Study on the Rural Revitalization and Urban-Rural Integration Efficiency in Anhui Province Based on Game Cross-Efficiency DEA Model

Sun, Shanhui; Zhang, Ni-Ni; Liu, Jia‐Bao

doi:10.1155/2022/7373435

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Another future research direction to be considered is expanding the size of research samples, including Chinese "211 Project" universities and additional excellent universities in the research system so as to more representatively reflect the level of Chinese higher education. In addition, future research can also consider the application of novel DEA methods to higher education performance assessment, such as the combination of DEA with artificial intelligence methods [24,41,42] and DEA with game theory [43] and PCA [44].…”

Section: Limitationsmentioning

confidence: 99%

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

2023

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In recent years, the increasingly fierce competition among higher education institutions (HEIs), the finite resources, and the enormous influence of the COVID-19 epidemic on higher education have made it especially important to evaluate the performance of Chinese higher education institutions. This paper utilizes the DEA-BCC and Malmquist index to analyze the efficiency and productivity of 34 Chinese “985 Project” universities in the period 2017–2021. The indicator system includes three inputs and five outputs, contained in Model 1 and Model 2 for comparative analysis. The results demonstrate that the COVID-19 epidemic has had a considerable negative impact on Chinese higher education, and has induced the reduction of technical efficiency and productivity. Setting up online MOOCs is conducive to enhancing the efficiency and productivity of HEIs; in addition, the efficiency mentioned varies noticeably among different university levels, and there is no significant difference in different university types and geographical locations.

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Section: Limitationsmentioning

confidence: 99%

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

2023

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“…Furthermore, the industrial structure of Anhui Province underwent tremendous changes during the study period, resulting in an imbalance in the spatial layout structure of construction land within the province. This resulted in significant differences in land-use efficiency among cities and regions, posing obstacles to achieving high-quality and sustainable development in Anhui Province [32][33][34][35]. Therefore, it is crucial to address the urgent issues of rational adjustment of the urban spatial layout, efficient allocation of land resources, and the realization of the connotative development in Anhui cities.…”

Section: Data Sourcesmentioning

confidence: 99%

Spatial-Temporal Evolution and Driving Mechanism of Urban Land Use Efficiency Based on T-DEA Model: A Case Study of Anhui Province, China

Liu

Wang

et al. 2023

Sustainability

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As China’s urbanization has shifted from high-speed to high-quality development, Urban Land Use Efficiency (ULUE) has become an important scale for evaluating urban connotative development. However, existing research has paid less attention to errors caused by different urban environmental factors and random disturbances in ULUE. Therefore, the purpose of this study is to eliminate the impact of environmental factors and random disturbances on ULUE measurement results by placing different cities under the same environmental conditions. First, a three-stage DEA envelopment analysis (T-DEA) model is introduced to calculate the ULUE of 16 prefecture-level cities in Anhui Province from 2001 to 2020. On this basis, the kernel density estimation model, gravity center model, and geographic detector models are used to study the spatial and temporal evolution and driving factors. The results show that (1) the ULUE increases nonlinearly with time, with an increase of 12.74%; (2) the overall peak of ULUE is on the rise, and changes from a single peak to a multi-peak, indicating that ULUE is constantly improving and that there is multi-level differentiation between different cities; (3) during the study period, the center of gravity of the ULUE value moved 22.66 km to the northwest; the overall moving distance was small, and the moving rate was slow; and (4) the influence of the interaction of double driving factors on ULUE is significantly greater than that of a single driving factor, and the factors of urban built-up area and degree of openness, as the key driving factors affecting ULUE, also have a degree of duality. In addition, to achieve efficient urban land use and to coordinate the environmental differences faced by different cities, the government must formulate systematic policies and development strategies considering the spatial characteristics of urban land use efficiency and the complexity of the driving factors.

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Does the digital economy promote the high–quality development of urban–rural integration? experience analysis based on panel data of 30 provinces in China

Xu,

Lian,

Niu

et al. 2024

Environ Dev Sustain

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Study on the Rural Revitalization and Urban-Rural Integration Efficiency in Anhui Province Based on Game Cross-Efficiency DEA Model

Cited by 3 publications

References 10 publications

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

Spatial-Temporal Evolution and Driving Mechanism of Urban Land Use Efficiency Based on T-DEA Model: A Case Study of Anhui Province, China

Does the digital economy promote the high–quality development of urban–rural integration? experience analysis based on panel data of 30 provinces in China

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