TY - JOUR
T1 - Spatial patterns of car sales and their socio-economic attributes in China
AU - Liu, Daqian
AU - Lo, Kevin
AU - Song, Wei
AU - Xie, Chunyan
N1 - Funding Information:
Received date: 2016-10-26; accepted date: 2017-02-24 Foundation item: Under the auspices of National Natural Science Foundation of China (No. 41301143) Corresponding author: SONG Wei. E-mail: [email protected] © Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag Berlin Heidelberg 2017
PY - 2017/10/1
Y1 - 2017/10/1
N2 - Using data from the Economic Advisory Center of the State Information Center (SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers (foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran’s indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.
AB - Using data from the Economic Advisory Center of the State Information Center (SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers (foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran’s indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.
KW - car sales
KW - China
KW - Location Quotient
KW - socio-economic attributes
KW - spatial clusters
UR - http://www.scopus.com/inward/record.url?scp=85029110700&partnerID=8YFLogxK
U2 - 10.1007/s11769-017-0902-x
DO - 10.1007/s11769-017-0902-x
M3 - Journal article
AN - SCOPUS:85029110700
SN - 1002-0063
VL - 27
SP - 684
EP - 696
JO - Chinese Geographical Science
JF - Chinese Geographical Science
IS - 5
ER -