How primary and supplementary reviews affect consumer decision making? Roles of psychological and managerial mechanisms

Wang, Yonggui; Tariq, Samia; Alvi, Tariq Hameed

doi:10.1016/j.elerap.2021.101032

Cited by 26 publications

(26 citation statements)

References 83 publications

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“…Online reviews are considered as an important component of electronic-word-of-mouth (eWOM; Cantallops & Salvi, 2014; Confente, 2015). They are very powerful in influencing consumers’ decision making (Y. Wang et al, 2021), such as trust and attitudes toward a hotel, booking intentions (El-Said, 2020), and hotels’ business outcomes, such as sales price (P Zhang et al, 2019) and market shares (Kwok et al, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…They are very powerful in influencing consumers' decision making (Y. Wang et al, 2021), such as trust and attitudes toward a hotel, booking intentions (El-Said, 2020), and hotels' business outcomes, such as sales price (P Zhang et al, 2019) and market shares (Kwok et al, 2017). On the flip side, consumer distrust toward a hotel through the development of online reviews will significantly affect their psychological discomfort, triggering negative eWOM and reducing purchase intentions (Ahmad & Sun, 2018).…”

Section: Literature Review Review Helpfulnessmentioning

confidence: 99%

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Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

Chunhong

Kwok

Xie

et al. 2021

Journal of Hospitality & Tourism Research

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A picture is worth a thousand words. User-generated photos (UGPs) are increasingly accompanying online reviews of hotels. This article draws on media richness theory to estimate the effects of UGPs on hotel reviews’ helpfulness. Based on a sample of 1,159,590 valid reviews with 464,316 photos, we utilized an integrated analytical model incorporating both econometric analyses and image-processing techniques. The results show that reviews accompanied by UGPs are generally rated as more helpful than those with textual content only. Furthermore, photos showing guestroom objects were rated as more helpful than those showing food & beverages. Finally, the positive effects of UGPs on review helpfulness were especially prominent for hotels with lower prices and negative reviews. This study adds new insights to the online review literature and advances the methodological approach in analyzing unstructured user-generated content. This study provides important implications for hotel managers and online booking platforms regarding UGP management.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Review Review Helpfulnessmentioning

confidence: 99%

Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

Chunhong

Kwok

Xie

et al. 2021

Journal of Hospitality & Tourism Research

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“…In addition, researchers may investigate the advertising response strategy to ordinary negative reviews in contexts in which negative reviews are more complex. In addition, we suggest that empiricism explores corresponding advertising response strategies for different types of negative reviews (e.g., primary and supplementary negative reviews; Wang et al, 2021) and provide managers with an enhanced comprehensive response to negative reviews.…”

Section: Discussionmentioning

confidence: 99%

“…Our research enriches the literature on how marketers can attend to negative reviews. Previous research has focused on how companies can manage negative reviews directly (i.e., a manager's direct customized response to the customer; e.g., Li et al, 2018; Wang et al, 2021). However, our work proposed using a non‐customized response to negative reviews via advertising.…”

Section: Introductionmentioning

confidence: 99%

Addressing negative product attribute reviews: The case of advertising product attributes and corporate social responsibility information

Wang

Chang

et al. 2023

Int J Consumer Studies

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Negative product reviews are bad for businesses. They can adversely affect product sales, brand evaluations, and brand loyalty. To attend to negative reviews, one approach is through advertising products or company virtues. The current study examines the efficacy of different advertising approaches (core product attribute advertising vs. non-core product attribute advertising vs. corporate social responsibility [CSR] advertising) in helping dilute the negative effect of dissimilar negative product attribute reviews (negative core product attribute reviews vs. negative non-core product attribute reviews). Through four experiments, we found that when the noncore attribute of a product had negative reviews, a core attribute advertising approach weakened the effect of negative reviews. However, CSR advertising was less effective. Furthermore, when the core attributes of a product had negative reviews, a non-core attribute advertising effort did not weaken, but actually augmented the impact of negative reviews. In addition, when the core attributes of a product received negative reviews, CSR advertising decreased the influence of negative reviews. Our findings provide theoretical and managerial implications for managing negative online reviews of product attributes.

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“…Online reviews are posted by customers who have experienced the hotel's services, so for potential customers, online hotel reviews are more persuasive than the hotel's own advertisements [5]. Online reviews will significantly influence customer attitudes, purchase decisions, and thus company performance [6][7][8][9]. A report on the Siteminder hotel services platform 2021 shows that more than two-thirds of of global travelers use travel review sites before booking, with 93% saying online reviews influence their booking decisions and 79% reading 6 to 12 reviews before making a purchase decision [10].…”

Section: Introductionmentioning

confidence: 99%

Sentiment analysis of hotel online reviews using the BERT model and ERNIE model—Data from China

Yu¹,

Liang

Zhu

2023

PLoS ONE

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The emotion analysis of hotel online reviews is discussed by using the neural network model BERT, which proves that this method can not only help hotel network platforms fully understand customer needs but also help customers find suitable hotels according to their needs and affordability and help hotel recommendations be more intelligent. Therefore, using the pretraining BERT model, a number of emotion analytical experiments were carried out through fine-tuning, and a model with high classification accuracy was obtained by frequently adjusting the parameters during the experiment. The BERT layer was taken as a word vector layer, and the input text sequence was used as the input to the BERT layer for vector transformation. The output vectors of BERT passed through the corresponding neural network and were then classified by the softmax activation function. ERNIE is an enhancement of the BERT layer. Both models can lead to good classification results, but the latter performs better. ERNIE exhibits stronger classification and stability than BERT, which provides a promising research direction for the field of tourism and hotels.

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How primary and supplementary reviews affect consumer decision making? Roles of psychological and managerial mechanisms

Cited by 26 publications

References 83 publications

Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

Addressing negative product attribute reviews: The case of advertising product attributes and corporate social responsibility information

Sentiment analysis of hotel online reviews using the BERT model and ERNIE model—Data from China

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