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Based on the key dimensions of the Metaverse environment (immersiveness, fidelity and sociability), this paper aims to develop the concept of sensory word-of-mouth (WOM) in Metaverse – the metaWOM. It attempts to upgrade the Reviewchain model and suggests the utilization of non-transferable tokens (NTTs) in curbing the explosion of fake WOM.

Following Macinnis’ (2011) approach to conceptual contributions, the authors browsed the currently available literature on WOM, Metaverse and NTT to portray the emergence of metaWOM.

By relying on Metaverse’s three building blocks, the authors map out the persuasiveness of metaWOM in the Metaverse-like environment. By incorporating NTT in the Reviewchain model, the authors upgraded it to provide a transparent, safe and trusted review ecosystem. An array of emerging research directions and research questions is presented.

This paper comprehensively analyzes the implications of a Metaverse-like environment on WOM and debates on technologies that can enhance the metaWOM persuasiveness. The proposed model in this paper can assist various stakeholders in understanding the complex nature of virtual information-seeking and giving.

This is the original attempt to delineate the sensory aspect of WOM in the Metaverse based on three crucial aspects of the Metaverse environment: immersiveness, fidelity and sociability. This paper extends the discussion on the issue of fake reviews and offers viable suggestions to curb the ever-growing number of fraudulent WOM.

Online consumer reviews are increasingly used by third-party e-commerce organizations to shed light on the positive and negative sides of the brands they sell. However, the large number of consumer reviews requires these organizations to shortlist the most helpful ones to cope with information overload. A growing number of scholars have been investigating the determinants of review helpfulness; however, little is known about the influence of cultural factors in consumer's evaluation of review helpfulness.

This study has adopted Hofstede's cultural values framework to assess the influence of cultural factors on review helpfulness. We used a sample of 570,669 reviews of 851 hotels published by reviewers from 81 countries on Booking.com.

Findings reveal that reviewers from cultural contexts that score high on power distance, individualism, masculinity, uncertainty avoidance and indulgence are more likely to write helpful reviews.

This is one of the first cross-cultural studies in marketing using a big data approach in examining how users of reviews from different countries evaluate the helpfulness of online reviews.

Recent figures show that users are discontinuing their usage of TripAdvisor, the leading user-generated content (UGC) platform in the tourism sector. Hence, it is relevant to study the factors that influence travelers’ continued use of TripAdvisor.

The authors have integrated constructs from the technology acceptance model, information systems (IS) continuance model and electronic word of mouth literature. They used PLS-SEM (smartPLS V.3.2.8) to test the hypotheses using data from 297 users of TripAdvisor recruited through Prolific.

Findings reveal that perceived ease of use, online consumer review (OCR) credibility and OCR usefulness have a positive impact on customer satisfaction, which ultimately leads to continuance intention of UGC platforms. Customer satisfaction mediates the effect of the independent variables on continuance intention.

Managers of UGC platforms (i.e. TripAdvisor) can benefit from the findings of this study. Specifically, they should improve the ease of use of their platforms by facilitating travelers’ information searches. Moreover, they should use signals to make credible and helpful content stand out from the crowd of reviews.

This is the first study that adopts the IS continuance model in the travel and tourism literature to research the factors influencing consumers’ continued use of travel-based UGC platforms. Moreover, the authors have extended this model by including new constructs that are particularly relevant to UGC platforms, such as performance heuristics and OCR credibility.

Consumers’ digital engagement can bring various benefits to both brands and consumers. Besides, few studies investigated the outcomes of engagement with restaurant brands on Instagram. Therefore, this study aims to examine the effect of consumer engagement (CE) with restaurant brands on consumer-related factors (namely, consumer’s brand knowledge, perceived enjoyment and consumer social interaction) and brand-related factors (namely, e-WOM and brand reputation), as well as the mediating role of consumer-related factors.

The sample consisted of 394 Instagram followers of restaurant/coffee shop brands, and covariance-based structural equation modeling and bootstrapping were used to assess the hypothesized relationships.

The results show that CE with restaurant brands on Instagram enhances brand-related outcomes as well as consumer-related outcomes. Moreover, consumer-related factors partially mediate these relationships.

The findings of this study provide insights for restaurant managers and digital marketers to stimulate consumer-brand engagement.

To the best of the authors’ knowledge, this study is among the first that examines the effect of CE with restaurant brands on consumer- and brand-related outcomes on Instagram. The context of the study is Iran, which adds to the literature on CE that mainly focuses on developed countries.

The conventional notion that adopting Artificial Intelligence (AI) positively affects firm performance is often confronted with various examples of failures. In this context, large-scale empirical evidence of the economic performance implications of adopting AI is poor, especially in the context of Small and Medium Sized Enterprises (SMEs). Drawing upon the Resource-Based View and the Digital Complementary Asset literature, we assessed whether the adoption of AI affects SMEs’ revenue growth.

First, we examine the relationship between the adoption of AI and SMEs’ revenue growth. Second, we assess whether AI complements the Internet of Things (IoT) and Big Data Analytics (BDA). We use firm-level data from the European Commission in 2020 on 11,429 European SMEs (Flash Eurobarometer 486).

Among the key findings, we found that ceteris paribus, the adoption of AI positively affects SMEs’ revenue growth and, in conjunction with IoT and BDA, appears to be even more beneficial.

Our results suggest that AI fosters SME growth, especially in combination with IoT and BDA. Thus, SME managers should be aware of the positive impacts of investments in AI and make decisions accordingly. Likewise, policymakers are aware of the positive effects of SMEs’ reliance on AI, so they may design policies and funding schemes to push this digitalization of SMEs further.

The travel and tourism industry (TTI) could benefit the most from artificial intelligence (AI), which could reshape this industry. This study aims to explore the characteristics of tourism AI start-ups, the AI technological domains financed by Venture Capitalists (VCs), and the phases of the supply chain where the AI domains are in high demand.

This study developed a database of the European AI start-ups operating in the TTI from the Crunchbase database (2005–2020). The authors used start-ups as the unit of analysis as they often foster radical change. The authors complemented quantitative and qualitative methods.

AI start-ups have been mainly created by male Science, Technology, Engineering and Mathematics graduates between 2015 and 2017. The number of founders and previous study experience in non-start-up companies was positively related to securing a higher amount of funding. European AI start-ups are concentrated in the capital town of major tourism destinations (France, UK and Spain). The AI technological domains that received more funding from VCs were Learning, Communication and Services (i.e. big data, machine learning and natural language processing), indicating a strong interest in AI solutions enabling marketing automation, segmentation and customisation. Furthermore, VC-backed AI solutions focus on the pre-trip and post-trip.

To the best of the authors’ knowledge, this is the first study focussing on digital entrepreneurship, specifically VC-backed AI start-ups operating in the TTI. The authors apply, for the first time, a mixed-method approach in the study of tourism entrepreneurship.

This study aims to explore US hotel guests’ privacy concerns with a twofold aim as follows: to investigate the privacy categories, themes and attributes most commonly discussed by guests in their reviews and to examine the influence of cultural proximity on privacy concerns.

This study combined automated text analytics with content analysis. The database consisted of 68,000 hotel reviews written by US guests lodged in different types of hotels in five European cities. Linguistic Inquiry Word Count, Leximancer and SPSS software were used for data analysis. Automated text analytics and a validated privacy dictionary were used to investigate the reviews by exploring the categories, themes and attributes of privacy concerns. Content analysis was used to analyze the narratives and select representative snippets.

The findings revealed various categories, themes and concepts related to privacy concerns. The two most commonly discussed categories were privacy restriction and outcome state. The main themes discussed in association with privacy were “room,” “hotel,” “breakfast” and several concepts within each of these themes were identified. Furthermore, US guests showed the lowest levels of privacy concerns when staying at American hotel chains as opposed to non-American chains or independent hotels, highlighting the role of cultural proximity in privacy concerns.

Hotel managers can benefit from the results by improving their understanding of hotel and service attributes mostly associated with privacy concerns. Specific suggestions are provided to hoteliers on how to increase guests’ privacy and on how to manage issues related to cultural distance with guests.

This study contributes to the hospitality literature by investigating a neglected issue: on-site hotel guests’ privacy concerns. Using an unobtrusive method of data collection and text analytics, this study offers valuable insights into the categories of privacy, the most recurrent themes in hotel guests’ reviews and the potential relationship between cultural proximity and privacy concerns.

The recent livestreaming commerce has magnified the role of influencer marketing, where the influencers are partnering with brands for product promotion. This study examines the impact of influencer attributes, interaction strategies and parasocial relationships on impulsive buying in livestreaming commerce.

A survey with 368 livestreaming commerce users was analyzed using the symmetric-thinking approach – partial least squares structural equation modeling (PLS-SEM) and asymmetric thinking approach – fuzzy set qualitative comparative analysis (fsQCA).

The results of PLS-SEM indicate that influencer trustworthiness, influencer interactivity and self-disclosure determine parasocial relationships, which in turn influence impulsive buying. The fsQCA finding returned three configurations with various combinations of the causal conditions (i.e. influencer attributes, interaction strategies, parasocial relationships, perceived fit uncertainty and perceived quality uncertainty) explaining the formation of impulsive buying.

These findings provide unique linear and nonlinear insights to explain the combinatory effects of influencer attributes, interaction strategies, parasocial relationships, perceived fit uncertainty and perceived quality uncertainty on impulsive buying in livestreaming commerce.

Users frequently target rival brands through direct criticism or indirect customer insults, yet the impact of such attacks on brand advocacy remains unexplored. The purpose of this study is to classify online attacks into brand-targeted attacks and consumer-targeted attacks and further investigate their differential impacts on brand advocacy and the underlying mechanism and a boundary condition of those impacts.

Three experimental studies using different types of brands (electronics, universities and sports footwear) are conducted to examine the effects of brand-related attack targets on brand advocacy.

This research shows that consumer-targeted attacks trigger higher brand advocacy through increasing perceived identity threat than brand-targeted attacks. Moreover, the effect of consumer-targeted attacks (versus brand-targeted attacks) on brand advocacy is mediated by perceived identity threat and mitigated when consumers’ identification with the attacked brand is strong.

The study’s findings yield practical applications for marketers and brand managers, assisting them in understanding consumers’ reactions to brand attacks. This study serves as a reference for firms to consider leveraging the association between brand identification and brand-related attack targets and uniting with loyal brand fans to manage online brand conflicts.

The present study extends prior literature on customer-brand relationships in the context of online attacks. Through investigating the impacts of brand-targeted and consumer-targeted attacks on brand advocacy, this research offers theoretical insights into consumers’ responses to online attacks with different targets.

China is the world’s largest consumer market for smartphones. Early adopters are highly influential in consumers’ decisions of new technologies. Therefore, understanding Chinese early adopters’ decision making in the smartphone market is of crucial importance to smartphone companies. There is a dearth of in-depth studies on the factors affecting consumers’ repurchase intention for smartphones. The purpose of this paper is to narrow this knowledge gap by developing a new conceptual framework explaining early adopters’ repurchase intention of smartphones.

Using 30 face-to-face interviews with Chinese early adopters of smartphones, the authors built a new theoretical framework to explain the factors that influence their repurchase intention.

Repurchase intention of smartphones is determined by aesthetic and utilitarian product-related factors (design appeal, perceived usefulness), socio-cultural factors (subjective norms, mianzi/face considerations), and brand-related factors (brand popularity, brand’s country of origin, perceived brand quality, and brand loyalty). The emerging framework also explores the factors affecting enhancing, maintaining, and saving mianzi/face.

In contrast to existing technology-driven models, the study’s emerging framework shows how aesthetic, socio-cultural, and brand-related factors can offer new insights in understanding repurchase intention in a rapidly developing market. As these factors are rarely examined in the information technology and/or marketing literatures, potential knowledge contribution can be highly expected.