2017, Vol.41, No.1

Journal of Tourism Sciences 2023 KCI Impact Factor : 2.7

pISSN : 1226-0533 / eISSN : 2713-6388
https://journal.kci.go.kr/JTS

The purpose of this paper is to prove demand forecasting methods by utilizing online search engines. This study utilizes text mining based issues and Keyword analysis data derived from online search engines to predict the number of visitors that exist demanding forecasting. In terms of forecasting tourists, this study compared NAVER trend statistics to the statistics of a Tourism Information System. and, it was carried out by applying the most appropriate model to forecast demand time series data. Also, it compared existing tourist forecast statistic results of a Tourism Information System in order to forecast the result of statistical NAVER trends. As a result, we have found that when utilizing NAVER trends the forecast is for Andong tourists to continue to increase until 2018 year. However, forecasting results though the Tourist Information System showed that the number of tourists decreased. This study proposes practical implications based on these results.

As social media is gaining in importance these days, many people share their travel experiences through social media and share their memories with others. Nevertheless, there still exist many hidden people who gather their precious travel information without posting their results on social media. To find reasons for their behavior, this study finds barrier factors on travel information sharing behavior and tries to adjust them within the 5 big factor model. The study then distinguishes the differences between the personality and its perceived barrier by adjusting the market segmentation. Therefore, the survey was basically designed for people who have travelled within one year and not posted their travel experiences on social media. The results show barrier types consisting of ‘privacy’, ‘lack of inner motivations’ and ‘structural constraints’. Using cluster analysis, we divided the subjects into three groups according to their personality based on the big 5 factor model and investigated their characteristics. The results help to understand the hidden traveler’s reasoning behind their behaviors and gives insight to stakeholder to make them turn to travel information sharer.

The purpose of this study is to examine the decision-making process in visit intention for the PyeongChang 2018 Olympic Winter Games by using Extended Theory of Planned Behavior(ETPB). Temporal and spatial distance constructs based on construal level theory, were included in the ETPB to examine their effects on attitude and behavioral intention. The results of this study reveal that temporal distance had a negative effect on behavioral intention. However, spatial distance did not have an effect on behavioral intention, but influenced attitude. Results also indicate that attitude, subjective norms and perceived behavioral control had a significant positive effect on behavioral intention. The effect of perceived behavioral control on behavioral intention was found to be more significant than any of the other constructs. These findings provide effective marketing strategies for dealing with the cognitive temporal and spatial distance of potential visitors to the Olympics.