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In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the Godspeed questionnaire series and tested across two hotel properties in Japan and the USA.

Potential participants were approached randomly by email invitation. A final sample size of 395 across two hotels, one in Japan and the other in the USA, was obtained, and the data were analysed using structural equation modelling.

The results confirm that perceived usefulness, driven by subjective norms and output quality, and perceived ease of use, driven by perceived enjoyment and absence of anxiety, are the immediate direct determinants of users’ re-patronage intentions for HSRs. Results also showed that users prefer anthropomorphism, perceived intelligence and the safety of an HSR for reusing it.

The findings have practical implications for the hospitality industry, suggesting multiple attributes of an HSRs that managers need to consider before deploying them in their properties.

The current study proposes an integrated model determining factors that affect the re-patronage of HSRs in hotels.

This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.

This study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.

This study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.

This study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

The study examines how the three dimensions of homophily (attitude, background, and value) influence the perceived usefulness, credibility, and enjoyability of travel content and follower behavior (i.e. willingness to search for more information and intention to visit the destination and purchase the tourism product). Likewise, the study investigates how content perception influences follower behavior.

A sample of 621 Instagram users from generations Y and Z who follow at least one travel influencer and intend to travel in the next twelve months was collected through an online survey. Partial least squares structural equation modeling was adopted to examine the data.

Attitudinal homophily influences follower behavior, value homophily impacts content perception, and background homophily has a counterproductive effect. Likewise, content perceived as useful and credible induces the intention to visit and purchase the tourism product.

The generalization of the results must be performed with care, as the context of analysis is limited to a social platform and only includes Portuguese individuals.

The findings help managers better understand which homophily cues influence content perception and maximize influencer persuasion. Based on the results, they can better decide which travel influencers should endorse their tourism products.

Research on homophily has neglected the multidimensionality of the concept and its analysis in the tourism context. By using a consolidated approach to homophily, content perception, and follower behavior, this study contributes to the tourism marketing literature and expands influencer marketing research.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

This study explores the tourists' behavioral intention toward tasting ethnic food by proposing 'enjoyment’ as an indirect mechanism in improvising the model of Wang. In other words, when affective and cognitive components are triggered positively while reading online gastronomy reviews on social media platforms, enjoyment is aroused, subsequently enhancing the desire to taste ethnic foods displayed online.

Data from 385 visitors from Kashmir, India, were gathered using a purposive sample technique. The research model was put to the test using PLS-SEM.

Direct and indirect mechanisms influence Behavioral Intention. Enjoyment acts as a mediator. Overall, the results validated the presence of three direct and full mediation paths.

This study will help tourism practitioners justify their promotional activities on social networking sites, particularly in endorsing regional ethnic dishes. For example, tourism authorities could collaborate with bloggers on social media and offer incentives to promote attractive images of ethnic food. Similarly, ethnic food outlets can improve online exposure and interactivity by encouraging travelers to leave feedback after visits.

Unlike other studies, this research broadens our understanding by focusing on direct and indirect mechanisms. The inclusion of a mediator enhanced the total variance of the dependent variable.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.

This study aims to explore tourism live streamers’ motivations of sharing their travel experiences based on the grounded theory.

The use of purposive and snowball sampling methods was used to conduct 22 in-depth semi-structured interviews. The manuscript was analyzed based on the grounded theory.

This study identifies five tourism live streamers’ motivations of sharing their travel experience, including information sharing, entertainment, self-presentation, monetary incentives and socialization. Information sharing and entertainment are identified as the most important motivations of travel livestreaming (TLS) among the motivations. Monetary incentive is identified as a new motivation for tourism live streamers compared to other social media users.

This study provides valuable suggestions for livestreaming platforms and tourism product providers to attract more tourism live streamers and better serve them.

To the best of the authors’ knowledge, this is one of the first studies to offer empirical findings and discussions on tourism live streamers’ motivations of sharing their travel experiences.

本研究旨在基于扎根理论探讨旅游直播主分享旅游体验的动机。

使用目的性和滚雪球抽样方法进行了22个深入的半结构化访谈。 本研究采用扎根理论对数据进行分析。

本研究发现了五种旅游直播主分享旅游体验的动机, 包括信息共享、娱乐、自我展示、金钱激励和社交。信息共享和娱乐被认为是旅游直播最重要的动机。与其他社交媒体的用户相比, 货币激励被认为是旅游直播的新动机。

本研究为直播平台和旅游产品提供商提供有用的建议, 以吸引更多的旅游直播者并更好地为他们服务。

这是对旅游直播主分享旅游体验的动机提供实证研究结果和讨论的首批研究之一。

este estudio tiene como objetivo explorar las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje según la teoría fundamentada.

Des méthodes d'échantillonnage raisonné et boule de neige ont été utilisées pour mener 22 entrevues semi-structurées approfondies. Le manuscrit a été analysé sur la base de la théorie ancrée.

este estudio identifica las motivaciones de cinco transmisores en vivo del turismo para compartir su experiencia de viaje, incluido el intercambio de información, el entretenimiento, la autopresentación, los incentivos monetarios y la socialización. El intercambio de información y el entretenimiento se identifican como las motivaciones más importantes de la transmisión en vivo de viajes (TLS) entre las motivaciones. El incentivo monetario se identifica como una nueva motivación para el transmisor en vivo del turismo en comparación con los usuarios de otras redes sociales.

este estudio proporciona sugerencias útiles para que las plataformas de transmisión en vivo y los proveedores de productos turísticos atraigan a más transmisores turísticos en vivo y les brinden un mejor servicio.

este es uno de los primeros estudios que ofrece hallazgos empíricos y debates sobre las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje.