Dataset List

Vol.|Area

No.11 Vol.11,2024
No.10 Vol.11,2024
No.09 Vol.11,2024
No.08 Vol.11,2024
No.07 Vol.11,2024
No.06 Vol.11,2024
No.05 Vol.11,2024
No.04 Vol.11,2024
No.03 Vol.11,2024
No.02 Vol.11,2024
No.01 Vol.11,2024
No.12 Vol.10,2023
No.11 Vol.10,2023
No.10 Vol.10,2023
No.09 Vol.10,2023
No.08 Vol.10,2023
No.07 Vol.10,2023
No.06 Vol.10,2023
No.05 Vol.10,2023
No.04 Vol.10,2023
No.03 Vol.10,2023
No.02 Vol.10,2023
No.01 Vol.10,2023
No.12 Vol.9,2022
No.11 Vol.9,2022
No.10 Vol.9,2022
No.09 Vol.9,2022
No.08 Vol.9,2022
No.07 Vol.9,2022
No.06 Vol.9,2022
No.05 Vol.9,2022
No.04 Vol.9,2022
No.03 Vol.9,2022
No.02 Vol.9,2022
No.01 Vol.9,2022
No.12 Vol.8,2021
No.11 Vol.8,2021
No.10 Vol.8,2021
No.09 Vol.8,2021
No.08 Vol.8,2021
No.07 Vol.8,2021
No.06 Vol.8,2021
No.05 Vol.8,2021
No.04 Vol.8,2021
No.03 Vol.8,2021
No.03 Vol.8,2021
No.02 Vol.8,2021
No.01 Vol.8,2021
No.09 Vol.7,2020
No.08 Vol.7,2020
No.07 Vol.7,2020
No.06 Vol.7,2020
No.05 Vol.7,2020
No.04 Vol.7,2020
No.03 Vol.7,2020
No.02 Vol.7,2020
No.01 Vol.7,2020
No.06 Vol.6,2019
No.05 Vol.6,2019
No.04 Vol.6,2019
No.03 Vol.6,2019
No.02 Vol.6,2019
No.01 Vol.6,2019
No.08 Vol.5,2018
No.07 Vol.5,2018
No.06 Vol.5,2018
No.05 Vol.5,2018
No.04 Vol.5,2018
No.03 Vol.5,2018
No.02 Vol.5,2018
No.01 Vol.5,2018
No.04 Vol.4,2017
No.03 Vol.4,2017
No.02 Vol.4,2017
No.01 Vol.4,2017
No.09 Vol.3,2016
No.08 Vol.3,2016
No.07 Vol.3,2016
No.06 Vol.3,2016
No.05 Vol.3,2016
No.04 Vol.3,2016
No.03 Vol.3,2016
No.02 Vol.3,2016
No.01 Vol.3,2016
No.02 Vol.2,2015
No.01 Vol.2,2015
No.02 Vol.1,2014
No.01 Vol.1,2014
China
Asia
Oceanic region
African
European
North American
South American
Arctic
Global Scale
Data Details

30 Cities Online Group Buying Analysis Dataset of China (2014)


SHI Kunbo1YANG Yongchun1
1 College of Earth and Environmental Sciences，Lanzhou University，Lanzhou730000，China

DOI:10.3974/geodb.2016.05.13.V1

Published:Aug.2016

Visitors：12772       Data Files Downloaded：260      
Data Downloaded：6.76 MB      Citations：

Key Words：

Online group-buying,spatial pattern,spatial mismatch,regional differences,cities,Progress in Geography

Abstract：

Using 30 cities online group buying data from the 360 group-buying navigation website (basic data was collected from 10th to 20th, May, 2014), the 30 Cities Online Group Buying Analysis Dataset of China (2014) was developed. The dataset is consisted of (1) Spatial distribution of comprehensive scale of experiential online group-shopping market; (2) Lorenz curve of quantity of experiential online group-buying commodities; (3) Relationship between comprehensive scale index and development level index of experiential online group-buying market; (4) Relationship between scale indices and development level indices of experiential online group-buying market; (5) Spatial mismatch between experiential online group-buying market and consumption potential; (6) Contribution of spatial mismatch between experiential online group-buying market and consumption potential; (7) Relationship between experiential online group-buying market's comprehensive scale index and economic development level; (8) Driving factors of the spatial pattern of experiential online group-buying market; (9) Relationship between experiential online group-buying market's comprehensive scale index and spatial mismatch contribution index. The dataset is archived in .shp and .xlsx data format with compressed data size of 27MB. The research paper was published at Journal of Progress in Geography, No.6, Vol. 32, 2015.

Foundation Item：

National Natural Science Foundation of China (41171143);Ministry of Human Resources of China (J1210065)

Data Citation：

SHI Kunbo, YANG Yongchun. 30 Cities Online Group Buying Analysis Dataset of China (2014)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2016. https://doi.org/10.3974/geodb.2016.05.13.V1.

Data Product:

ID Data Name Data Size Operation
1 30CitiesOnlineGroupBuyChina.rar 26.61KB
Co-Sponsors
Superintend