Dimensions of lodging guest satisfaction among guests with mobility challenges: A mixed-method analysis of web-based texts

Given that many lodging businesses cannot afford to provide satisfactory services to people with mobility challenges, this study recommends a strategic order of service attribute development to maximize customer satisfaction with minimal costs. The crucial lodging service attributes of this population are identified and distinguished by degrees of influence on customer satisfaction based on the analyses of 543 web travel reviews. The results suggests prioritizing the bottom-line delivery of basic and performance factors (i.e. room access and staff attitude capability), whereas optionally offering the delivery of excitement factors or above-and-beyond delivery of performance factors, such as luggage and equipment support and general lodging features. Being the first attempt to integrate quantitative and qualitative web content analysis with Penalty-Reward Contrast Analysis, this study captures the real-life tourist service evaluation criteria with improved accuracy and reliability. It also enables a thorough and efficient exploitation of customer-generated web textual data.     

Exploring the factors of gastronomy blogs influencing readers’ intention to taste

In recent years gastronomy blogs providing an important channel for electronic word-of-mouth (eWOM) to take place are quickly becoming a popular new source of reading material for blog readers. However, little is published to understand what factors from gastronomy blogs play critical roles in predicting readers’ intention to taste local food and beverages. Based on reviewing previous studies, this study developed a research model containing three main categories of variables: (1) inspiring taste desire (i.e., experiencing appeal and generating empathy), (2) forming taste awareness (i.e., providing image, delivering knowledge and presenting guides) and (3) facilitating interpersonal interaction (i.e., social influence and cybercommunity influence), and suggested that these potential variables can influence readers’ behavioral intention to taste directly. Data collected from 329 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The results indicated that excluding delivering knowledge, all the other proposed variables (i.e., experiencing appeal, generating empathy, providing image, presenting guides, social influence and cybercommunity influence) were the critical components significantly influencing online readers’ intention to taste, and the proposed model accounted for 70% of the variance. The findings of this study will not only help hospitality and tourism practitioners in understanding the perceptions of potential customers, but also provide insights into research on technology's influence on hospitality and gastronomy.     

An FsQCA Investigation of eWOM and Social Influence on Product Adoption Intention

Abstract

Following the causal complexity theory, fsQCA has emerged as an advanced methodology in examining hypotheses and creating new theories in social science. However, fsQCA falls short dealing with structural associations and with latent variables when multi-faceted scales are combined into a single indicator by mean. To extend the application of fsQCA, the study demonstrates an approach to investigate a multi-layered problem of eWOM, social influence, and product adoption intention. The findings from fsQCA successfully confirmed the results from the statistical approach that eWOM and social influence have structural associations with customer adoption intentions of new high-tech products.     

The effect of characteristics of source credibility on consumer behaviour: A meta-analysis

The aim of this research is to synthesise findings from existing studies on the characteristics of source credibility of electronic word of mouth (eWOM) communications in a single model by using meta-analysis. Findings from 20 research papers show that source expertise, trustworthiness, and homophily significantly influence perceived eWOM usefulness and credibility, intention to purchase, and information adoption. The results of this study add to existing knowledge of the influence of source characteristics on consumer behaviour, which will advance our understanding of information processing. Marketers can use the findings of this meta-analysis to enhance their marketing activities.     

‘Retweet for a Chance to…’: an analysis of what triggers consumers to engage in seeded eWOM on Twitter

Twitter provides an important channel for brands to seed electronic word of mouth (eWOM) by followers retweeting brand messages, but prior research has not established a theoretical framework for how brands can maximise eWOM. This study presents and tests a theoretical model incorporating interactive, textual and visual tweet features to predict eWOM, using tweets by leading brands from three industries. Industry was found to be an important moderator of the effect of tweet features; after controlling for the reach and frequency of tweets, hashtags, retweet requests and photos were consistently associated with a higher retweet rate across industries, but the effect of URL links, non-initial mentions and video varied across industries, in some cases decreasing the retweet rate. Implications for research and practice are discussed.     

How differences in eWOM platforms impact consumers’ perceptions and decision-making

ABSTRACT

This article aims to examine the effects of different features of various eWOM (electronic word-of-mouth) platforms on consumers’ perceived credibility of eWOM regarding the product-related risks. Based on the stimuli–organism–response (S–O–R) theory, this study establishes a model to explore the relationships among eWOM platforms, tie strength, social cues, and perceived eWOM credibility. A mixed design of 2 (eWOM platforms) × 2 (product-related risks) conditions experiment and a survey method is applied to verify the model. The results show that tie strength between eWOM publishers and recipients positively influences the perceived eWOM credibility. The volume of social cues in eWOM platforms positively influences the perceived credibility of a female, while the opposite is true for a male. Both tie strength and volume of social cues in social media are greater than those in e-commerce websites. For products with low risks, eWOM in e-commerce websites is perceived to be more credible. Findings implicate that interactive functions should be added to the product comment area to enhance communications between the reviewers and potential consumers. Findings also encourage the cooperation between e-commerce websites and social media and suggest that managers should develop proper strategies in different situations.     

Creating and detecting fake reviews of online products

Customers increasingly rely on reviews for product information. However, the usefulness of online reviews is impeded by fake reviews that give an untruthful picture of product quality. Therefore, detection of fake reviews is needed. Unfortunately, so far, automatic detection has only had partial success in this challenging task. In this research, we address the creation and detection of fake reviews. First, we experiment with two language models, ULMFiT and GPT-2, to generate fake product reviews based on an Amazon e-commerce dataset. Using the better model, GPT-2, we create a dataset for a classification task of fake review detection. We show that a machine classifier can accomplish this goal near-perfectly, whereas human raters exhibit significantly lower accuracy and agreement than the tested algorithms. The model was also effective on detected human generated fake reviews. The results imply that, while fake review detection is challenging for humans, “machines can fight machines” in the task of detecting fake reviews. Our findings have implications for consumer protection, defense of firms from unfair competition, and responsibility of review platforms.     

The more the better? Exploring the effects of reviewer social networks on online reviews

ABSTRACT

Conventional wisdom suggests that firms leverage key influencers (e.g. individuals with high centrality) in online communities to stimulate buzz. Using a large panel dataset including 1,569,264 online Yelp reviews and the ego-network of 366,715 individual reviewers over a nine-year period, this study examines the effects of number of ties and network density on the volume and valence of online reviews. In contrast with the general belief that key influencers always generate positive buzz, the findings show that they can adversely affect future review valence. Specifically, reviewers with many connections on Yelp can reduce the positivity of reviews of the same business in the next period. This finding has implications for marketing practice in online community management and social media intervention.     

Investigating the impact of social media images’ value,consumer engagement,and involvement on eWOM of a tourism destination: A transmittal mediation approach

Tourism organizations use social media to promote their destinations and attract new customers. However, there is a challenge in how tourism organizations can choose or create social media images to successfully attract consumers' attention, induce their engagement with the destination, and motivate their eWOM behavior. This study aims to identify and test the direct and indirect factors related to social media images of tourism destinations that could predict eWOM. Using the Stimulus-Organism-Response (S–O-R) as an umbrella framework, we integrated Ducoffe's model and the Elaboration Likelihood Model (ELM), to study the role of social media destination images' features (entertainment, informativeness, irritation, credibility, personalization, and incentives) on consumer's perceived value and eWOM through consumer engagement and involvement. Using a survey research method, we collected data from 307 individuals and tested the proposed structural model using the PLS-SEM-based transmittal mediation approach. The findings supported the proposed relationships providing valuable theoretical and practical implications.     

The effect of utilitarian and hedonic motivations on mobile shopping outcomes. A cross-cultural analysis

Mobile devices are ubiquitous in the lives of modern consumers, who use them for information-seeking and purchasing activities, fostering the emergence of m-commerce. This trend has been exacerbated by the COVID-19 pandemic, which has boosted m-commerce growth in both developed and developing countries. Hence, there is a need for cross-cultural research concerning the factors affecting behavioural intentions. Drawing upon the hedonic information systems model, we measure the impact of utilitarian factors on satisfaction, repurchase intention, and eWOM through the mediation of enjoyment across two countries characterized by different stages of m-commerce readiness and culture: China and Italy. Findings suggest that the impact of utilitarian factors on satisfaction is stronger among Italian users than Chinese users. On the contrary, for Chinese users, who use their mobile phones as a primary device to shop online, the mediation effect of enjoyment on satisfaction and eWOM is stronger. With this study, we contribute to cross-cultural research in m-commerce and provide guidelines to mobile retailers operating in diverse international markets.