Study on the evolution of B&amp;Bs spatial distribution based on exploratory spatial data analysis (ESDA) and its influencing factors—with Yangtze River Delta as an example

Qiu, Yishu; Zhen-min, Zhu; Huang, Heping; Bing, Zhenhua

doi:10.1080/22797254.2020.1785950

Cited by 13 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1 proposes to make use of rural special industries and cultural connotations, develop leisure tourism and catering B&B that can meet the needs of urban and rural residents, realize the optimal allocation of rural resources, and develop new service industry in the countryside. The integration of agriculture with other industries, especially with tourism, is becoming a new driving force for agricultural economic growth, and rural tourism has become an effective way to promote the re-employment of farmers and improve the rural environment [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Econometric Analysis of Leisure Agriculture and Rural Tourism Scenery Based on Spatial Data Analysis

Liu¹,

Gao

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Exploratory spatial data analysis (ESDA) shows that there is a significant spatial autocorrelation of tourism development in China, which is manifested by the aggregation of spatial distribution. The results of the great likelihood estimation of the spatial lag model show that the parameters ρ of both the total tourism income model and the domestic income model are significantly positive, indicating that the spatial linkage between agricultural and rural tourism income is very strong and the spillover effect of agricultural and rural tourism is larger than that of overall tourism. Tourism superstructure facilities, human resources, and tourism infrastructure are statistically significant and are important influencing factors for overall tourism and agricultural and rural tourism development. And the overall fit of agricultural and rural tourism model is poor. The findings of the study better grasp how to make rural tourism make a greater contribution to the regional economy of Chengdu and maximize its positive role, and put forward relevant countermeasure suggestions, which will provide theoretical guidance and decision-making reference for relevant departments on how to better play the economic effect of tourism, and will also have a realistic reference role on how to develop rural tourism in western cities of China.

show abstract

Section: Introductionmentioning

confidence: 99%

Econometric Analysis of Leisure Agriculture and Rural Tourism Scenery Based on Spatial Data Analysis

Liu¹,

Gao

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…It can measure the aggregation or dispersion of the spatial element attributes of the study object [ 39 ]. It mainly includes global spatial autocorrelation analysis and local spatial autocorrelation analysis [ 40 ]. This study used global and local spatial autocorrelation analysis to reveal the overall spatial correlation and internal correlation characteristics of the medical and health services efficiency in a comprehensive manner.…”

Section: Methodsmentioning

confidence: 99%

Research on Urban Medical and Health Services Efficiency and Its Spatial Correlation in China: Based on Panel Data of 13 Cities in Jiangsu Province

Lin

Chen

et al. 2021

Healthcare

View full text Add to dashboard Cite

The improvement of the efficiency of medical and health services is of great significance for improving the high-quality and efficient medical and health services system and meeting the increasingly diverse health needs of residents. Based on the panel data of 13 cities in Jiangsu Province, this research analyzed the relative effectiveness of medical and health services from 2015 to 2019 using the super efficiency slack-based measure-data envelopment analysis model, and the Malmquist index method was used to explore the changes in the efficiency of medical and health services from a dynamic perspective. Furthermore, the spatial autocorrelation analysis method was used to verify the spatial correlation of medical and health services efficiency. In general, there is room for improvement in the efficiency of medical and health services in 13 cities in Jiangsu Province. There are obvious differences in regional efficiency, and there is a certain spatial correlation. In the future, the medical and health services efficiency of China’s cities should be improved by increasing the investment in high-quality medical and health resources, optimizing their layout and making full use of the spatial spillover effects between neighboring cities to strengthen inter-regional cooperation and exchanges.

show abstract

“…The spatial scope of data collection in this study is mainly the administrative jurisdiction of 16 districts and counties in Shanghai, with the community as the smallest spatial unit. The residential population data studied came from the 2021 population statistics of Shanghai, and the data on HFFs at all levels mainly came from the 2021 network POI data of Gaode Map, the 2021 Google satellite aerial map, the 2021 Shanghai Facilities Statistics Spatial autocorrelation analysis studies the correlation between spatial samples and their surrounding samples, reflecting the distribution characteristics of spatial samples, which are mainly divided into global autocorrelation and local autocorrelation (Qiu et al, 2021. In this paper, the local Moran's I is selected as the measurement index to observe the spatial distribution characteristics of HFFs in Guangzhou.…”

Section: Research Regions and Datamentioning

confidence: 99%

Understanding Accessibility of Health and Fitness with Big Data Techniques: Facility Visualization in Shanghai with Multi-Source Data

Shen

Wu²

2022

JER is an international, peer-reviewed journal that publishes f

View full text Add to dashboard Cite

Accessibility of health and fitness services is important for the rehabilitation in the post-epidemic era. The emergence of multi-source data offers new and timely approaches to understanding health and fitness facilities (HFFs) in cities. Taking Shanghai as an example, this paper obtained the HFFs dataset through platforms such as GaoDe, and crawled data were accurately classified into Street level, District level and Municipal level. Based on spatial data mining, the spatial differentiation of current HFFs was understand. The analysis through Kernel Density Estimation (KDE) and the Multi-mode Two-step Floating Catchment Area Method (M2SFCA) indicates that HFFs basically meet the needs of most residents in the city within their service scope. The Lorentz curve results shows that top 20% community residents enjoy up to 73.66% of HFFs. This shows that there is a large difference in HFF accessibility among community residents. This article presents a visualization example of spatial computing in understanding health accessibility and can provide a timely reference for policy making.

show abstract

Study on the evolution of B&Bs spatial distribution based on exploratory spatial data analysis (ESDA) and its influencing factors—with Yangtze River Delta as an example

Cited by 13 publications

References 8 publications

Econometric Analysis of Leisure Agriculture and Rural Tourism Scenery Based on Spatial Data Analysis

Econometric Analysis of Leisure Agriculture and Rural Tourism Scenery Based on Spatial Data Analysis

Research on Urban Medical and Health Services Efficiency and Its Spatial Correlation in China: Based on Panel Data of 13 Cities in Jiangsu Province

Understanding Accessibility of Health and Fitness with Big Data Techniques: Facility Visualization in Shanghai with Multi-Source Data

Contact Info

Product

Resources

About