Prediction Model of Physical Goods Sales based on Time Series Analysis
Keywords:Physical goods, Time series analysis, ARMA model, Online consumption prediction.
With the advent of the era of big data, most online historical consumption data are collected and simply stored in the cloud, but they are not receiving enough attention. This paper takes "online sales of physical goods" as the research object, uses "time series analysis related theory and sales prediction theory" to study and analyze "data from January 2020 to December 2021", and finally uses EViews software, using ARMA model for modeling and prediction. Establishing a mathematical model to effectively analyze and predict the "online physical goods sales ability", to a certain extent, has a practical guiding significance for e-commerce enterprises to make the optimal business decisions.
China Internet Information Center. The 49th Statistical Report on Internet Development in China [R]. Beijing: China The Internet Information Center, 2022.
Dong Yan, time, when the sweet rain. The Influence of Online Marketing on Online Consumer Purchase Behavior [J]. Economic problem exploration Cable, 2020 (10): 45-55.
Zuo Civilization, Chen Shaojie, Wang Xu, Chen Huaqiong. A Multi-attribute Behavior Decision Model of Network Consumers Based on Foreground Theory[J]. Journal of Management Engineering, 2019,33 (03): 125-135.
Kansra Pt,Oberoi S .Determinants of Online Purchase Intention Among Young Consumers in Punjab: A Cross-Sectional Study[J].International Journal of Social Ecology and Sustainable Development (IJSESD), 2022, 13.
Zhang Jingxuan, Zhang Weiwei. Prediction of e-purchase behavior based on neural network [J]. Applied mathematics into Exhibition, 2021,10 (10): 7.
Li Weiqing, Chi Maomao, Wang Weijun. Online Consumer Preference Prediction Study Based on Perceived Value [J].management Newspaper, 2021,18 (06): 912-918.
Dong J,Huang T,Min L,et al.Prediction of Online Consumers'Repeat Purchase Behavior via BERT-MLP Model[J]. Electronic Research and Application, 2022 (006-003).
Rajendrakumar R .The prediction of online shopping consumers' attitude based on certain statements of consumer and marketing factors with reference to post graduate students in Coimbatore City[J].International Journal of Business Information Systems, 2022, 39.
Wang Xue. High-level subject prediction studies based on time-series models [J]. Intelligence Journal, 2019,38 (6).
Yan Jinghua, Hou Miao Miao. Time series prediction of theft crime based on LSTM Network [J]. Data points Analysis and Knowledge Discovery, 2020,4 (11): 84-91.
Zhigang Wang. Research on Deep prediction prediction prediction based on Chain chains [J]. Modern Computer, 2020 (34).
Ke Miao, Huang Huaguo, et al. Based on LSTM Neural Network [J]. Fujian Normal University Journal of Fuqing Branch School, 2020 (05): 25-33.
Huang Hongmei. Time-series analysis (M) was applied. Tsinghua University Press, 2016.
Nie Shuyuan. The Early Development of the Time-Series Analysis (Dj.Northwestern University, 2012.
Chris Chatfield.The Analysis of Time Series MTaylor and Francis,2013.
Box G E P,Jenkins G M.Time Series Analysis,Forecasting,and Control[M].San Francisco,California: Holden Day1976.
Box G EP,Pierce D ADistribution of Autocorrelations in Autoregressive Moving Average Time Series Models[J].Journal of the American Statistical Association, 197065(332):1509-1526.
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