Will the relevance of review language and destination attractions be helpful? A data-driven approach

Hlee, Sunyoung; Lee, Hyunae; Koo, Chulmo; Chung, Namho

doi:10.1177/1356766720950356

Cited by 14 publications

(20 citation statements)

References 81 publications

(172 reference statements)

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“…Online reviews play an important role in consumers' attitudes and their purchase decisionmaking process (Hlee et al, 2020;Kim et al, 2016;Lee et al, 2020;Liu and Park, 2015;Mudambi and Schuff, 2010). Hence, consumers' purchase intentions and their behavioral reactions, influenced by the persuasive cues of OHRs, have been empirically validated by a number of studies (e. g., Berezina et al, 2016;Vermeulen and Seegers, 2009;Xie et al, 2011;Zhao et al, 2015).…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

How reviewer level affects review helpfulness and reviewing behavior across hotel classifications: the case of Seoul in Korea

Hlee

2020

IMDS

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PurposeThe purpose of this study is to explore the effect of reviewer qualification and credibility (RQC) and hotel classification involving online hotel reviews (OHRs). The study examines the effects of the reviewer level as a proxy of RQC on review helpfulness and reviewing behavior (review rating, review length). The study also included hotel classification as a moderating variable.Design/methodology/approachData from 1,968 reviews were collected from TripAdvisor.com using a web data-harvesting technique. Hypothesized relations in the model were tested with t-test and MANOVA analysis.FindingsThe empirical results show that the effect of reviewer level on review helpfulness is not significant. In addition, a high-level reviewer tends to leave a lower rating and a lengthier review than a low-level reviewer. Regarding the moderating effects, for the high-level reviewer, three-star independent hotels have a greater effect on review helpfulness.Research limitations/implicationsThe study has several useful implications for researchers, hotel industry when managing OHR and disseminating information to their potential consumers.Practical implicationsThe findings help online review website organizers manage the operation of RQC and hotel classification in a proper manner. Marketing managers, especially those of three-star independent hotels, can effectively utilize review management to the desired effect.Originality/valueUnlike previous studies, this study explores the effect of RQC on review helpfulness and reviewing behaviors across the hotel classification. In addition, this study contributes to the hotel industry developing more effective online reviews from the reviewer level and diverse hotel types (three-star independent, four-star chain, five-star luxury hotels).

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

How reviewer level affects review helpfulness and reviewing behavior across hotel classifications: the case of Seoul in Korea

Hlee

2020

IMDS

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“…First, we advance the eWOM literature by highlighting the role of endorsement styles and directly comparing the relative persuasiveness of explicit and implicit endorsements. While prior research shed light on the impact of eWOM language on its effectiveness and trustworthiness (Baker & Kim, 2019;Filieri, 2016;Hlee et al, 2021;Huang et al, 2022;E. Y. Wang et al, 2022;Wu et al, 2017), this is the first study that assessed the influence of explicit and implicit endorsement styles on persuasion in the travel & tourism context.…”

Section: Theoretical Contributionsmentioning

confidence: 99%

“I Love It” Versus “I Recommend It”: The Impact of Implicit and Explicit Endorsement Styles on Electronic Word-of-Mouth Persuasiveness

Liao

Feng

et al. 2023

Journal of Travel Research

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Consumers usually endorse tourism products differently when sharing positive electronic word-of-mouth (eWOM). This research examines the relative persuasiveness of two endorsement styles, that is, explicit endorsement (e.g., “I recommend it”) and implicit endorsement (e.g., “I love it”). Drawing on the persuasion knowledge model, we propose that explicit endorsements are less persuasive than implicit endorsements because the former trigger stronger persuasion knowledge. We further argue that source trustworthiness mitigates the persuasion effect difference between the two endorsement styles. This article assesses these hypotheses across different sources (anonymous reviewers, friends, influencers), channels (online community, social commerce platform, social networking app), and products (hotels, restaurants) using secondary data analysis and two experiments. Three studies provide support for our hypotheses. By revealing the relationship between endorsement styles and eWOM persuasiveness, this article provides important implications for implementing effective product endorsement.

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“…OCRs provide a rich source of data to extract the dimensions of customer satisfaction for tourism sectors ( Chen et al, 2019 ; Hlee et al, 2020 ; Joung, Kim & Kim, 2021 ; Lien, Wen & Wu, 2011 ; Zinko et al, 2021 ). The results of the studies using OCRs ought to be more dependable and exact than those statistical results acquired from conventional satisfaction surveys dependent on little data samples ( Sánchez-Franco, Navarro-García & Rondán-Cataluña, 2019 ).…”

Section: Literature Reviewsmentioning

confidence: 99%

Determining the factors affecting customer satisfaction using an extraction-based feature selection approach

Riantama

2022

PeerJ Computer Science

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The coronavirus disease 2019 (COVID-19) causes tremendous damages to the world, including threats to human’s health and daily activities. Most industries have been affected by this pandemic, particularly the tourism industry. The online travel agencies (OTAs) have suffered from the global tourism market crisis by air travel lockdown in many countries. How online travel agencies can survive at stake and prepare for the post-COVID-19 future has emerged as an urgent issue. This study aims to examine the critical factors of customers’ satisfaction to OTAs during the COVID-19 pandemic. A text mining method for feature selection, namely LASSO, was used to deal with online customer reviews and to extract factors that shape customers’ satisfaction to OTAs. Results showed that refunds, promptness, easiness and assurance were ranked as the most competitive factors of customers’ satisfaction, followed by bad reviews & cheap and excellent service & comparison. New factors to customers’ satisfaction were revealed during the global tourism recession. Findings provide OTAs guidelines to reset services priorities during the pandemic crisis.

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Will the relevance of review language and destination attractions be helpful? A data-driven approach

Cited by 14 publications

References 81 publications

How reviewer level affects review helpfulness and reviewing behavior across hotel classifications: the case of Seoul in Korea

How reviewer level affects review helpfulness and reviewing behavior across hotel classifications: the case of Seoul in Korea

“I Love It” Versus “I Recommend It”: The Impact of Implicit and Explicit Endorsement Styles on Electronic Word-of-Mouth Persuasiveness

Determining the factors affecting customer satisfaction using an extraction-based feature selection approach

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