기상 정보를 이용한 의류제품의 판매량 예측 모형 연구
A Study on the Sales Forecast Model of Apparel Products Using Meteorological Factors
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연구목적: 본 연구구에서는 날씨가 의류제품의 판매에 영향을 미친다는 기존 연구 결과를 바탕으로, 기상 요인들이 의류 제품의 판매에 미치는 영향을 알아보고, 과거 데이터에 대한 시계열 분석을 통해서 판매량 예측 모형을 제시한다. 연구설계 및 방법론: 국내 유명 의류 제조업체의 각 품목별 일일 판매 데이터와 기상 정보 데이터의 분석을 통해서 기상 요인들이 판매에 미치는 영향을 알아보고, 이를 바탕으로 ARIMA 모델을 이용한 판매 예측 모형을 개발한다. 분석 및 연구 결과: 각 의류 품목에 계절 ARIMA 모형을 적용하여, 계절적 요인과 기온이나 강수량 등의 기상요인, 휴일 효과, 세일 기간 등을 포함한 시계열 판매량 예측 모형을 도출하였으며, 예측값이 얼마나 정확한지 확인하였다. 시사점 및 연구의 한계점: 의류 제품은 날씨가 판매량에 많은 영향을 미치는 계절 상품으로서, 의류 업체들은 기상 정보를 마케팅에 활용하기 위해 노력하고 있다. 본 연구에서 개발한 기상 정보를 활용한 의류제품의 판매량 예측 모형은 기상 변화에 따른 생산 및 주문 시기 조정, 재고 관리, 판촉 전략 등 기업의 날씨 마케팅에 활용될 수 있을 것으로 기대한다. 향후 연구 방향: 데이터의 한계가 있으며, 향후 연구는 의류 판매에 영향을 미치는 다른 변수들이나, 다른 기업의 데이터들을 포함하여, 연구의 타당성을 높이는 방향이 필요하다. 공헌점: 의류 제품은 날씨가 판매량에 많은 영향을 미치는 계절 상품으로서, 의류 업체들은 기상 정보를 마케팅에 활용하기 위해 노력하고 있다. 기상 정보가 판매에 미치는 영향에 대한 실증 연구로서 의미가 있다.
Abstract
Purpose: This study proposes a sales forecast model of apparel products using meteorological factors and the daily sales data from a leading Korean clothing company, based on previous studies on the influence of weather on the sales of apparel products. Design/methodology/approach: We analyze the influence of weather on the sales of each item, and propose a sales forecast model using a seasonal time-series ARIMA (Autoregressive Integrated Moving Average) model. This model considers seasonal factors, meteorological factors such as temperature and precipitation, and weekend factors to forecast the sales of each item. Results/findings: We identify the effects of meteorological factors on the sales of apparel products, and then we forecast the revenue using this model. Finally, we verify the accuracy of the sales forecast model. Research implications/limitations: Apparel products are widely recognized as seasonal products that are significantly affected by meteorological factors. The sales forecast model of apparel products considering real daily sales data and meteorological factors is expected to be used in diverse parts of weather marketing such as production and ordering, inventory management, and sales promotion. Future work/research: Future study must improve the forecast model validity of this study by adding other variables that influence sales, and by using sales data from other companiesOriginality/value: Fashion and apparel companies make efforts to use meteorological information for marketing. The contribution of this study can be found in the empirical test of the sales forecast model of apparel products, including real daily sales data and meteorological factors.
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