Spatial‐Temporal Evolution and Influencing Factors of Urban Green Innovation Efficiency in China

Lu, Chengwu; Chen, Min; Tian, Guixian

doi:10.1155/2022/4047572

Cited by 27 publications

(25 citation statements)

References 52 publications

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“…‘IS’ should attract the attention of all supply chain financial enterprises, and the level of ‘IS’ should be continuously improved. Figure 1 shows the main features and functions of supply chain IS (Lu et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

RETRACTED: The genetic algorithm and BP neural network in financial supply chain management under information sharing

2023

Expert Systems

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In today's global business competition environment, the significant changes in the market environment make it very difficult for supply chain enterprises to gain a place in the fierce market only by their strength. This article will do the following research work to effectively play the role of supply chain management. First, the concepts, and characteristics, related applications of supply chain information sharing (IS) and genetic algorithm back propagation (GABP) neural networks, are expounded. Then, the feasibility of applying BP neural network (BPNN) to evaluate supply chain IS is analysed. Next, the assessment indicator system for IS is constructed from four aspects: IS infrastructure, IS member characteristics, IS content, and the quality of supply chain enterprises. Finally, the principle and algorithm of BPNN are analysed, the network model is constructed, the BPNN process based on GA is designed, and every step in the process is explained in detail. The sample input is provided for the network model by obtaining and sorting data. The supply chain IS assessment model based on the GABP neural network is constructed. The results show that the assessment model of supply chain IS based on the GABP neural network has high accuracy, and the highest network accuracy reaches 95.01%, which proves that the assessment model based on BPNN has certain advantages for the supply chain IS of the financial industry.

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Section: Methodsmentioning

confidence: 99%

RETRACTED: The genetic algorithm and BP neural network in financial supply chain management under information sharing

2023

Expert Systems

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“…Based on the measured regional green development performance or green development level, scholars have also carried out deeper research. One avenue is the spatial differentiation of regional green development [37,38], and the other is the factors that affect the level of regional green development and their spatial spillover effects [11][12][13][14][15]39]. For example, Zhao et al [37] found that the green innovation efficiency in eastern, central, and western China is basically on the rise, but that there are differences in the upward trend, and this is based on the Tobit regression model to explore the impact of green finance and environmental regulation on green innovation efficiency in this region.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The intensity of environmental regulation and the degree of opening to the outside world will also inhibit urban green innovation. Lu et al [12] measured the development level of green intelligence in prefecture-level cities from 2005 to 2018 and explored both its temporal and its spatial evolution characteristics, and they used quantile regression tests and threshold regression to analyze its influencing factors and threshold effects. It was found that the level of opening to the outside world and the size of the city have a significant positive impact, while the level of economic development and the size of the government have a negative impact.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Based on the evaluation of green development performance, relevant research has analyzed the spatial differentiation of regional green development, and it has analyzed its influencing factors and spatial spillover with different methods. The influencing factors discussed include green finance, environmental regulation, city size, government financial support, industrial structure, economic development level, opening-up degree, and human capital level [11][12][13][14][15][16][17]. To replenish the shortcomings of these approaches, this paper conducts an investigation of policy implementation instead of theoretically and empirically trying to establish a multi-dimensional and comprehensive evaluation index of private enterprises, thereby grasping the actual situation of green development.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatial Characteristics and Influencing Factors of Green Development Progress Level of Private Enterprises in China: Based on Large Collection Surveys

Rong,

Zhang,

Yang

et al. 2023

Sustainability

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As the market subject of China’s economic development, private enterprises play an important role in fighting against pollution and solving ecological and environmental problems. It is especially important to evaluate the green development progress of Chinese private enterprises in the epidemic era. This paper conducts a questionnaire survey on 10,623 private enterprises in 31 provinces of China, and based on 6223 industrial survey results, it focuses on the production and operation status of private enterprises in terms of pollution reduction performance, energy saving, and carbon reduction intensity in order to construct a green development progress index. The spatial Moran index test and the spatial Durbin model are used to analyze the regional correlations and influencing factors of green development progress in China. The results show that the green development of enterprises with a main business income of more than 100 million CNY and key areas such as Fenwei Plain have improved significantly in 2021, especially with the increase in a private enterprise scale, the carbon reduction regime, the pollution abatement regime, and the pollution control manner, and because the investment, profitability, and pollution discharge of private enterprises is more significant. The indexes of the provinces in the southeast coastal area and the northeastern region of China are the highest and lowest, respectively, in terms of pollution, which is demonstrated by the spatial aggregation effect on the surrounding areas by Moran local index analysis. The urbanization level and government financial support for environmental protection are just two of the negative factors regarding this issue, while the economic development level and industrial structure are positive factors that have a spatial spillover effect.

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“…Continuing to deepen sustainable development, green and ecological benefits have become some of the main goals in the study of land use benefits. Land use is closely related to population growth, urbanization quality and environmental issues [13,14] and based on the connotation of land use benefit, some researchers quantified the green land use benefit of 284 cities at the provincial level and above in China based on green development goals, and pointed out that there are obvious spatial differences [15][16][17]. Studies from urban and rural land cover perspectives point out the differences in ecosystem functions between urban and rural areas [18], while the level of green land use has been evaluated from the perspective of the coupling coordination between land use and economic growth [19].…”

Section: Introductionmentioning

confidence: 99%

An Evaluation and Promotion Strategy of Green Land Use Benefits in China: A Case Study of the Beijing–Tianjin–Hebei Region

Wen-ying

Sun

et al. 2022

Land

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Green development is the inevitable choice for global sustainable development, and China has chosen green development as its national strategy. Land use changes will affect a soil’s organic matter by changing the land’s productivity, soil quality and fertility. It is of great significance for ensuring soil fertility, improving the environment and promoting the carbon cycle that the concept of green development is implemented in the process of land use activity. Establishing an indicator system and evaluation method for a green land use benefit evaluation suitable for green development is helpful for strengthening the responsibility and consciousness of such land use, and to provide theoretical guidance and decision-making references for promoting such developments and evaluations. In this study, based on a connotation analysis of green land use, the entropy weight method and BP (Back Propagation) neural network model method were used to construct an evaluation index system for green land use benefits, including four criterion layers and eighteen evaluation indexes, and the entropy-BP neural network evaluation method was proposed to reveal the problems in green land use benefits in the Beijing–Tianjin–Hebei region. The results showed that the green land use benefit level in the region was low, while the spatial pattern was high in the north, low in the middle and high in the south. Langfang, Beijing and Handan were the lowest centers of green land ecological benefit, while Beijing and Tianjin were the lowest centers of green land economic benefit. The green governance benefit and green space benefit were in a relative spatial equilibrium. The cultivated land area, forestry products, sewage centralized treatment degree and built-up area ratio were the most important influences on the green ecological benefit, green economic benefit, green governance benefit and green space benefit, respectively. The entropy-BP neural network evaluation system and method have certain applications in the design of relevant assessment reward-and-punishment systems. Accelerating the optimization of the Beijing–Tianjin–Hebei territorial space’s development and utilization pattern, and constructing a green benefit sharing mechanism of land use, are important strategies to improve the benefits of green land use.

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Spatial‐Temporal Evolution and Influencing Factors of Urban Green Innovation Efficiency in China

Cited by 27 publications

References 52 publications

RETRACTED: The genetic algorithm and BP neural network in financial supply chain management under information sharing

RETRACTED: The genetic algorithm and BP neural network in financial supply chain management under information sharing

Spatial Characteristics and Influencing Factors of Green Development Progress Level of Private Enterprises in China: Based on Large Collection Surveys

An Evaluation and Promotion Strategy of Green Land Use Benefits in China: A Case Study of the Beijing–Tianjin–Hebei Region

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