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RETRACTED ARTICLE: Research on sales information prediction system of e-commerce enterprises based on time series model

Author

Listed:
  • Jian Liu

    (Changzhou Vocational Institute of Engineering)

  • Chunlin Liu

    (Nanjing University Business School)

  • Lanping Zhang

    (Changzhou Vocational Institute of Engineering)

  • Yi Xu

    (Changzhou Tiansheng New Materials Co, Ltd)

Abstract

Sales forecasting plays an important role in guiding the sales and marketing of e-commerce enterprises, and warehousing department planning warehouse location. At the same time, sales data can better reflect future sales trends. This paper establishes a sales forecasting and analysis model for commodities with common characteristics using their historical sales data through time series model, and forecasts the sales inventory of a certain kind of products from a quantitative point of view. In order to improve the predictive reliability, this paper introduces external observable data and qualitative analysis of historical data prediction model by using hidden Markov model to predict the characteristics of hidden values, so as to further improve the reliability of prediction model.

Suggested Citation

  • Jian Liu & Chunlin Liu & Lanping Zhang & Yi Xu, 2020. "RETRACTED ARTICLE: Research on sales information prediction system of e-commerce enterprises based on time series model," Information Systems and e-Business Management, Springer, vol. 18(4), pages 823-836, December.
    • Handle: RePEc:spr:infsem:v:18:y:2020:i:4:d:10.1007_s10257-019-00399-7
    DOI: 10.1007/s10257-019-00399-7
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    References listed on IDEAS

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    1. Schneider, Matthew J. & Gupta, Sachin, 2016. "Forecasting sales of new and existing products using consumer reviews: A random projections approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 243-256.
    2. Antonis A Michis, 2015. "A wavelet smoothing method to improve conditional sales forecasting," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(5), pages 832-844, May.
    3. Arunraj, Nari Sivanandam & Ahrens, Diane, 2015. "A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 321-335.
    4. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
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    Cited by:

    1. Mingwei Sun & Katarzyna Grondys & Nazim Hajiyev & Pavel Zhukov, 2021. "Improving the E-Commerce Business Model in a Sustainable Environment," Sustainability, MDPI, vol. 13(22), pages 1-22, November.

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