文章基本信息

标题：Forecasting Utilizing a Day of the Week Index In the Case of Café
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作者：Kazuhiro Takeyasu ; Komei Suzuki
期刊名称：Journal of Computations & Modelling
印刷版ISSN：1792-7625
电子版ISSN：1792-8850
出版年度：2015
卷号：5
期号：4
出版社：Scienpress Ltd
摘要：

Café shop sales forecasting is an important factor for the manager in order to keep the shop in surplus. He/she manages the shop by increasing/decreasing the employee/part-timer on the forecasting result. In this paper, we propose a new method to improve forecasting accuracy and confirm them by the Café shop sales data. Focusing that the equation of exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, a new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Generally, smoothing constant is selected arbitrarily. But in this paper, we utilize above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate smoothing constants. Thus theoretical solution is derived in a simple way and it may be utilized in various fields. Combining the trend removing method with this method, we aim to improve forecasting accuracy. Furthermore, “a day of the week index” is newly introduced for the daily data and we have obtained good result. The effectiveness of this method should be examined in various cases.