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수입자동차 리콜 수요패턴 분석과 ARIMA 수요 예측모형의 적용

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영문명
Analysis of the Recall Demand Pattern of Imported Cars and Application of ARIMA Demand Forecasting Model
발행기관
한국산업경영시스템학회
저자명
정상천(Sangcheon Jeong) 박소현(Sohyun Park) 김승철(Seungchul Kim)
간행물 정보
『산업경영시스템학회지』제43권 제4호, 93~106쪽, 전체 14쪽
주제분류
공학 > 산업공학
파일형태
PDF
발행일자
2020.12.30
4,480

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논문 표지

국문 초록

영문 초록

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

목차

1. 서 론
2. 이론적 배경
3. 연구방법
4. 분석 결과
5. 결 론
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APA

정상천(Sangcheon Jeong),박소현(Sohyun Park),김승철(Seungchul Kim). (2020).수입자동차 리콜 수요패턴 분석과 ARIMA 수요 예측모형의 적용. 산업경영시스템학회지, 43 (4), 93-106

MLA

정상천(Sangcheon Jeong),박소현(Sohyun Park),김승철(Seungchul Kim). "수입자동차 리콜 수요패턴 분석과 ARIMA 수요 예측모형의 적용." 산업경영시스템학회지, 43.4(2020): 93-106

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