mm) and 0.003 mm respectively for micro-texture level evaluation. Moreover, the effectiveness of σ is also validated by calibrating with standard grooved surface. It can be concluded that the proposed indices in this study are suitable to the evaluation of pavement texture level and pavement texture distribution.

An adaptability evaluation of large-scale solar energy for hot water application based on energy-economic-environment consideration: A case study of city-residential buildings in China

Evaluation of city-residential solar hot water systems (SHWS) in a large-scale area is a complicated topic since many endogenous and exogenous factors would affect the results. This paper presents an adaptability evaluation model for regional SHWS in city-residential buildings through using multiple attribute-decision methods. The evaluation factors, including six variable parameters and eight constant parameters, were selected based on energy-economic-environment consideration. In addition, the provincial databases of the utilization of solar energy resources in China were established and 31 provincial capital cities were investigated. The results are summarized as follows: 1) the five most important factors, with summing weights accounting for 54% in total, are the solar radiation intensity, payback period, solar fraction, installation area, and water supply temperature; 2) compared with the evaluation methods regarding different factors, energy-economic-environment adaptability evaluation method is more reliable, especially when there are huge differences existing in solar energy resources, economic levels, and energy prices. 3) sensitivity analysis shows that it has little influence on the evaluation results when the weight of the first level evaluation index changes within 25%. The conclusions in this paper provide valuable guidance for renewable energy planner and decision makers.

How does the urbanization level change in the Yangtze River economic belt, China? A multi-scale evaluation using DMSP/OLS nighttime light data

Based on DMSP/OLS nighttime light data, we select the Yangtze River Economic Belt (YREB) as the research area to evaluate the urbanization level of the YREB at provincial, regional, and county scales. First, we construct the compounded night light index (CNLI) based on the nighttime light data by extracting the integrated light intensity (I) and the built-up area (S) of the Yangtze River economic belt from 1992 to 2012, and we respectively calculate the CNLI of the YREB at the province, regional and county scales of the YREB such that we can comprehensively analyze the spatial and temporal distribution characteristics and dynamic changes of the process of urbanization in the YREB. Second, we construct two traditional urbanization level evaluation index models based on socio-economic statistics: The integrated urbanization level index model (IU) and the urbanization composite index model (Cf), which are used to respectively calculate the urbanization levels at the province, region, and county scales of the YREB. Finally, we establish a multi-scale urbanization model of CNLI, IU, and Cf in order to perform correlation analysis of CNLI, IU, and Cf on different scales. The results show that CNLI can objectively reflect the development status of urbanization level, and provide a new index and method for better monitoring the state of urban development and evaluating the annual change of urbanization.

An empirical study on the potential of land resources utilization in urban agglomeration development zones based on combination analysis

To alleviate the contradiction between human and land caused by the limitation of land resources and the irreversibility of land use in the development zone of urban agglomeration, 24 indexes were selected from four aspects: land use status, resource security, economic feasibility, and social acceptability to establish the level evaluation index system for the sustainable use of land resources in Baoding high-tech zone; also, the combination weighting method was used to determine the development level. The index weight of land resource utilization potential in the development zone was established. The subjective and objective linear combination was also established to obtain the proportion of subjective and objective. The multi-factor comprehensive evaluation model was used to evaluate the sustainable utilization degree of land in the high-tech zone. The comprehensive analysis of land-intensive use potential was made from five aspects: expansion potential, structure potential, intensity potential, management potential, and the number of years of land available; the analysis of the limiting factors and the combination of these factors of the land in the development zone was made to obtain the natural index after the renovation, and the natural quality potential of the cultivated land renovation was obtained according to the difference of the natural index before and after the renovation. The empirical results show that the high-tech zone’s land-use rationality index is relatively high during 2014-2018. During the evaluation period, the index continued to rise; the high-tech zone's resource security score was low, and there was no change during the evaluation period, which is basically at a low level. During the five years, the high-tech zone’s land-use sustainability has experienced the fluctuation process of first rising and then declining, which is in the stage of medium sustainable development. In the future, the potential for improvement is enormous. The prospect of the high-tech zone’s exploitable land structure is small, and the land structure is relatively reasonable, which is in line with the development orientation of the high-tech site. But the industrial land intensity in the zone also has a specific potential for excavation. The high-value areas of the natural quality potential of the land improvement in the high-tech site are mainly distributed in the west, northeast, and a few in the north and south.