The effect of online reviews on hotel booking intention: The role of reader-reviewer similarity

Chan, Irene Cheng Chu; Lam, L.; Chow, Cheris W. C.; Fong, Lawrence Hoc Nang; Law, Rob

doi:10.1016/j.ijhm.2017.06.007

Cited by 124 publications

(90 citation statements)

References 78 publications

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“…This is consistent with research done by Ref. [41], who stated that online reviews provided a great deal of information to consumers. It was meaningful and useful for them in deciding while booking a hotel online.…”

Section: H5 Hypothesis Testingsupporting

confidence: 92%

Factors Affecting Consumers’ Decision for E-Hotel Booking

Syed

Suroso

2018

CommIT (Communication and Information Technology) Journal

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With more accessibility to the Internet and modernization of e-payment systems, the approach to address the travel requirements has dramatically changed over the years. The service offered by the Online Travel Agents (OTAs) has a huge impact on a very competitive online marketplace. The purpose of this research is to observe, examine, and analyze key factors which a consumers’ decision to use a particular travel agent website for e-hotel booking can be predicted. The data are compiled using IBM SPSS. The key methods are applied for data analysis in addition to other statistical methods including factor analysis and multinomial logistic regression analysis. The analysis of data reveals a positive association of website quality factors, product related factors, and consumer relationship factors with consumers’ decision to book from a certain travel agent website. Viewing the big picture, consumer relationship factors are found to be more influential as compared to website quality and product related factors. Moreover, the researchers reveal product price as the most influential variable, but it indicates no statistical significance with consumers’ decision. There are many different price products which are available across different travel agent websites. The convenience of payment method is found to be a significant attribute associated with the consumers’ decision to book from a travel website. In addition, attributes of travel products variety and online reviews provided by the travel websites are observed to be statistically significant. This research indicates the trends of consumer decision-making for e-hotel booking in Indonesia.

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Section: H5 Hypothesis Testingsupporting

confidence: 92%

Factors Affecting Consumers’ Decision for E-Hotel Booking

Syed

Suroso

2018

CommIT (Communication and Information Technology) Journal

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“…However, the effect of negativity bias diminished when the majority of the reviews were negative. Nevertheless, other researchers have demonstrated the power of positive online reviews (e.g., Chan, Lam, Chow, Fong, & Law, 2017). For instance, Blal and Sturman (2014) found that positive reviews had a stronger effect on consumers' purchase intentions toward higher tier hotels, whereas review volume had a more positive effect on lower tier hotels.…”

Section: Review Valancementioning

confidence: 98%

Let’s Talk About This in Public: Consumer Expectations for Online Review Response

Zhang

Gao

Zheng

2019

Cornell Hospitality Quarterly

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Online consumer reviews are becoming one of the key drivers of hospitality firm performance. Although research has investigated different aspects of online reviews such as their volume and length, issues regarding the effectiveness of review response demand for further investigation. Drawing on theories of expectancy value and communication, we develop and test a framework of consumer expectations regarding company responses. Results from two experiments show that consumer preferences for responses to their online reviews depend on the factors of valence (positive vs. negative), explanation type (explained action vs. explained reaction), and response channel (private vs. public). Perceived usefulness is found to be the underlying mechanism that explains these effects. The study’s theoretical contributions and managerial implications are discussed.

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“…Perceived health risk was measured by four items adopted from existing research ( Quintal et al, 2010 ; Wong and Yeh, 2009 ). To measure hotel booking intention, four items were developed based on existing items ( Chan et al, 2017 ; Wang et al, 2015 ). All items of each construct were reliable (expected interaction: α = 0.96, perceived health risk: α = 0.93, hotel booking intention: α = 0.95).…”

Section: Studymentioning

confidence: 99%

Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanliness

Shin

Kang

2020

International Journal of Hospitality Management

416

373

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Highlights Hotels can reduce customers’ perceived health risk via technology innovation. Technology innovation can achieve social distancing and enhance cleanliness in the COVID-19 era. Perceived health risk mediates the relationship between expected interaction and booking intention. Perceived cleanliness moderates the impact of expected interaction on perceived health risk. The perceived health risk mechanism is effective in post-pandemic scenarios.

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The effect of online reviews on hotel booking intention: The role of reader-reviewer similarity

Cited by 124 publications

References 78 publications

Factors Affecting Consumers’ Decision for E-Hotel Booking

Factors Affecting Consumers’ Decision for E-Hotel Booking

Let’s Talk About This in Public: Consumer Expectations for Online Review Response

Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanliness

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