A Sales Forecasting Model for the Consumer Goods with Holiday Effects
- https://doi.org/10.2991/jracr.k.200709.001How to use a DOI?
- Consumer goods; sales forecasting; holiday effects; seasonal decomposition; ARIMA model; seasonal factor
In reality, there are so-called holiday effects in the sales of many consumer goods, and their sales data have the characteristics of double trend change of time series. In view of this, by introducing the seasonal decomposition and ARIMA model, this paper proposes a sales forecasting model for the consumer goods with holiday effects. First, a dummy variable model is constructed to test the holiday effects in consumer goods market. Second, using the seasonal decomposition, the seasonal factor is separated from the original series, and the seasonally adjusted series is then obtained. Through the ARIMA model, a trend forecast to the seasonally adjusted series is further carried out. Finally, according to the multiplicative model, refilling the trend forecast value with the seasonal factor, thus, the final sales forecast results of the consumer goods with holiday effects can be obtained. Taking the cigarettes sales in G City, Guizhou, China as an example, the feasibility and effectiveness of this new model is verified by the example analysis results.
- © 2020 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Mu Zhang AU - Xiao-nan Huang AU - Chang-bing Yang PY - 2020 DA - 2020/07/15 TI - A Sales Forecasting Model for the Consumer Goods with Holiday Effects JO - Journal of Risk Analysis and Crisis Response SP - 69 EP - 76 VL - 10 IS - 2 SN - 2210-8505 UR - https://doi.org/10.2991/jracr.k.200709.001 DO - https://doi.org/10.2991/jracr.k.200709.001 ID - Zhang2020 ER -