Online reviews are an important influencing factor in consumer purchasing decisions, and consumers' diverse cultural backgrounds affect the expression of online reviews as well as decision-making process. This study proposes an integrated ranking method through online reviews. Specifically, the study constructs a fraudulent review detection model to detect fraudulent reviews. Then introduces the Hofstede's national cultural framework and cultural distance theory to propose a method for calculating the weighted sentiment values of reviews, and interval-valued Pythagorean fuzzy sets are used for representation. Finally, the ranking function is improved by introducing a weight factor to aggregate the ratings and reviews, and obtain the hotel ranking. To validate the proposed method, a case study is conducted using real hotel reviews. The results show that this method provides a suitable and differentiated ranking of alternatives for consumers in specific countries. This paper also offers insights for online review websites and hotel managers.
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Shi et al. (2025) studied this question.
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