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Companies understand the potential to use gamification marketing to facilitate a better connection. However, most endeavours in gamification fail. This study aims to identify the design factors that drive the marketing effectiveness of branded applications (apps) with gamification features.

This study investigates branded apps covering various industries such as hospitality, retail and financial services. A total of 296 respondents were recruited from an online questionnaire platform.

The results show that playability, design aesthetics, goal clarity, incentive provision and symbolic benefits were drivers of consumer–brand engagement, which in turn generated purchase intention, app continuance intention and brand loyalty.

Based on the elemental tetrad model, this study specified relevant factors identified in the literature to represent the technology, aesthetic, mechanical and story elements. The authors contribute to the literature by identifying design factors as drivers of consumer–brand engagement in the branded app context.

Numerous companies have launched branded applications to foster consumer–brand relationships. Due to fierce competition among branded apps, the retention rate is quite low. The facilitation of behavioural outcomes through branded apps is a highly relevant research area. This paper investigates the drivers of behavioural outcomes in the context of branded apps from an investment model perspective.

This work examines various branded apps primarily used by consumers in disparate product categories, namely, Target, Walmart, Under Armour, Nike, Pandora, Spotify, Starbucks, Burger King, Disney and Netflix. Four hundred and one valid online questionnaires were obtained and partial least squares structural equation modelling was used for data analysis.

The results obtained extend the investment model to the context of branded apps and show that app investment size and app satisfaction facilitate brand relationship commitment, successively enhancing app continuance intention, brand purchase intention and app word-of-mouth (WOM) intention. Furthermore, app confidence benefits and self-enhancement benefits facilitate app satisfaction, while app social benefits and special treatment benefits facilitate app investment size.

The present work applies an investment model to various branded apps to show how relationship components facilitate behavioural outcomes. We contribute to the literature by identifying four types of app relational benefits as drivers of relationship components in the context of branded apps.

With the rapid surge of mobile marketing, an increasing number of brands have launched branded emoticons in an attempt to build brand relationships with consumers. Despite the apparent promise of branded emoticon usage, there is only limited academic research on branded emoticons. This paper aims to build on impression management theory and the conceptualization of cuteness to investigate how the effect of cuteness in branded emoticon design influences perceived playfulness in mobile instant messaging (MIM) interaction and the creation of brand engagement in self-concept.

Consumers with usage experience of branded emoticons in MIM apps were recruited to complete an online survey. Partial least squares structural equation modelling was used to analyze the data.

Two facets of cuteness – kindchenschema cuteness and whimsical cuteness – can project a favourable social image to consumers that facilitates playfulness in social interaction and enhances brand engagement in self-concept, which leads to their willingness to purchase the brand and stickiness to the MIM apps.

The popularity of branded emoticons represents a new form of social interaction and an innovative way to build brand relationships. The present study is the first to examine the design aspects of branded emoticons and highlights that the cuteness of a branded emoticon may be a crucial factor in engaging consumers in MIM.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.

The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

The growing integration of artificial intelligence (AI) assistants and voice assistants provides a platform for AI to enter consumers’ everyday lives. As these voice assistants become ubiquitous, their widespread adoption underscores the need to understand how to create voice assistants that can naturally interact with and support users. Grounded in the stereotype content model from social psychology, this study aims to investigate the influence of perceived humanness and personality on building trust and continuous usage intentions in voice assistants. Specifically, a fresh perspective examining the determining factors that shape personality trait perceptions of competence and warmth in voice assistants is proposed.

An online survey of 457 participants and structural equation modeling is conducted to validate the research model.

Anthropomorphism, social presence and interactivity drive perceived warmth, whereas performance and effort expectations drive perceived competence. Perceived competence and perceived warmth together positively affect users’ trust in voice assistants, leading to a higher likelihood of continuous usage intentions.

This research provides profound theoretical contributions to the emerging field of human-AI interaction and offer practical implications for marketers aiming to leverage voice assistant personalities to build trusted and long-lasting interactions.

Dealing with online rumors or fake information on social media is growing in importance. Most academic research on online rumors has approached the issue from a quantitative modeling perspective. Less attention has been paid to the psychological mechanisms accounting for online rumor transmission behavior on the individual level. Drawing from the theory of stimulus–organism–response, this study aims to explore the nature of online rumors and investigate how the informational characteristics of online rumors are processed through the mediation of psychological variables to promote online rumor forwarding.

An experimental approach to this issue was taken; the researchers investigated how the informational characteristics of online rumors and the psychological mediators promote online rumor transmission.

Four information characteristics (sense-making, funniness, dreadfulness and personal relevance) and three psychological motivators (fact-finding, relationship enhancement and self-enhancement) promote online rumor-forwarding behavior.

Because any online rumor transmitted on social media can go viral, companies may eventually encounter social media-driven crises. Thus, understanding what drives rumor-forwarding behavior can help marketers mitigate and counter online rumors.

Sellers view facial recognition mobile payment services (FRMPS) as a convenient and cost-saving way to receive immediate payments from customers. For consumers, however, these biometric identification technologies raise issues of usability as well as privacy, so FRMPS are not always preferable. This study uses the stressor–strain–outcome (S–S–O) framework to illuminate the underlying mechanism of FRMPS resistance, thereby addressing the paucity of research on users' negative attitudes toward FRMPS.

Drawing from the stressor–strain–outcome (S–S–O) framework, the purpose of this study is to illuminate the underlying mechanism of FRMPS resistance. To this end, they invited 566 password authentication users who had refused to use FRMPS to complete online survey questionnaires.

The findings enrich the understanding of FRMPS resistance and show that stressors (i.e. system feature overload, information overload, technological uncertainty, privacy concern and perceived risk) aggravate the strain (i.e. technostress), which then leads to users’ resistance behaviors and negative word of mouth.

Advances in payment methods have profoundly changed consumers’ consumption and payment habits. Understanding FRMPS resistance can provide marketers with strategies for dealing with this negative impact. This study theoretically confirms the S–S–O paradigm in the FRMPS setting and advances it by proposing thorough explanations of the major stressors that consumers face. Building on their findings, the authors suggest ways service providers can eliminate the stressors, thereby reducing consumers’ fear and preventing resistance or negative word-of-mouth behaviors. This study has valuable implications for both scholars and practitioners.

This study investigates the determinants of effective human and artificial intelligence (AI) relationship-building strategies for brands. It explores the antecedents and consequences of consumers' interactant satisfaction with communication and identifies ways to enhance consumer purchase intention via AI chatbot promotion.

Microsoft Xiaoice served as the focal AI chatbot, and 331 valid samples were obtained. A two-stage structural equation modeling-artificial neural network approach was adopted to verify the proposed theoretical model.

Regarding the IQ (intelligence quotient) and EQ (emotional quotient) of AI chatbots, the multi-dimensional social support model helps explain consumers' interactant satisfaction with communication, which facilitates affective attachment and purchase intention. The results also show that chatbots should emphasize emotional and esteem social support more than informational support.

Brands should focus more on AI chatbots' emotional and empathetic responses than functional aspects when designing dialogue content for human–AI interactions. Well-designed AI chatbots can help marketers develop effective brand promotion strategies.

This research enriches the human–AI interaction literature by adopting a multi-dimensional social support theoretical lens that can enhance the interactant satisfaction with communication, affective attachment and purchase intention of AI chatbot users.

Financial technology (FinTech) is undergoing a transformation as a result of robotics and artificial intelligence. FinTech service providers are embracing contactless technology, including the development and widespread adoption of innovative payment service. Among the many types of contactless payment services, facial recognition payment (FRP) has gained in popularity. To capitalize on this rising popularity, comprehending the mechanisms underlying continuous usage intention toward FRP is essential. Drawing from the stimulus–organism–response (S-O-R) model, this study investigates how FRP attributes facilitate continuous usage intention.

In total, 321 Chinese FRP users completed an online survey. Partial least squares structural equation modeling analyzed the results of the survey.

The results reveal that relative advantage and compatibility, user-interface attractiveness and perceived security (stimuli) promote performance expectancy, effort expectancy and positive emotion (organism), which in turn foster FRP continuous usage intention (response).

This research presents an S-O-R model that incorporates several attributes from DOI theory, the UTAUT model and the AIDUA framework to elucidate the antecedents of consumers' continuous usage intention toward FRP. The findings corroborate the significance of the S-O-R mechanism in FRP, setting the groundwork for the acceptance and development of biometric authentication technologies in service contacts and banks. In addition, the study highlights opportunities and essential aspects for FinTech service developers and providers to consider in terms of their practical significance.