Prediction of Sales on Some Large-Scale Retailing Types in South Korea

• 발행기관: 한국유통과학회
• 저자명: Dong-Bin Jeong
• 간행물 정보: 『East Asian Journal of Business Management』vol.7 no.4, 35~41쪽, 전체 7쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2017.10.31

영문 초록

Purpose – This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters’ additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.

목차

1. Introduction

2. Time Series Analysis

3. Summary and Research Results

4. Concluding Remarks and Limitation

References

키워드

Large-Scale Retailing Type ARIMA Model Exponential Smoothing Method Optimal Forecasts