Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.     

The effect of travel purpose and self-image congruency on preference toward airline livery design and perceived service quality

This paper examines travelers’ preference for airline livery design, which is an important component of sensory experience for tourists. Based on surveys of both U.S. and South Korean respondents, this study finds that airline livery preference depends on travel purpose (i.e. business vs. vacation). Designs preferred by the two travel segments differ in terms of color tone, hue, line, and shape. Business traveler-preferred designs signal punctual, efficient, classy, and safe service; while vacation traveler-preferred designs elicit feelings of fun, friendly, and exotic service. It is also shown that travelers prefer airline livery that is congruent with their situational self-image, depending on the travel occasion at hand. In fact, self-image congruency of design is approximately half of the variance in airline livery preference. Finally, results show that self-image congruency also increases perceived service quality.