scholarly journals A longitudinal study of e-commerce diversity in Europe

2021 ◽  
Author(s):  
Adam Sadowski ◽  
Karolina Lewandowska-Gwarda ◽  
Renata Pisarek-Bartoszewska ◽  
Per Engelseth
Keyword(s):  
Spatial Data ◽  
Online Shopping ◽  
Statistical Data ◽  
Spatial Diversity ◽  
Regional Level ◽  
Spatial Data Analysis ◽  
Household Preferences ◽  
Global And Local ◽  
Data Analysis Methods ◽  
Local Spatial Autocorrelation

AbstractOwing to increased access to the Internet and the development of electronic commerce, e-commerce has become a common method of shopping in all countries. The purpose of this study is more precisely to research e-commerce diversity in Europe at the regional level and develop the conception of “E-commerce Supply Chain Management”. Statistical data derived from the European Statistical Office were applied to analyse the spatial diversity of e-retailing. Assessments of the regional diversity of e-retailing applied geographic information systems and exploratory spatial data analysis methods such us global and local spatial autocorrelation statistics. Clusters of regions with similar household preferences related to online shopping were identified. A spatial visualisation of the e-retailing diversity phenomenon may be utilised for the reconfiguration of supply chains and to adapt them to actual household preferences related to shopping methods.

Regionální disparity ve voličském chování: Prostorová analýza voličské podpory České pirátské strany v krajských volbách

2021 ◽  
Author(s):  
Pavel Maškarinec
Keyword(s):  
Spatial Data ◽  
Regional Policy ◽  
Regional Governance ◽  
Regional Level ◽  
Capital City ◽  
Spatial Data Analysis ◽  
Regional Government ◽  
Regional Politics ◽  
Electoral Support ◽  
Regional Elections

The presented paper deals with the regionalization of the electoral support of the Czech Pirate Party (Pirates) in regional elections using methods and techniques of spatial data analysis. The aim is to answer the question whether the territorial distribution of Pirate electoral support allows this party to participate in governance at the regional level and thus influence the form of regional policy in individual regions. The results of the analysis show that the spatial distribution of Pirates’ electoral support in regional elections differed quite significantly not only from the pattern found in the elections to the Chamber of Deputies of the Czech Parliament and elections to the European Parliament, but also between individual regional elections. This suggests the current lack of anchorage of Pirates’ electoral support in regional politics, but at the same time, it may have its origins in the second-order character of regional elections and the candidacy of many local and regional entities in regional elections. On the other hand, the results of the regional elections in 2020 meant that the Pirates received seats in all regional councils, but especially in nine of the thirteen regions they joined the regional government (similarly to two years earlier when they joined government of capital city of Prague), gaining the opportunity to influence, with regard to its priorities, the form of regional governance in most Czech regions.

Spatial Disequilibrium Development and its Policies of Central China: The Case of Hubei Province

2013 ◽  
Vol 361-363 ◽  
pp. 160-167
Author(s):  
Yun Liu ◽  
Li Li Chang ◽  
Chong Peng
Keyword(s):  
Spatial Data ◽  
Statistical Data ◽  
Global Analysis ◽  
Spatial Differentiation ◽  
Hubei Province ◽  
Central China ◽  
Spatial Data Analysis ◽  
Economic Space ◽  
Reasonable Choice ◽  
Disequilibrium Theory

Central China is progressively paving its way to the second carrier of Chinese population after the east coastal areas with disequilibrium theory as the guidance of provincial spatial development. Based on ESDA (exploratory spatial data analysis) with statistical data of GDP per capita of Hubei Province by county-level (2000-2010), this paper reveals the spatial differentiation characteristics of economic differences among counties in Hubei Province. According to global analysis of ArcGIS and GeoDA095i, economic space of the county presents the trend of climbing up and then declining. Besides, differences between counties are remarkable. The LISA clean-cut indicates different developed and underdeveloped districts. Finally, contrasting to policy response that the provinces cope with disequilibrium theory in Central China, the results show that the Central China continues to promote disequilibrium development is a reasonable choice, and it’s also indispensible to pay attention to controlling magnification of differences in regional development.

scholarly journals Spatial Analysis of Housing Prices and Market Activity with the Geographically Weighted Regression

2020 ◽  
Vol 9 (6) ◽  
pp. 380
Author(s):  
Radosław Cellmer ◽  
Aneta Cichulska ◽  
Mirosław Bełej
Keyword(s):  
Spatial Heterogeneity ◽  
Housing Market ◽  
Spatial Data ◽  
Geographically Weighted Regression ◽  
Housing Prices ◽  
Spatial Diversity ◽  
Spatial Data Analysis ◽  
Weighted Regression ◽  
Market Activity ◽  
Administrative Units

The main part of the study will be to demonstrate that models taking into account spatial heterogeneity (Geographically Weighted Regression and Mixed Geographically Weighted Regression) which reproduce housing market determinants better reflect market relationships than conventional regression models. The spatial heterogeneity of the housing market determinants results in the spatial diversity of the market activity, as well as of real estate prices and values. The main aim of the study was to analyse an effect of these socio-demographic and environmental factors on average housing property prices and on the number of transactions in a spatial approach. In previous research conducted on a national scale, usually all variables were treated in a similar way, i.e., as global or local variables. During the research, an attempt was also made to answer the question of which of the variables adopted for analysis have a local impact on prices and market activity, and which are global. The study was conducted in Poland and used data from the year 2018 on 380 counties (Local Administrative Units). The study showed that determinants both for average prices and for the housing market activity show spatial autocorrelation with high–high and low–low cluster groups. Owing to these models, it was possible to draw specific conclusions on local determinants of flat prices and the market activity in Poland. The study findings have confirmed that they are an extremely effective tool for spatial data analysis.

scholarly journals Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

2021 ◽  
Vol 293 ◽  
pp. 02051
Author(s):  
Yuwei Wang ◽  
Kaicheng Wu ◽  
Wang Gao
Keyword(s):  
Spatial Data ◽  
Global Scale ◽  
Spatial Data Analysis ◽  
Wuhan City ◽  
The Sustainable Development ◽  
Aggregation Pattern ◽  
Per Capita ◽  
Football Field ◽  
Global And Local

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.

scholarly journals Testando a hipótese de dependência espacial na taxa de crime dos municípios da Região Sul do Brasil / Testing the space dependence hypothesis on crime rate of the municipalities of the south region of Brazil

2018 ◽  
Vol 8 (1) ◽  
pp. 118-141
Author(s):  
Otoniel Rodrigues dos Anjos Júnior ◽  
Stélio Coêlho Lombardi Filho ◽  
Juliane Da Silva Ciríaco ◽  
Magno Vamberto Batista da Silva
Keyword(s):  
Spatial Data ◽  
Spatial Model ◽  
Crime Rate ◽  
Behavioral Pattern ◽  
Spatial Data Analysis ◽  
The South ◽  
Show Evidence ◽  
Classical Linear Regression ◽  
Space Dependence ◽  
Global And Local

Este artigo tem como objetivo testar a hipótese de dependência espacial na taxa de criminalidade dos municípios da região Sul do Brasil. Para tanto, utilizou-se dados relativos aos homicídios provenientes do Sistema de Informação de Mortalidade (SIM-DATASUS), pertencente ao Ministério da Saúde, e variáveis do DATASUS e do Censo Demográfico. As análises descritivas revelaram que a criminalidade segue um determinado padrão comportamental quanto à escolha dos municípios em que a mesma ocorre. Com base na Análise Exploratória de Dados Espaciais (AEDE), observou-se que tanto o indicador de associação global quanto o local apontam indícios de não aleatoriedade do crime no espaço. A partir desse resultado, estimou-se o Modelo Clássico de Regressão Linear, visando constatar tal dependência e, em seguida, o modelo econométrico-espacial SAR-MQ2E para a obtenção de estimativas mais precisas e robustas. Os resultados do modelo espacial mostraram que a criminalidade sulista está correlacionada ao crime passado, ao desemprego, à densidade demográfica, ao Índice de Desenvolvimento Humano e às diferenças individuais de cada Estado (captadas pela dummies de Estado). AbstractThis paper aims to test the spatial dependence hypothesis on crime rate of the municipalities of the south region of Brazil in the year 2012. To this end, it were collected data from the Mortality Information System (SIM-DATASUS), belonging to the Ministry of Health, together with variables from DATASUS and the Demographic Census. Descriptive analyzes revealed that crime follows a certain behavioral pattern regarding the choice of the municipalities in which it occurs. Based on the Exploratory Spatial Data Analysis (ESDA), it was observed that both the indicator of global and local association show evidence of the non-randomness of crime in space. From this result, it was estimated the Classical Linear Regression Model, aiming to verify such dependency, and then the SAR-MQ2E econometric-spatial model to obtain more accurate and robust estimates. The results of the spatial model showed that southern crime correlates with past crime, unemployment, demographic density, Human Development Index and individual differences in each state (captured by the state dummies).

scholarly journals Dependencia espacial de la tasa municipal de desempleo en Andalucía. Un análisis espacial exploratorio

2021 ◽  
Author(s):  
Antonio Jesús Acevedo Blanco ◽  
Violante Martínez Quintana
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Spatial Dependence ◽  
Hot Spots ◽  
Spatial Context ◽  
Spatial Data Analysis ◽  
Exploratory Spatial Data Analysis ◽  
Sociological Research ◽  
Para Determinar ◽  
Global And Local

El presente trabajo examina la dependencia espacial, global y local, de la Tasa Municipal de Desempleo en Andalucía. Aplicando el software Geoda realizamos en primer lugar un ejercicio exploratorio encaminado a identificar los valores atípicos superiores del indicador. Posteriormente se implementan estadísticos propios del Análisis Espacial Exploratorio para determinar la dependencia espacial del desempleo en Andalucía. En la última sección de resultados se identifican los puntos calientes (Hot Spots) de mayor incidencia en la construcción del indicador de autocorrelación espacial. Se concluye tras el examen de resultados en la necesidad de añadir el territorio entre las variables de análisis para el estudio sociológico del paro.The current paper examines the spatial, global and local autocorrelation of the Municipal Unemployment Rate in Andalusia. Applying the Geoda software, firstly, we carried out an exploratory exercise aimed at identifying the superior outliers of the indicator. Later, statistics of the Exploratory Spatial Data Analysis are implemented to determine the spatial dependence of unemployment in Andalusia. In the last section of results, the hot spots with the highest incidence in the construction of the spatial autocorrelation indicator are identified. After examining the results it’s concluded on the need to add the spatial context among the analysis variables for the sociological research of unemployment.

scholarly journals An Analysis of Existing Production Frameworks for Statistical and Geographic Information: Synergies, Gaps and Integration

2021 ◽  
Vol 10 (6) ◽  
pp. 374
Author(s):  
Francisco Javier Ariza-López ◽  
Antonio Rodríguez-Pascual ◽  
Francisco J. Lopez-Pellicer ◽  
Luis M. Vilches-Blázquez ◽  
Agustín Villar-Iglesias ◽  
...  
Keyword(s):  
Spatial Data ◽  
Process Model ◽  
Statistical Data ◽  
Legal Framework ◽  
Public Agencies ◽  
Quality Model ◽  
Statistical Process ◽  
The Third ◽  
Spatial Data Quality ◽  
Statistical Area

The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the possibility and need to achieve a better integration between them through the interoperability of systems, processes, and data. The statistical area is well led and has well-defined frameworks. The geospatial area does not have clear leadership and the large number of standards establish a framework that is not always obvious. On the other hand, the lack of a general and common legal framework is also highlighted. Additionally, three examples are offered: the first is the application of the spatial data quality model to the case of statistical data, the second of the application of the statistical process model to the geospatial case, and the third is the use of linked geospatial and statistical data. These examples demonstrate the possibility of transferring experiences/advances from one area to another. In this way, we emphasize the conceptual proximity of these two areas, highlighting synergies, gaps, and potential integration.

scholarly journals Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1056
Author(s):  
Yu Chen ◽  
Mengke Zhu ◽  
Qian Zhou ◽  
Yurong Qiao
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spatial Data ◽  
Central Area ◽  
Urban System ◽  
Entropy Method ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Eastern Region ◽  
Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

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