DocumentCode
2930358
Title
China e-commerce market analysis: Forecasting and profiling internet user
Author
Sin, Liem Gai ; Bus, M. ; Purnamasari, Ria
Author_Institution
Dept. of Economic & Bus., Ma Chung Univ., Malang, Indonesia
fYear
2011
fDate
10-12 July 2011
Firstpage
79
Lastpage
82
Abstract
E-commerce has been increasing rapidly and will obviously be more popular in the future. The growth of internet is believed to have given an impact on e-commerce´s growth in China because approximately thirty percent of Chinese alter to be active internet users. The trend is pointed out to the increase of e-commerce transaction value. This research aims to provide an insight to the Chinese e-commerce market by performing a forecast of internet users. Age, gender, and income, as part of demographic profiles, are selected since they are considered to positively influence the internet user´s online activity. Furthermore, this research also provides an analysis of guidelines for companies that want to enter the China e-commerce market. For the purpose of this research, time series analysis using ARIMA model will be used as the research method. Overall, findings assert Chinese internet users seem to grow rapidly. Male users are still predicted to the dominate market although, surprisingly, the result shows that male internet users are to go down gradually by 2015. In addition, the result shows that internet users who have high income are increasing. Therefore, it is indicated that luxury products become potential products to be marketed. Considering the overall phenomenon, it is likely that China will still continue to be a prospective e-commerce market in the future.
Keywords
Internet; autoregressive moving average processes; demand forecasting; electronic commerce; time series; transaction processing; ARIMA model; China e-commerce market analysis; Internet user; demographic profiles; forecasting; luxury products; online activity; time series analysis; transaction value; Companies; Education; Forecasting; Internet; Manuals; Predictive models; ARIMA; Demographic Profile; E-Commerce; Forecasting; Profiling;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Innovation and Technology Management (APBITM), 2011 IEEE International Summer Conference of Asia Pacific
Conference_Location
Dalian
Print_ISBN
978-1-4244-9654-9
Type
conf
DOI
10.1109/APBITM.2011.5996297
Filename
5996297
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