Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach

Wang, Shaohua; Chen, Yanyan; Huang, Jian; Chen, Ning; Lu, Yao

doi:10.1155/2019/5306247

Cited by 15 publications

(15 citation statements)

References 19 publications

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“…e low level of capital investment also caused problems in the information exchange between ethnic areas and the outside world [20][21][22][23]. In today's information age, a large part of the people in ethnic areas have not had access to computers and the Internet, and the coverage of radio and television is also very low.…”

Section: Constraints On Capital and Infrastructurementioning

confidence: 99%

Analysis of the Influence of Human Resources on the Economic Development of Minority Areas Based on Data Mining

Guo

Liu

Zheng

2022

Computational Intelligence and Neuroscience

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In order to break the bottleneck of the human capital stock restricting local economic growth in the typical western regions with backward national economic development, a research on the analysis of the impact of human resources on the economic development of ethnic regions based on data mining is proposed. On the basis of systematically reviewing the current situation and the theoretical basis of the relationship between human capital and economic growth, the method of combining normative research and empirical research is adopted, and the theories of macroeconomics, development economics, and regional economics are synthesized. In the research, the human capital and economic development in a certain western region are analyzed by establishing an econometric model. The results show that the average value of each year is taken as the inspection index, and the contribution rate is 0.0012, which shows that the contribution of human capital stock in economic growth is very small, indicating that physical capital stock is still the main driving force for local economic development. It is concluded that the research provides some relevant recommendations for human capital development to achieve sustainable local economic development.

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Section: Constraints On Capital and Infrastructurementioning

confidence: 99%

Analysis of the Influence of Human Resources on the Economic Development of Minority Areas Based on Data Mining

Guo

Liu

Zheng

2022

Computational Intelligence and Neuroscience

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“…They are all transformed from the general spatial econometric model. The form of the general spatial econometric model is shown as follows [49]:…”

Section: Spatial Durbin Model (Sdm)mentioning

confidence: 99%

The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective

Peng

Liu

Zhang

et al. 2021

IJERPH

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Urban population density distribution contributes towards a deeper understanding of peoples’ activities patterns and urban vibrancy. The associations between the distribution of urban population density and land use are crucial to improve urban spatial structure. Despite numerous studies on population density distribution and land use, the significance of spatial dependence has attained less attention. Based on the Baidu heat map data and points of interests data in the main urban zone of Guangzhou, China, the current paper first investigated the spatial evolution and temporal distribution characteristics of urban population density and examined the spatial spillover influence of land use on it through spatial correlation analysis methods and the spatial Durbin model. The results show that the urban population density distribution is characterized by aggregation in general and varies on weekends and weekdays. The changes in population density within a day present a trend of “rapid growth-gentle decline-rapid growth-rapid decline”. Furthermore, the spatial spillover effects of land use exist and play the same important roles in population density distribution as the direct effects. Additionally, different types of land use show diverse direct effects and spatial spillover effects at various times. These findings suggest that balancing the population density distribution should consider the indirect effect from neighboring areas, which hopefully provide implications for urban planners and policy makers in utilizing the rational allocation of public resources and regarding optimization of urban spatial structure.

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“…The spatial binary weight matrix (SBWM) was formed using GeoDa software (Version 1.16.0.12). We constructed our SBWM with the Rook criterion using the conventional method, holding that the weight is defined as 1 when two areas share a boundary but is valued at 0 otherwise ( 16 , 17 ). However, Hainan Province has no common boundary with any other provinces because of its special geographical location.…”

Section: Methodsmentioning

confidence: 99%

Regional maldistribution of human resources of rehabilitation institutions in China Mainland based on spatial analysis

Chen

Zhao

et al. 2022

Front. Public Health

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ObjectiveWith the demand for rehabilitation has been increasing faster for the aging of China's population, the equity of rehabilitation resource has aroused great concern. This study aimed to analyze the spatial distribution and evolution of the human resources of rehabilitation institutions and propose targeted countermeasures and suggestions to promote optimal allocation.MethodsA total of 31 provinces in China Mainland were identified and geocoded. The spatial weight matrix was introduced to analyze the spatial correlation. Spatial autocorrelation analysis and tests were used to analyze the spatial distribution and evolution characteristics of rehabilitation institutions' human resources in China from 2016 to 2019.ResultsThe average density of rehabilitation staff from 2016 to 2019 has been rising yearly (From 1.60 to 1.88). From 2018 to 2019, the proportion of rehabilitation professionals was higher than 75% in only 5 provinces, and no provinces met 75% from 2016 to 2017. Global Moran's I index from 2016 to 2019 showed no apparent aggregation phenomenon in the allocation of management personnel resources (P > 0.05). Three provinces in western China belonged to the Low-Low area and a province in northeastern China fitted to the Low–High area, with statistically significant differences. In addition, the changes in the spatial distribution and evolution trend of the human resources of rehabilitation institutions in different periods were affected by health policies.ConclusionsAlthough the overall spatial distribution gap of human resource allocation of rehabilitation institutions is shrinking, there are still internal structural defects and a maldistribution at the provincial level. It is necessary to improve the overall number of staff in rehabilitation institutions and to ameliorate the proportion of different types of staffing.

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Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach

Cited by 15 publications

References 19 publications

Analysis of the Influence of Human Resources on the Economic Development of Minority Areas Based on Data Mining

Analysis of the Influence of Human Resources on the Economic Development of Minority Areas Based on Data Mining

The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective

Regional maldistribution of human resources of rehabilitation institutions in China Mainland based on spatial analysis

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