Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Analysis and Estimation of Food and Beverage Sales at Incheon Int'l Airport by ARIMA-Intervention Time Series Model

ARIMA-Intervention 시계열 모형을 이용한 인천국제공항 식음료 매출 분석 및 추정 연구

  • Yoon, Han-Young (Division of Comprehensive Aviation Studies, Hanseo University) ;
  • Park, Sung-Sik (Division of Flight Operation, Korea National University of Transportation)
  • 윤한영 (한서대학교 항공융합학부) ;
  • 박성식 (한국교통대학교 항공운항학과)
  • Received : 2018.10.08
  • Accepted : 2019.02.01
  • Published : 2019.02.28
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Abstract

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

본 연구는 2015년 6월부터 2018년 8월까지 인천국제공항 여객터미널에서 발생한 품목별 식음료 매출액(POS) 데이터를 기반으로 2020년 12월까지 식음료 매출액을 추정하고자 하였다. 이를 위해 연구자는 시계열 분석기법들 중 하나인 ARIMA-Intervention(개입모형)을 이용하여 인천국제공항 식음료 매출액에 영향을 미칠 것으로 판단되는 주요 시계열 영향변수들을 구분하고 그에 따른 변화폭을 추정하였고 그 결과를 토대로 향후 발생가능할 것으로 예측되는 식음료 월별 매출액을 추정하는 것을 목적으로 한 것이다. 개입변수는 국내 THAAD 배치에 따른 중국 정부의 2016년 7월부터 2017년 12월까지 한국 방문을 자제를 권고한 한한령으로 설정하였다. 정상 예측치의 경우에 비록 식사 매출 상승세가 둔화되었다 하더라도 하계 극성수기인 2019년 7월 203억, 2019년 8월 212억으로 월별 매출액이 200억을 돌파할 것으로 예측되며 2020년에는 각각 214억 및 221억으로 증가할 것으로 예측되었다. 음료 매출액은 2019년 7월에는 77억, 2019년 8월에는 81억으로 예측되며 2020년에는 79억 및 82억으로 증가할 것으로 전망되었다. 저비용항공사들은 정규항공사에 비해 식음료 서비스가 전무하거나 유료화 정책으로 운영하기 때문에 저비용항공사 이용객들은 여객터미널에서 출국 및 입국 시 식음료 서비스를 이용하는 빈도가 높을 수 밖에 없을 것이다. 앞서 예측자료에 제시된 것처럼 식음료 매출은 저비용항공사의 성장과 동반하여 증대될 가능성이 높을 것이다.

Keywords

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Fig. 1. ARIMA process by Box-Jenkins

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Fig. 2. Quarterly sales revenue of food and beverage (left bar : food, right bar : beverage)

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Fig. 3. Time series data of food ales from June 2015 to Dec. 2020

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Fig. 4. Differencing data of food sales from June 2015 to Dec. 2020

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Fig. 7. White noise residuals ACF and PACF of food

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Fig. 8. Forecasting food revenue from Sep. 2018 to Dec. 2020

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Fig. 9. Time series data of beverage sales from June 2015 to Dec. 2020

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Fig. 10. Differencing data of beverage sales from June 2015 to Dec. 2020

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Fig. 11. Auto correlation function of beverage

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Fig. 12. Partial auto correlation function of beverage

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Fig. 13. White noise residuals ACF and PACF of beverage

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Fig. 14. Forecasting beverage revenue from Sep. 2018 to Dec. 2020

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Fig. 5. Auto correlation function of food

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Fig. 6. Partial auto correlation function of food

Table 1. Categories of food and beverage

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Table 2. Model fitness and statistics of food

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Table 3. Model fitness and statistics of food

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Table 4. Prediction of food & beverage sales

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