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The purpose of this paper is to examine how different types of user experience in TikTok impact purchase intention via commitment to the influencer and commitment to the platform, with customer type included to determine moderating effects. Three types of user experience are considered: information experience, entertainment experience and parasocial-relationship-based experience.

This study collected 458 valid questionnaires from TikTok users, employing the structural equation modeling approach to examine the proposed research model.

Information experience, entertainment experience and parasocial-relationship-based experience are found to critically stimulate user commitment to the influencer and commitment to the platform, in turn driving TikTok-based purchase intention. Tests incorporating customer type reveal that commitment to the influencer more strongly influences the purchase intention of repeat customers, with commitment to the platform more likely to stimulate purchase intention among potential customers.

On a theoretical level, the paper is among the first to examine TikTok-based user purchase intention with customer type as a moderator. On a practical level, the results can guide marketers to effectively promote products using TikTok and inspire TikTok managers to develop customized strategies to stimulate initial and repeat sales.

TikTok is moving to the stage of commercialization and monetization by introducing e-commerce features. Although this move should cultivate particularly fertile ground for companies to sell products, TikTok user purchase behavior has yet to receive sufficient research attention, with little currently known about their purchase motivations. The current study uncovers the significant antecedents of users' purchase intention through TikTok, and further reveals the motivational differences among potential and repeat customers.

In the vibrant world of social commerce (SC), where information flows freely, interactions thrive and online purchases abound, there is an escalating challenge. Users are uninstalling and disengaging due to approach and avoidance stimuli, a trend mirroring the approach-avoidance motivation model (AAMM). Our study, anchored in AAMM and the stimulus-organism-response (SOR) model, aims to dive into the complex dynamics of these factors that shape users' SC continuance intentions.

Our findings, drawn from 472 SC users in Malaysia, paint an intriguing research framework via PLS-SEM analysis by testing the proposed hypotheses. A purposive sampling technique was utilized, deliberately selecting respondents based on specific criteria. Subsequently, data were gathered through the distribution of face-to-face questionnaires at selected shopping malls, facilitating a focused and comprehensive exploration of consumer perspectives.

The empirical results demonstrate the following: (1) Users' determination to stay engaged on SC platforms hinges on approach factors, like emotional support, surveillance gratification and multisensory gratification. (2) Simultaneously, avoidance factors such as technostress and perceived deception exert their negative influence. (3) Flow experience, rooted in flow theory, emerges as the underlying mechanism connecting these duality stimuli, influencing the continuance intention.

In a departure from conventional research, our study pioneers a comprehensive approach and boldly confronts the research gap by introducing a rich tapestry of antecedents, embracing both the appeal of approach factors and the deterrence of avoidance ones, using the AAMM that sheds light on how individuals navigate between embracing opportunities and avoiding pitfalls based on perceived gains and losses. This holistic approach enables us to redefine our understanding of digital engagement dynamics, offering a captivating journey into the realm of user experience and intention that transcends the ordinary.

User discontinuance on short-video platform has become increasingly prevalent in recent years. Short-video discontinuance refers to reduced use, controlled use or suspended use of the short-video platform. In this study, we examined factors associated with discontinuance behavior on short-video platform.

From the perspective of stressor–strain–outcome (SSO), we put forward a theoretical model integrating perceived information overload and perceived system feature overload (stressors), dissatisfaction (psychological strain), flow experience and regret to explain discontinuance behavior on short-video platform (behavioral outcome). We collected 482 survey data from Douyin users in China, and empirically examined the proposed research model via Partial least squares structural equation modeling (PLS-SEM) technique.

Our results demonstrated that perceived system feature overload exerts a positive effect on perceived information overload. Perceived system feature overload has a stronger influence on dissatisfaction than perceived information overload. Regret increases user dissatisfaction, while flow experience decreases user dissatisfaction. We also discovered that dissatisfaction and regret have significant positive effects on discontinuance behavior. Interestingly, flow exerts no significant influence on discontinuance behavior.

This study enriches the body of knowledge on social media discontinuance by revealing the interaction and effects of flow experience, dissatisfaction and regret on discontinuance. This study also extends the understanding on the complex role of flow experience in leading to social media discontinuance. Additionally, this study deepens the research on the interaction between perceived system feature overload and perceived information overload as well as their different influences on negative emotion.

The purpose of this paper is to analyse the future of the implementation of artificial intelligence (AI) technologies in services experience provided by cultural institutions (e.g. museums, exhibition halls and cultural centres) from experts’, cultural tourists’ and users’ point of view under the Industry 5.0 approach.

The research was conducted using a qualitative approach, which was based on the analysis of the contents obtained from two roundtable discussions with experts and cultural tourists and users. A thematic analysis using NVivo was done to the data obtained.

From a futuristic Industry 5.0 approach, AI is considered to be more than a tool – it as an integral part of the entire experience. AI aids in connecting cultural institutions with users and is beneficial since it allows the institutions to get to know the users better and provide a more integrated and immersive experience. Furthermore, AI is critical in establishing a community and nurturing it daily.

The most important contribution of this research is the theoretical model focused on the user experience and AI application in services experiences of museums and cultural institutions from an Industry 5.0 approach. This model includes the visitors’ and managers’ points of view through the following dimensions: the pre-experience, experience and post-experience. This model is focused on human–AI coworking (HAIC) in museums and cultural institutions.

Since the introduction of the outstanding web AI chat system, ChatGPT, it has caused a significant impact in both academia and the business world. Many studies have started to explore its potential applications in various fields. However, there is a lack of research from the perspective of user experience. To fill this theoretical gap and provide a theoretical basis for the operation and design of related services, this study plans to develop a set of evaluation scales for AI chat system user experience and explore the relationship between various factors and user satisfaction.

This study obtained 41 evaluation indicators through literature review and user research. Subsequently, these indicators were used as questionnaire items, combined with satisfaction metrics. A total of 515 questionnaires were distributed, and factor analysis and linear regression were employed to determine the specific elements influencing user experience and the user satisfaction model.

This study found that the factors influencing user experience are usefulness, accuracy, logical inference, interactivity, growth, anthropomorphism, convenience, credibility, ease of use, creativity, and security. Among these factors, only accuracy, anthropomorphism, creativity, and security indirectly influence satisfaction through usefulness, while the rest of the factors have a direct positive impact on user satisfaction.

This study provides constructive suggestions for the design and operation of related services and serves as a reference for future theoretical research in this area.

Building on Stimulus-Organism-Response theory, the current study examines the influence of pickup service quality in buy-online pickup in-store service (BOPIS) on users' perceived relationship investment with the mediating role of users' perceived experience quality and relationship proneness. This research also demonstrates the subsequent impact of BOPIS users' perceived relationship investment on their relationship performance indicators, like their cross-buying behaviors (breadth), frequency of their purchase (depth) and longevity of their relationship (length) with the store. The moderating role of BOPIS users' service experience consciousness in a few proposed relationships was tested.

The research is descriptive, quantitative and cross-sectional investigation. The study employed a purposive sampling technique. It was conducted using data collected using a validated self-administered questionnaire from 786 Indian omnichannel shoppers who have used BOPIS services in the past. The proposed conceptual model was tested using Partial Least Squares-Structural Equation Modeling.

The results indicate that BOPIS users' perceived experience quality and relationship proneness positively mediate pickup service quality and perceived relationship investment. The users' perceived relationship investment subsequently significantly positively impacts different dimensions of their relationship performance with the store (breadth, depth and length). Additionally, BOPIS users' service experience consciousness has a significant negative moderating effect on the direct relationship between pickup service quality and different dimensions of relationship performance.

The study is conducted in the Indian population, where omnichannel retailing is still nascent.

This study addresses the need to investigate the relationship performance indicators of BOPIS users, like their cross-buying behaviors(breadth), frequency of their purchase(depth) and longevity of their relationship(length) with the store. This study is the first to show that pickup service quality might explain the relationship performance of BOPIS users through their perceived experience quality, relationship proneness and relationship investments. The moderating role of BOPIS users' service experience consciousness in a few proposed relationships was also tested for the first time.

This study aims to measure the effect of augmented reality (AR) on immersive experiences, place satisfaction, user engagement and perceived authenticity.

The population of the research consists of museum visitors visiting the Sakip Sabanci Museum in Turkey, which provides an interactive experience to the audience using AR technology via iPads. The data were collected both online and offline. The research was carried out with 397 questionnaire forms. The hypotheses were tested through smart partial least squares (PLS) 3.

Immersive experience positively affects place satisfaction, user engagement and perceived authenticity. It was also concluded that user engagement and perceived authenticity mediated the relationship between immersive experience and place satisfaction.

The entire universe could not be reached, as the study had limitations in terms of time, cost, accessibility and control difficulties. Therefore, the study was carried out with 397 visitors who visited the Sakip Sabanci Museum (SSM) in Turkey and used AR technology.

The study emphasized the importance of AR in cultural tourism. The interactions of museum visitors with AR can be greatly enhanced by immersive experiences. Expanding AR to provide different experiences can increase the number of visitors.

Although there are recent studies on AR, it seems insufficient to investigate and empirically examine this subject in the context of museums. No studies conducted in Turkey have investigated the current topic of this study. Conducting this research in Turkey with the proposed research model will make the topic easier to understand, proving the study's originality.

Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

This study aims to investigate the engagement gap between Metaverse and in-person travel, the influence of Metaverse tourism on tourists and the industry and the challenges and responses associated with Metaverse technology. The study presents practical cases and highlights the implications of this research for practice, society and future research.

This study uses a literature review to explore concerns about Metaverse technology in tourism. It analyzes the difference between in-person travel and Metaverse tourism, the impact on tourists and the industry and challenges and responses to Metaverse. The review shows a rising trend in Metaverse tourism research.

These findings suggest differences between Metaverse tourism and in-person travel. By providing personalized travel options, social interaction, immersive experiences and soliciting visitor feedback, it is possible to enhance the tourist experience. Additionally, the study highlights the opportunities and challenges that Metaverse tourism presents to the tourism industry. The study provides practical cases in the tourism industry and implications for practice, society and future research.

The study’s implications for Metaverse tourism are practical, societal and future research-related. Metaverse technology can enhance the tourist experience through personalized options, social interaction, immersive experiences and feedback. This inclusivity can promote social equity and cultural exchange. Further research is needed to explore the social effects of Metaverse tourism and its long-term impacts on local communities, economies and the environment.

This study contributes by exploring the impact of Metaverse tourism, supporting academic research and practice. It fills a knowledge gap by analyzing the application of Metaverse technology in tourism, providing insights for researchers and practitioners. It offers practical guidance by identifying opportunities and challenges in Metaverse tourism, fostering industry innovation. Additionally, it informs policymakers about the impact of Metaverse tourism on development.