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Based on more than 2.7 million online reviews (ORs) collected with big data analytical techniques from Booking.com and TripAdvisor.com, this paper aims to explore if and to what extent environmental discourse embedded in ORs has an impact on electronic word-of-mouth (e-WOM) helpfulness across eight major destination cities in North America and Europe.

This study gathered, by means of Big Data techniques, 2.7 million ORs hosted on Booking.com and TripAdvisor, and covering hospitality services in eight different destinations cities in North America (New York City, Miami, Orlando and Las Vegas) and Europe (Barcelona, London, Paris and Rome) over the period 2017–2018. The ORs were analysed by means of ad hoc content analytic dictionaries to identify the presence and depth of the environmental discourse included in each OR. A negative binomial regression analysis was used to measure the impact of the presence/depth of online environmental discourse in ORs on e-WOM helpfulness.

The findings indicate that the environmental discourse presence and depth influence positively e-WOM helpfulness. More specifically those travelers who write explicitly about environmental topics in their ORs are more likely to produce ORs that are voted as helpful by other consumers.

Implications highlight that both hotel managers and platform developers/managers should become increasingly aware of the importance that customer attach to environmental practices and initiatives and therefore engage more assiduously in environmental initiatives, if their objective is to improve online review helpfulness for other customers reading the focal reviews. Future studies might include more destinations and other operationalizations of environmental discourse.

This study constitutes the first attempt to capture how the presence and depth of hospitality services consumers’ environmental discourse influence e-WOM helpfulness on multiple digital platforms, by means of a big data analysis on a large sample of online reviews across multiple countries and destinations. As such it makes a relevant contribution to the area at the intersection between big data analytics, e-WOM and sustainable tourism research.

The purpose of this research is to analyse the influence of mobile word of mouth (m-WOM), received at the physical store, which “challenges” the consumer's preferences in a webrooming experience. The impacts of the social relationship between the sender and the receiver of the m-WOM and product category (electronics versus fashion accessories) are examined.

An online experiment was carried out which manipulated the presence and type of challenging m-WOM, and product category, in a 3 × 2 between-subjects factorial design. The participants were 204 consumers recruited through a market research agency. Their perceptions about the helpfulness of the m-WOM, and their product preferences and choices, were analysed.

Receiving in-store m-WOM was perceived as helpful by webroomers and affected their preferences and choices. For electronics online reviews posted by anonymous customers were more influential than friends' opinions, whereas the opposite was the case with fashion accessories. The trustworthiness and expertise of the m-WOM source may explain the effects of m-WOM.

m-WOM entails challenges and opportunities for retailers in the omnichannel era. The findings suggest that allowing customers to access m-WOM may be beneficial; however, retailers must consider the type of m-WOM that may be most suitable for their businesses. Recommendations for referral and review sites are also offered.

This study examines the impact of challenging m-WOM on shopping experiences, combining online, mobile and physical channels. The results revealed the importance of the information source and product category in the determination of consumers' perceptions of helpfulness, preferences and choice.

In the field of hospitality, most studies use English reviews and neglect non-English sources. The purpose of this paper is to exploit a predictive framework for review helpfulness that can process both Chinese and English textual comments.

This study develops some methods for feature extraction from Chinese online reviews, extracts more comprehensive predictors and proposes a novel prediction framework of classification before regression. Hofstede’s cultural theory is used to explain differences in the determinants of the helpfulness of reviews in Chinese and English.

The findings reveal that travelers from various countries do have discrepant perspectives on reviews helpfulness. Chinese tourists pay more attention to the reviewer profiles, whereas American tourists pay more attention to the review-related features.

This research offers hoteliers with actionable implications for meeting the needs of travelers from dissimilar cultural societies. The authors’ prediction framework can be used by website developers to create a review helpfulness rating system that allows visitors to acquire beneficial information.

On the one hand, the methods developed for extracting features of Chinese review, the hybrid set of features with several novel predictors and the prediction framework proposed in this study contribute to the methodology. On the other hand, this study is one of the few articles based on Hofstede’s cultural theory to guide a cross-cultural study on reviews helpfulness in hotel sector, which in turn contributes to the theory.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

The authors' research examines how negative electronic word-of-mouth (e-WOM) alters focal customers' post-recovery justice perceptions and attitudes to determine their future behavior with the service provider. Specifically, this paper develops and tests a conceptual model to investigate how negative e-WOM alters focal customers' perceptual and attitudinal outcomes after the service recovery experience. It also examines the post-recovery effect of negative e-WOM on focal customers’ willingness to patronize the service after their recovery experience.

To test the hypotheses, two pretests and two experimental studies with created scenarios in the retail context were conducted.

The authors' findings reveal that services are judged during and well beyond failure and recovery occurrences. To maintain a loyal customer base, service managers should develop processes that address service complaints both within and beyond the service consumption stage. The authors also find that despite a favorable recovery, focal customers gravitate toward the failure experience and develop unfavorable attitudes toward the service provider, leading to likely defections.

The authors' research demonstrates the persuasive power of negative e-WOM at the post-service recovery stage, making a unique contribution to the service recovery literature. This research also contributes to the persuasive effect of negative e-WOM, demonstrating message context as a boundary condition of negative e-WOM effects. In general, the authors' work highlights the importance of understanding the psychological processes involved in eliciting the persuasive influence of negative e-WOM in the post-service recovery stage that may lead to the defection of “so-called” successfully recovered customers.

The study explored users' tendency of confirmation bias when processing congenial vs. uncongenial electronic-word-of-mouth (e-WOM) about mystery fictions, a hedonic product category with strong experience and hedonic characters.

A two-stage judgment approach was employed where the participants were asked to judge a set of mystery novels twice: one before, and another after they were exposed to positive and negative e-WOM. The first-stage judgment established two favored and two disfavored titles by each participant. They were then asked to read six consumer reviews – three positive and three negative – for each of the four titles. The procedures created four review evaluation situations: two congruent and two incongruent, which allowed the authors to assess the participants' perceptions of congenial and uncongenial reviews and their rating adjustments of the titles. Participants' involvement in mystery novels was also measured to test its moderating effect on confirmation bias.

Confirmation bias in the evaluation of e-WOM was observed and reinforced by the user's involvement in the genre. Congenial reviews were perceived to be significantly more credible, better reflect the intrinsic value of a title and less subjectively motivated than uncongenial reviews. Furthermore, after exposure to equal amount of positive and negative e-WOM, an asymmetrical adjustment of final rating of the titles was observed. A significantly greater downward adjustment was observed for disfavored than favored titles. Stronger positive confirmation bias was also observed in the evaluation of WOM.

Previous studies on e-WOM have shown conflicting findings on the relative efficacy of positive vs. negative reviews. By introducing the factor of prior attitudes, the study demonstrated that whether WOM is consistent with an individual's prior attitude, rather than the valences of WOM in itself, determines its persuasiveness. Thus, it established the confirmation bias in users' processing of e-WOM. The finding highlights the importance for marketers to establish a positive initial impression, which, as the findings demonstrated, helps alleviate the damages caused by negative WOM.

This is the first study that has ever attempted to study the effect of confirmation bias during the users' processing of e-WOM in an experimental setting. By having the participants judge the books before and after exposure to congenial and uncongenial e-WOM, the authors were able to establish the link between the users' prior commitment to a book and their subsequent judgment of both the titles and the e-WOM.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2020-0026

This study clarifies the integration-related effects of photos and text on consumer information processing and decision-making outcomes.

The authors conducted an experiment by recruiting 162 workers from Amazon Mechanical Turk. These participants were randomly assigned based on a full factorial, between-subject design with four possible conditions (2 [separate vs alternate layout] × 2 [photo-first vs text-first sequence]). The authors conducted a two-way analysis of variance to test the main effects and the interaction effects of layout and sequence on perceived diagnosticity, pleasantness feelings and attitudes toward products or services reviewed through electronic word-of-mouth (e-WOM); the authors also applied Process Models 4 and 8 to explore the mechanism of these effects.

The experimental results reveal that text-first sequence is generally more effective than photo-first sequence in enhancing perceived diagnosticity and attitudes toward products or services. However, when a photo is displayed first, a separate layout is more effective than an alternate layout in enhancing perceived diagnosticity and attitudes. By contrast, regardless of the sequence, an alternate layout is more effective than a separate layout in inducing pleasantness feeling.

Future studies should further explore photo-based e-WOM, including other photo characteristics (e.g. visual quality, quantity and content).

This study provides guidelines for businesses to use photos on social media to achieve strategic goals.

This study addresses an identified need; that is, how the presentation of photo cues (e.g. layout and sequence) influences consumer decisions.

Businesses need to make quick decisions and adjustments to fulfill the growing online demand. Previous studies examined various factors affecting the online sales performance of products such as books, electronics and movies; however, they paid limited attention toward the local brand clothing products. The current study investigates the importance of different kinds of seller-generated and consumer-generated signals such as price, discount, product ratings, review volume, review sentiment, number of questions and interaction between some of these factors for predicting the sales performance of clothing products.

The multiple linear regressions has been employed to investigate the influence of various predictor variables on sales performance. The study also examines the importance of these predictor variables by using different machine learning models, including random forest (RF), neural networks and support vector regression (SVR).

The findings of the study emphasize the importance of price and discount rates offered on the product. The quantitative characteristics of reviews, such as review volume and average rating, have been found to be more important predictors than sentiment strengths. However, the sentiment strength of reviews with higher helpfulness scores plays a significant role in predicting sales performance.

The study highlights the varying importance of seller-based and consumer-based signals in predicting sales performance. It also investigates the interaction effect of these two kinds of signals. The consumer-generated signals have been further divided into two components based on social influence theory, and the interaction effects of these components have also been examined.

This study aims to apply the stimulus-organism-response framework to uncover the underlying mechanism by which the perceived helpfulness of online customer reviews (OCRs) drives behavioural intentions in mobile travel app commerce. Also, the current study explores how vendor-driven perceived usefulness of a product and its attributes influence the mediated relationship between perceived helpfulness of OCRs (OCRs helpfulness) and behavioural intentions.

The online survey (n = 151) was used to collect the data. The authors used structural equation modelling and the bias-corrected bootstrap method to test the proposed conceptual model for mediation and moderated-mediation effect.

Findings indicate that the perceived OCRs helpfulness has an indirect positive effect, via trust and attitude, on travel app downloading intention. Moreover, results suggest that the presence of vendor cues (vendor-generated informational content about a travel app) does not significantly moderate the mediating effect of perceived OCRs helpfulness on travel app downloading intention.

The present study reinforces the applicability of the warranting principle in the context of travel app commerce by exploring the relative effectiveness of customer-generated and vendor-generated informational content in influencing travel app downloading intention.

本研究旨在应用SOR框架来解释在线评论的有效性影响在旅行APP行为意向的潜在机理。此外，本研究探索了供应商驱动的对产品的认知有效性和商品属性来影响认知有效性和行为意向的中介关系。

本研究运用网络调研 （n=151）来收集数据。本论文运用结构方程建模和偏差纠正辅助程序来测试提出的理论模型和调节式中介作用。

研究结果显示在线评论的有效性通过信任度和态度对旅行APP的下载使用意向具有间接正相关的作用。此外，结果显示当供应商信息（供应商制定的有关旅行APP的信息内容）并不能有效调节网络顾客评论对下载意向的中介作用。

本研究加强了担保原则在旅行APP贸易背景下的适用性，探索了顾客驱动和供应商驱动的信息内容对旅行APP下载意向影响的相对有效性。

The purpose of this paper is to investigate how consumers respond to price changes by analyzing online product reviews (OPRs) posted on a product (Amazon’s Kindle 2), and to suggest several future research topics on online consumers’ reactions embedded in OPRs.

An exploratory case study is conducted using OPRs added to the Kindle 2. By analyzing 6,714 OPRs, the authors examine how online consumers respond to two continual price decreases embedded in the observable (star rating and review depth) and implicit (positive and negative emotions) features of OPRs as well as how the number of OPRs per day has changed after two price drops.

The authors found that all four features of OPRs (star rating, review depth, positive emotion, and negative emotion) and the number of OPRs per day had significantly changed after two price decreases for both long-term and short-term periods. In addition, online consumers’ reactions to price decreases in terms of these four features and the change in the number of OPRs per day were different between the first and the second price drops.

This study investigates online consumers’ reactions to price decreases only. Future research should investigate other cases where price changes under the dynamic pricing strategy in order to find the relationship between price increases/decreases and consumers’ reactions.

This study implies that online merchants should consider consumer groups’ innovation adoption stages and make strategic decisions for price decreases to improve the sales of their products.

While prior research involving the effects of price changes on consumers’ reactions has focussed on offline consumers, this is among the first attempts to address the long- and short-term reactions to price changes in terms of both the observable and implicit features of OPRs, and suggests that consumers’ reactions to price changes in OPRs are more complex.