Investigating The Impact of Sensory Experience on Budget Hotel Rooms to Maximize Guests Satisfaction

Wirakusuma, Reiza Miftah; Samudra, Anak Agung Anom; Sumartini, Ni Kadek Asri

doi:10.22334/jbhost.v7i1.284

Cited by 1 publication

(1 citation statement)

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“…With excitement and happiness, tourists head to an unfamiliar tourist destination. If the tourist hotel could provide a clean and tidy room, it could make the tourists happier, thus enhancing their travel experience [44].…”

Section: Identification and Classification Of Tourist Demandsmentioning

confidence: 99%

Construction of the tourist sentiment dictionary for hotels to mining tourist demands: Based on Macao’s hotel reviews from Agoda

Wang,

Zhu,

Zhang

et al. 2024

Smart. Tour.

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<p><span lang="AZ-LATIN">Tourist hotels (or tourist accommodations) are located near tourist attractions, primarily serving tourists. In recent years, with the gradual improvement of people’s living standards around the globe, tourists’ demands and standards for tourist hotel construction have been rising accordingly. In the context of technologization and informatization, various hotel booking platforms (Agoda, Booking, Trip, etc.) cover a large amount of review data in evaluating systems to reflect tourists’ demands. Meanwhile, identifying demand-oriented reviews and extracting core consumer demands from them is crucial for optimizing hotel services and enhancing tourist satisfaction. Therefore, this study explores the demands of tourists in tourist hotels from the perspective of text sentiment analysis and takes Macao, a famous tourist destination, as an example, based on reviews of tourist hotels on the Agoda site platform. Specifics are as follows: (1) Based on pointwise mutual information (PMI) and information entropy (IE), it realizes the identification of sentiment words in the field of tourist hotels and constructs a sentiment dictionary to address the problem of poor relevance between word segmentation results; (2) It summarizes the five types of reviews containing tourist demands (positive, negative, suggestion, demand, and comparison) and their characteristics to solve the ambiguity of texts and further accurately reveal the main demands of tourists; (3) It classifies tourist demands and group similar tourist demands into the same categories to address the problem of multiple expressions for the same demand. The present study provides empirical experiences from Macao’s hotels and contributes to the literature on text sentiment analysis in tourist hotels. Furthermore, the study results could enhance the mining accuracy and provide a detailed summarization of consumer demands and directions for the sustainable optimization improvement of tourist services.</span></p>

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Section: Identification and Classification Of Tourist Demandsmentioning

confidence: 99%