Scenario Based Forecasting Smart Tourism City’s Tourist Demand Using Feasibility Rates

Hee Chung Chung; Koo Chulmo; CHUNG NAMHO

doi:10.17086/JTS.2020.44.7.163.179

Recently, a growing number of local governments are seeking to invigorate the local economy through smart tourism, a high value-added industry. Thus, while many researchers discuss the economic value of smart tourism, there are few studies that present specific data. Therefore, the purpose of this study is to provide empirical basis for the economic value of smart tourism by predicting changes in the number of tourists through smart tourism. Furthermore, it aims to present specific and objective data to local governments that seek to revitalize the local economy through smart tourism. To achieve this research objective, this study utilized demand forecasting techniques that take into account visit intention and feasibility rates, and collected data through online surveys. Specifically, the study sampled the residents of metroplitan area through quota sampling and examined their respective willingness to visit Jeonju, Gyeongju, and Gangneung when they were traditional tourist cities and smart tourist cities. The analysis shows that the average number of tourists in smart tourist cities is expected to increase twice as much. In addition, as a result of analyzing the differences in the willingness to visit between existing cities and smart tourism cities, women showed higher willingness to visit than men, and 60s showed the highest willingness to visit. These analysis results were not only empirical grounds for the economic value of smart tourism, which had been discussed only conceptually, but the study also presented basic data to local governments seeking to vitalize the local economy through smart tourism.

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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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이 논문은 한국연구재단의 지원을 받아 작성되었습니다.

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