계량기법과 질적 기법을 이용한 복합리조트 카지노 수요예측

이충기 한국호텔관광학회 2015 호텔관광연구 Vol.17 No.4

ntegrated Resort Casino is a hot issue and thus, how many Integrated Resorts are appropriate is a major concern for both government and private sector. Experts assert that the number of Integrated Resorts to be legalized should be determined on the basis of accurately forecasting demand for Integrated Resort. In this respect, the objective of this study is to forecast demand for Integrated Resort in the area of Yeongjong-do, Incheon. To achieve this objective this study employed both quantitative and qualitative forecasting techniques. This study also conducted an onsite survey for foreign tourists to examine visit intention if Integrated Resort is opened in Yeongjong-do, Incheon. The quantitative technique with visit intention forecasted that two to three Integrated Resorts are most appropriate in Yeongjong-do, Incheon. On the other hands, the qualitative technique using Delphi model predicted that two Integrated Resorts are most appropriate considering demand for casino: otherwise exceeding this demand could cause oversupply of Integrated Resorts. The results of this study will provide policy-makers with casino guidelines when legalizing the number of Integrated Resorts.

한국의 인-바운드 관광환경에 적합한 정량적 수요예측 기법의 최적 모델 검정에 관한 연구

이승곤(Seung Kon Lee),윤유식(Yoo Shik Yoon),김동일(Dong Il Kim) 한국관광연구학회 2011 관광연구저널 Vol.25 No.4

The purpose of this study is to select the most appropriate quantitative forecasting model to predict the Japanese travel demand to Korea in the near future. And also, This research progressed from the results of previous study that the forecasting accuracy of model could be changed according to data apply to forecasting model. The models to evaluate consisted of exponential smoothing model, ARIMA model and regression model from among the models confirmed in previous studies on accuracy. The data for analysis has applied the number of Japanese tourist in 15 years. Each model was assessed based on MAPE(mean absolute percentage error) and the probability of improvement of forecasting accuracy was additionally evaluated by combined techniques. The results of model estimation indicates that Winter`s exponential smoothing model was measured as the best model(MAPE=8.72%) in individual model, and also the combination model consisted of Winters exponential smoothing model and cubic regression model was relatively outperformed(MAPE=8.63%) the other combined techniques.

국제회의 방문자 수요예측 사례연구

김혁수(Hyuk Soo Kim) 한국호텔외식관광경영학회 2009 호텔경영학연구 Vol.18 No.1

This paper aims at forecasting the demand of convention visitors in Songdo and Incheon province, using quantitative techniques. The demand of convention visitors was predicted by using technique of quantitative model with survey method of Holt and Winters. Quantitative model with two survey methods was used to predict the convention demand in Songdo & Incheon from 2008 to 2017. Accuracy of this model was tested based on measurement of MAPE. The results of this study show that quantitative model predicted the demand of convention visitors in Songdo and Incheon to be from 15,199 and 26,740 respectively in 2008 to 29,868 and 52,548 respectively in 2017, and the demand of convention visitors in Korea to be from 355,113 in 2008 to 697,851 in 2017. This study will be useful for convention planners and practitioners in terms of application of these results to many decision-making process and financial factors.

호텔산업의 합리적 수요예측 방법에 관한 연구

윤설민(Seol Min Yoon),황순애(Soon Ae Hwang),이충기(Choong K Lee) 한국호텔외식관광경영학회 2009 호텔경영학연구 Vol.18 No.1

Although quantitative data are available in the hotel industry, traditionally hotel managers tend to predict their room sales based on their simple judgement because of lack of knowledge on quantitative forecasting models. This practice, however, does not guarantee accuracy of their room sales in near future, making hotel yield management difficult. In this respect, this study aims to compare forecasting accuracy between quantitative and qualitative forecasting techniques when predicting hotel room sales. To this end, this study employs quantitative forecasting techniques such as Holt, Winters, and Regression models using actual data of hotel room sales. Then, these forecasts are compared with traditional qualitative forecasts by hotel managers in terms of accuracy. The results of this study indicate that forecasts by quantitative approach were more accurate than traditional qualitative forecasts by hotel managers in terms of hotel room sales. In other words, forecasts by hotel managers were found significantly different from actual room sales. The findings suggest that hotel management should utilize more accurate quantitative forecasting approach than traditional qualitative method when predicting room sales. Furthermore, the Winters Exponential Smoothing model was found to be the most appropriate forecasting method in terms of simplicity and accuracy. Thus, this study also suggest that hotel managers should utilize relatively simple forecasting method of the Winters model in particular when data of room sales depict seasonality.

호우 영향예보를 위한 수문학적 정량강우예측(HQPF) 개선 연구

신윤후(Yoon Hu Shin),김성민(Sung Min Kim),지용근(Yong Keun Jee),이영미(Young-Mi Lee),김병식(Byung-Sik Kim) 한국방재안전학회 2022 한국방재안전학회 논문집 Vol.15 No.4

최근 짧은 시간 동안 많은 강우가 내리는 국지성 집중호우가 빈번히 발생하고 이로 인한 침수피해가 증가하고 있다. 국지성 집중호우로 인한 피해를 예방하기 위하여 기상청이 제공하는 지역 앙상블 예측시스템(Local ENsemble prediction System, LENS)과 관측자료와 동네예보 자료를 활용한 기계학습과 확률 매칭(Probability Matching, PM) 기법을 이용하여 수문학적 정량강우예측정보(Hydrological Quantative Precipitation Forecast, HQPF)을 개발하였다. 국지성 집중호우로 인한 침수피해 대비를 위한 호우 영향정보로 HQPF를 생산하고 있지만, 낮은 강우강도에 대하여 과대예측하는 경향이 나타났다. 본 연구에서는 HQPF의 예측정확도 향상과 과대예측 성향을 개선하기 위하여 머신러닝 학습자료 기간확대, 앙상블 기법 분석 및 확률매칭(PM) 기법 프로세스 변경을 통하여 HQPF 개선하였다. 개선된 HQPF의 예측성능을 평가하기 위해 2021년 8월 27일 ~ 2021년 9월 3일 장마전선으로 인한 호우 사례를 대상으로 예측성능 검증을 수행하였다. 10 mm 이하의 강우에 대하여 예측정확도가 크게 향상되었고, 관측과 유사한 발생가능성 및 강우영역을 예측하는 등 과대예측 성향이 개선되었음을 확인하였다. In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

BIE Expo 방문객 수요예측

이충기(Lee Choong-Ki),송학준(Song Hak-Jun),신창열(Shin Chang-Yeol) 한국관광레저학회 2007 관광레저연구 Vol.19 No.3