Insights into TripAdvisor's online reviews: The case of Tehran's hotels

Khorsand, Ramina; Rafiee, Majid; Kayvanfar, Vahid

doi:10.1016/j.tmp.2020.100673

Cited by 36 publications

(24 citation statements)

References 73 publications

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“…Therefore, it becomes crucial for hotel marketing managers to understand the most relevant client characteristics that influence satisfaction [21,22]. Namely, their expectations and interests, culture, nationality, seasonality, travel experience, and socio-demographic characteristics [16,[23][24][25][26].…”

Section: Client Satisfaction In the Hotel Industrymentioning

confidence: 99%

Predictors of Hotel Clients’ Satisfaction in the Cape Verde Islands

et al. 2022

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Tourism has been fundamental for countries’ economic development, and Africa is the destination with the biggest tourism growth potential. Using 1414 travelers’ online reviews collected from TripAdvisor, the present work aims to understand which variables predict the satisfaction of Cape Verde’s hotel clients. Satisfaction was analyzed using sentiment analysis and ANOVA to predict the effect of the gathered variables on clients’ satisfaction. Results indicate that 90% of the clients revealed positive satisfaction and that nationality, date of stay, and previous traveler experiences affect satisfaction. Contrarily to our predictions, there is no statistically significant evidence that gender influences satisfaction. The findings of this study will help hotel marketing managers to align their strategies accordingly and meet their clients’ expectations.

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Section: Client Satisfaction In the Hotel Industrymentioning

confidence: 99%

Predictors of Hotel Clients’ Satisfaction in the Cape Verde Islands

et al. 2022

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“…Besides, Mellinas et al (2019) used the average global rating of hotel attributes as the independent variable and investigated the interrelationships of perceived evaluations of hotel attributes between the rating of location and the subjective service elements. Moreover, Khorsand et al (2020) used the useful information extracted from online reviews to forecast a new consumer's rate of a hotel.…”

Section: Hotel Online Reviewsmentioning

confidence: 99%

The impact of COVID-19 on hotel customer satisfaction: evidence from Beijing and Shanghai in China

Sun

Jiang²,

Feng

et al. 2021

IJCHM

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Purpose The purpose of this study is to provide better service to hotel customers during the COVID-19 era. Specifically, this study focuses on understanding the changes in hotel customer satisfaction during the epidemic and formulating effective marketing strategies to satisfy and attract guests. Design/methodology/approach As the first victim of the COVID-19 virus, China’s hotel industry has been profoundly affected and customer satisfaction and needs have also changed. Taking 105,635 hotel reviews obtained from Tripadvisor.com in Beijing and Shanghai as samples, this study explores the changes in consumer satisfaction by using text-mining methods. Findings The results suggest that there are significant differences in overall ratings, spatial distribution and ratings of different traveller types before and after the epidemic. Generally, customers have higher “tolerance” and are more inclined to give higher ratings and pay more attention to hotel prevention and control measures to reduce health risks after the COVID-19. Research limitations/implications This paper proves the changes in customer satisfaction before and after the COVID-19 at the theoretical level and reveals the changes in customer attention through the topic model and provides a basis for guiding hotel managers to reduce the impact of the COVID-19 crisis. Practical implications Empirical findings would provide useful insights into tourism management and improve hotel service quality during the COVID-19 epidemic era. Originality/value This research explores the hotel customer satisfaction in the field of hotel management before COVID-19 and after COVID-19, by using text mining to analyse mandarin online reviews. The results of this study will suggest that the hotel industry should continuously adjust its products and services based on the effective information obtained from customer reviews, so as to realize the activation and revitalization of the hotel industry in the epidemic era.

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“…In today's business world, consumers usually attempt to view online reviews before purchasing services and products [26][27][28]. In social media, their users can discuss and share restaurant-related information, and others can easily access their opinions [29]. According to a survey reported by ReportLinker in 2017, almost all (98%) customers trust online reviews and consider them as one of the most reliable information sources.…”

Section: Introductionmentioning

confidence: 99%

Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry

2020

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Due to the COVID-19 pandemic, the sales of fast-food businesses have dropped sharply. Customer satisfaction has always been one of the key factors for the sustainable development of enterprises. However, in the fast-food restaurant business, gaining the knowledge of customer satisfaction is one of the critical tasks. Moreover, text reviews in social media have become one of important reference sources for customers’ decisions in buying services and products. Therefore, the main purpose of this study is to explore whether customer voices from social media reviews are different during the COVID-19 outbreak and to propose a new method to reduce interpersonal contact when collecting data. A text mining scheme which includes least absolute shrinkage and selection operator (LASSO) and decision trees (DT) are presented to discover the essential factors for customers to increase their satisfaction from unstructured online customer reviews. Finally, three real world review sets were employed to validate the effectiveness of the presented text mining scheme. Experimental results can help companies to properly adapt to similar epidemic situations in the future and facilitate their sustainable development.

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Insights into TripAdvisor's online reviews: The case of Tehran's hotels

Cited by 36 publications

References 73 publications

Predictors of Hotel Clients’ Satisfaction in the Cape Verde Islands

Predictors of Hotel Clients’ Satisfaction in the Cape Verde Islands

The impact of COVID-19 on hotel customer satisfaction: evidence from Beijing and Shanghai in China

Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry

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