Abstract
Few studies have examined tourism risk perception from a company perspective, which can better reflect their real risk situation. Moreover, when companies' risk perception is captured, it can have an impact on investor confidence and lead to abnormal market volatility. Therefore, it is essential to investigate tourism companies' risk perceptions and their effect on investor confidence. For this purpose, we first identify 31 risk perceptions from textual risk disclosures in annual reports using text mining technology. We then construct a panel regression model to assess its influence on investor confidence. This study overcomes the barriers to tourism companies' risk perception identification and effect characterization in data acquisition and technology. This work can enrich the research on tourism risk perception and improve tourism companies' risk management efficiency. The findings suggest that tourism companies should increase their protection against liquidity risk and actively explore international markets to enhance investor confidence.
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