| Summary: | 碩士 === 國立暨南國際大學 === 經濟學系 === 101 === Tourism is classified as a weather-dependent industry , so the impact of weather changing should not be ignored. The research in UK mentions that especially the domestic visitors in collecting weather information are more convenient than the foreign visitors, while making their travel decisions can be easily affected by the weather. This study aims to quantify the trend of visitor`s change caused by weather factors. Our findings can provide a valuable reference for the tourism industries to reduce their loss by anticipating weather and increase their revenue by promoting the pleasant climate. Samples collected weather-factor data from Central-Weather-Bureau , visitor data of feature spots from Tourism-Bureau (a total of 25856 observations). Following the research of Taylor (2009) with the UK domestic tourism survey, I adopted random effects panel data regression model to estimate the impact of weather factors. Furthermore, accounting for the lagged influence of weather information on travel behaviors, I employ Arellano–Bond dynamic panel data estimator in dynamic model to re-investigate the weather effects.
Empirical result indicates that the temperature, rainfall, and wind speed increase will lead to a decline in visitors, while the hour of sunshine increases outdoor traveling. However, the weather influence is not obvious in the continuous holidays. The weather variables in the model of Spring-break are all not significant except for the significantly
negative rainfall effects in Summer-vacation. Therefore tourism-related industries should pay more attentions to weather changes in regular days, while focus on probability of rainfall during Spring-break and Summer-vacation.
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