축소추정량을 이용한 쿠폰상환율 예측모형에 관한 연구
The Study on the Coupon Redemption Rate Prediction Model Using Shrinkage Estimator
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초록
본 연구의 목적은 쿠폰의 상환율을 보다 정확히 예측할 수 있는 모형을 개발하는 데 있다. 쿠폰의 상환율 예측이 중요한 이유는 상환율을 예측함으로써, 1)최적의 쿠폰 발행 조건 파악, 2)효율적 촉진 예산 집행, 3)신제품 확산의 조기 파악 등이 가능하기 때문이다. 기존의 연구에서는, 쿠폰상환율에 영향을 미치는 할인액, 점유율, 배포수단 등의 독립변수를 사용한 회귀모형을 이용하여 상환율을 예측하거나, 기간별 상환량을 기초로 한 시계열모형을 통하여 상환율을 예측하였다. 기존 연구에서 회귀모형의 계수들은 예상 밖의 부호를 보이거나 불안정한 값을 보이는데, 이러한 단점을 보완하기 위해서 본 연구에서는 축소추정량을 사용하였다. 시간모형에서는 쿠폰상환 패턴을 와이불분포를 사용하여 예측하였다. 또한 두 모형을 결합하여 쿠폰상환율 예측의 정확도를 높이고자 하였다. 미국의 쿠폰 상환업체 NCH가 제공한 자료를 이용하여 실증분석을 한 결과 다음의 결론을 얻었다. 첫째, 연도 더미변수와 브랜드 더미변수를 사용하는 것이 예측력을 높일 수 있고, 둘째, 축소추정량에 의한 예측이 더욱 정확하며, 셋째, 시간 경과에 따른 쿠폰 상환패턴이 와이불분포를 따른다고 가정하는 것이 적합하며, 넷째, 결합모형의 상환량 예측 정확도가 축소회귀모형이나 와이불 시간모형의 그것보다 높다.
Abstract
The purpose of this study is to develop the better model to predict the coupon redemption rate. The prediction of coupon redemption is important because it is essential 1) for finding the optimal coupon issuing condition, 2) for execution of efficient promotion budget, and 3) for early estimation of new product diffusion rate. In previous researches, coupon redemption rate was predicted by regression model using face value, market share, and distribution media as independent variables, or by time series model using periodic redemption quantities. In previous researches, coefficients of regression model sometimes showed unexpected signs and had volatile values. To remedy this weakness, shrinkage estimators are used in this study. In timing model, Weilbull distribution is used to capture coupon redemption pattern. Also both regression model and timing model are combined to enhance the accuracy of prediction.Through empirical study using data provided by US redemption agency NCH, following conclusions are drawn. First, introduction of year dummies and brand dummies enhanced prediction accuracy. Second, model with shrinkage estimators showed better prediction. Third, coupon redemption pattern with time resembled Weibull distribution. Finally, prediction accuracy of combined model was better than that of shrinkage regression model and Weibull timing model.
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