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This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.

The study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.

The results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.

The study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.

This paper aims to investigate whether digital connectedness between family members, attained through social media, increases the intention to travel overseas to visit family or relatives. In the context of the education sector, this paper specifically investigates the likelihood of a family member traveling to see a family member who is currently studying in Australia, despite their regular interactions on digital social platforms.

This paper draws on the perspectives of earlier conceptual papers by Chacko et al. (2012) and Solnet and Hood (2008) in an effort to identify root causes and a possible solution. The context of Singapore and the international literature are also reviewed to establish theoretical and practical gaps that need to be filled.

The study finds that both “perceived media richness” of social media and communication applications and the “perceived connectedness” gained through social media and communication applications have a positive effect on the “intention to travel to the study destination.” Of the two variables measured in the study, perceived connectedness provides the strongest influence with nearly double the path coefficient as compared to the perceived media richness. Overall, an explanation of 32 per cent in one’s intention to travel provides a substantial discovery of travel intentions.

The role that digital social media like Facebook plays in human connectivity is not a foregone conclusion, when one could argue that digital connectivity especially enhanced by the richness of social media has the potential to replace or minimize physical relationships. Yet, this study demonstrates that such associations between the family members are in fact augmented by social media.

The purpose of this paper is to examine the extent to which presence, media richness, and narrative experiences yield the highest experiential value in augmented-reality interactive technology (ARIT).

A survey is performed to collect data. Valid questionnaires of 344 ARIT users are identified. The hypothesized associations are analyzed using structure equation modeling.

Empirical results indicate that narrative experience induces a higher experiential value than other simulative experiences, including presence and media richness.

Results of this study provide a valuable reference for managers attempting to design an ARIT process in order to optimize the experiential value in various online simulation environments.

This study adopts an integrated framework that incorporates narrative theory, media richness theory, and presence in the online ARIT. Exactly how narrative experience, media richness, and presence affect the formation of experiential value in the ARIT process is explored as well.

Virtual reality (VR), as a new type of media technology, significantly improves the audience experience with product presentation in the marketing communication field. The apartment rental market, particularly in China, has no exception in adopting VR technology in its communication strategy. VR usage has been boosted since the outbreak of COVID-19 and has become a widespread application in the global apartment rental market. Although extant studies have analyzed how real estate companies use VR technology to enhance customer experience, few studies have been made to explore the power of VR in apartment rental advertising, particularly in targeting the youth in China market. To fill this research gap, this study aims to figure out how young consumers perceive VR advertising and characteristics of VR used in apartment rental advertisements, and how VR advertising affects young consumers’ intentions to rent an apartment.

A cross-sectional survey was conducted in 2021 with 301 Chinese university students aged 18 to 23. All respondents were invited offline and guided to watch one selected rental advertisement with VR technology featuring an apartment of about 50 square meters and then complete a questionnaire.

VR’s media richness in the apartment rental advertising increases its sense of presence perceived by the survey respondents. Both VR’s media richness and sense of presence positively influence respondents’ attitudes toward the advertised apartment. If respondents evaluate the advertised apartment positively, they are more willing to rent the advertised apartment.

The sample size is not large enough to represent all Generation Z consumers in China. The use of the nonprobability sampling method also limits the generalizability of the study results.

To counter the challenges created by COVID-19, apartment rental service providers and apartment owners/landlords are suggested to enhance the application of VR technology to the apartment rental advertisements to grow young consumers’ interest in the advertised apartments and even their renting intention.

To the best of the authors’ knowledge, this is the first quantitative study to assess young consumers’ responses to VR apartment rental advertising in China.

The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media richness (MR) theory and Information Manipulation Theory 2 (IMT2).

A conceptual model was developed to understand customers' online shopping intention by watching deepfake videos. A quantitative survey was conducted among the 1,180 customers using a structured questionnaire to test the conceptual model, and data were analyzed with partial least squares structural equation modeling.

The outcome of this research provides the antecedents of the online shopping intention of customers after watching AI-based deepfake videos. These antecedents are MR, information manipulation tactics, personalization and perceived trust. Perceived deception negatively influences customers' online shopping intention, and cognitive load has no effect. It also elucidates the manipulation tactics used by the managers to develop AI-based deepfake videos.

The distinctive model that emerged is insightful for senior executives and managers in the e-commerce and retailing industry to understand the influence of AI-based deepfake videos. This provides the antecedents of online shopping intention due to deepfakes, which are helpful for designers, marketing managers and developers.

The authors amalgamate the MR and IMT2 theory to understand the online shopping intention of the customers after watching AI-based deepfake videos. This work is a pioneer in examining the effect of AI-based deepfakes on the online shopping intention of customers by providing a framework that is empirically validated.

This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.

This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.

The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.

The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.

The purpose of this paper is to understand the effect of platform characteristics (i.e. media richness and interactivity) on individual perception (i.e. outcome expectations) and consequent behavioral response (i.e. user participation in online health communities (OHCs)) based on the stimulus-organism-response (S-O-R) model.

This study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) for which data were collected from 321 users with OHC experience using an online survey.

The empirical results show the following: (1) the three dimensions of media richness significantly affect the three outcome expectations, except that richness of expression has no significant effect on the outcome expectation of health self-management competence. (2) Human-to-human interaction significantly affects the three outcome expectations. Moreover, compared with human-to-human interaction, human-to-system interaction has a stronger impact on the outcome expectation of health self-management competence. (3) The three outcome expectations have a significant influence on user participation in OHCs.

This study extends the understanding about how platform characteristics (i.e. media richness and interactivity) motivate user participation in the context of OHCs. Drawing on the S-O-R model, this study reveals the underlying mechanisms by which media richness and interactivity are associated with outcome expectations and by which outcome expectations is associated with user participation in OHCs. This study enriches the literature on media richness, interactivity, outcome expectations and user participation in OHCs, providing insights for developers and administrators of OHCs.

This study aims to investigate how business-to-business (B2B) companies use message strategies on social media platform and how these strategies are effective in improving customer perceived value and encouraging customer engagement, as well as how B2B companies differ from business-to-customer (B2C) counterparts in terms of utilization and effectiveness of social media message strategy.

Based on content analysis of Sina Weibo brand pages and survey of website visitors, this paper examines the differences of social media message strategies and their impacts upon customer perceived value and customer engagement between B2B and B2C companies.

B2B companies use more rational appeals and less emotional appeals, have lower degree of informativeness and perform better in interactivity and variety than B2C companies. These five dimensions of message strategy have different roles in engaging customers via perceived value across B2B and B2C settings.

The research makes significant contributions to B2B social media marketing literature by answering two interrelated questions, namely, “What companies are doing?” and “What companies should do?” on social media websites. Besides, it provides insightful implications for B2B companies on how to implement appropriate message strategies in their social media marketing efforts by conducting Importance-Performance Analysis.

Chatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human conversational agents. The purpose of this paper is to identify what affects users’ intention to reuse and whether they perceive any difference between the two.

A conceptual model was developed based on computer-mediated communication (CMC) and interpersonal communication theories. Data were collected online from four different continents (North America, Europe, Asia and Australia). Partial least squares structural equation modeling was applied to examine the research model.

The findings mainly reveal that media richness and social presence positively influence trust and reuse intention through task attraction and social attraction; IM users reported significantly higher scores in terms of communication experience, perceived attractiveness of the conversational agent, and trust than chatbot users; users’ trust in the conversational agents is mainly determined by perceived task attraction.

Customers’ evaluation of the communication environment is positively related to their perceived competence of the conversational agent which ultimately affect their intention to reuse chatbot/IM. The findings reveal determinants of chatbot/IM adoption which have rarely been mentioned by previous work.

Practitioners should note that consumers in general still prefer to interact with human conversational agents. Practitioners should contemplate how to combine chatbot and human resources effectively to deliver the best customer service.

This study goes beyond the Computer as Social Actor paradigm and Technology Acceptance Model to understand chatbot and IM adoption. It is among one of the first studies that compare chatbot and IM use experience in the tourism and hospitality literature.

This study aims to identify distinct online media user segments on the basis of three media theories, namely media displacement theory, media complementarity theory and media richness theory.

A large‐scale, mobile‐based web survey was conducted in Japan to assess behavioural variables (media time allocation, media richness perceptions, and media access motives) and demographics.

The latent class model reveals four distinct media user segments: dual media users (i.e. users of the internet on both the mobile and the PC); mobile internet users; PC internet users; and passive online users. Dual media users are likely to: spend more time on information searching; perceive greater levels of media richness in online media; and share common motives for accessing internet media via both mobile and PC. The findings are consistent with our theoretical expectations.

Any exploratory clustering of consumers is by definition a snapshot that depends on time and place. Consequently the findings would very likely have been different if the underlying data had been sampled at another time or in different locations. Despite this limitation the findings corroborate some of the basic tenets of theories of media competition and complementarity.

The fact that almost a third of online media users access internet content via both mobile and PC suggests the increasing importance of cross‐media strategies.

This is a pioneering study that examines media competition and complementarity between the mobile internet and the PC internet.