DocumentCode :
2208525
Title :
Garment E-Commerce Forecast Based on Grey Model
Author :
Hui, Hongqi ; Zu, Yidan
Author_Institution :
Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
2936
Lastpage :
2939
Abstract :
Garment e-commerce sales forecast is important for the e-business development strategy planning and the integration of garment supply chain upstream and downstream enterprises. GDP, per capita consumption expenditure of urban residents, the total retail sales of consumer goods, the number of internet users are selected as economic forecast indexes. On the basis of grey incidence degree, close correlation indexes are chosen to establish multi-variable grey model to forecast. In consideration of the historical data of garment e-commerce not being obtained, experts´ estimation is cooperated. By many iterative fitting on grey model, the credible garment e-commerce forecast amount is calculated. A case analysis of Hebei Garment e-commerce is provided for illustrative purposes.
Keywords :
Internet; clothing industry; economic indicators; electronic commerce; forecasting theory; grey systems; iterative methods; retail data processing; sales management; supply chain management; GDP; Hebei garment e-commerce; Internet users; close correlation indexes; consumer goods; e-business development strategy planning; economic forecast indexes; garment e-commerce sales forecast; garment supply chain downstream enterprise; garment supply chain upstream enterprise; grey incidence degree; iterative fitting; multivariable grey model; per capita consumption expenditure; total retail sales; urban residents; Clothing; Economic forecasting; Economic indicators; Electronic commerce; Internet; Marketing and sales; Predictive models; Statistics; Supply chains; Technology forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
Type :
conf
DOI :
10.1109/ICISE.2009.618
Filename :
5454552
Link To Document :
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