{'fraction_non_alphanumeric': 0.015723270440251572, 'fraction_numerical': 0.0, 'mean_word_length': 5.306930693069307, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Modeling the Impact of Sudden Environmental Changes on Visitor Arrival Forecasts: The Case of the Gulf War

Most forecasting models for tourist arrivals were constructed under the assumption of only minor changes in the environment. The performance of forecasting models in situations of sudden, drastic environmental change(s) has not been given much attention. Using the Gulf War as an example of sudden environmental change, the present article explored the relative performance of different forecasting models. The findings showed that in terms of forecasting accuracy, the naive II model was the best in dealing with unstable data.