TL;DR
This study uses natural language processing to compare Chinese and Western tourists' satisfaction factors in Japanese hotels, revealing cultural differences in preferences and expectations through analysis of online reviews.
Contribution
It introduces an automated, data-driven NLP approach to analyze cross-cultural tourist satisfaction, focusing on soft and hard attributes in hotel reviews.
Findings
Chinese prioritize room quality over hospitality
Western tourists value staff behavior more
Environmental factors like Chinese-friendly environment affect satisfaction
Abstract
Since culture influences expectations, perceptions, and satisfaction, a cross-culture study is necessary to understand the differences between Japan's biggest tourist populations, Chinese and Western tourists. However, with ever-increasing customer populations, this is hard to accomplish without extensive customer base studies. There is a need for an automated method for identifying these expectations at a large scale. For this, we used a data-driven approach to our analysis. Our study analyzed their satisfaction factors comparing soft attributes, such as service, with hard attributes, such as location and facilities, and studied different price ranges. We collected hotel reviews and extracted keywords to classify the sentiment of sentences with an SVC. We then used dependency parsing and part-of-speech tagging to extract nouns tied to positive adjectives. We found that Chinese tourists…
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Taxonomy
Methodstravel james
