A Sales Forecasting Model for the Consumer Goods with Holiday Effects

DOI

10.2991/jracr.k.200709.001How to use a DOI?

Keywords

Consumer goods; sales forecasting; holiday effects; seasonal decomposition; ARIMA model; seasonal factor

Abstract

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.

Copyright

© 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/).

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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  - 10.2991/jracr.k.200709.001
ID  - Zhang2020
ER  -