Economic Valuation of a Cherry Blossom Forecast System: Assessing Tourism Benefits and Public Willingness to Pay in Taiwan
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Published:2026
Wan-Yu Liu, Yen-Yu Lin, 2026. "Economic Valuation of a Cherry Blossom Forecast System: Assessing Tourism Benefits and Public Willingness to Pay in Taiwan", Advances in Hospitality and Leisure, Joseph S. Chen
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Abstract
The economic value of meteorological information is essential for tourism, particularly for seasonal attractions like cherry blossom viewing, where accurate forecasts can significantly enhance visitor experiences. This study assesses the economic impact of a cherry blossom forecast system in Taiwan using the Contingent Valuation Method to estimate public willingness to pay (WTP) and its influence on travel behavior. A nationwide survey was conducted to gather data on tourists’ preferences, forecasting needs, and payment intentions. The findings indicate that implementing such a system could generate NT$1.9–3.1 billion annually, increase the frequency of cherry blossom visits by 1.8 times, and extend visitor stays by an average of 3.27 hours per year. The estimated mean WTP per person is NT$106.02 per year, reflecting strong public demand for improved forecasting services. Statistical analyses reveal that socioeconomic factors, such as age, marital status, and occupation, significantly influence WTP, with older and married individuals demonstrating higher valuations. Protest responses accounted for 24.2% of the sample, with many respondents believing that the government should fund the service rather than relying on user contributions. The study highlights the critical role of meteorological services in enhancing tourism experiences and increasing destination attractiveness. It suggests that Taiwan should adopt a cherry blossom forecast system similar to Japan’s well-established model to provide accurate and accessible forecasting information. The findings offer valuable policy recommendations for integrating meteorological data into tourism planning, improving visitor satisfaction, optimizing travel planning, and maximizing economic benefits through data-driven tourism management.
