Search Results (129)

With the rapid advancement and widespread adoption of artificial intelligence (AI), AI-powered personalized product recommendation (AI-PPR) has become a core tool for enhancing user experience and driving monetization on short-form video platforms, fundamentally reshaping consumer behavior. While prior research has largely focused on impulse buying intention (I-BI)—purchases triggered by emotional and sensory stimuli—there remains a lack of systematic exploration of spontaneous buying intention (S-BI), which emphasizes rational and cognitively driven decisions formed in unplanned contexts. Addressing this gap, this study integrates the Technology Acceptance Model (TAM) with a perceived evaluation perspective to propose and validate a dual-mediation framework: “AI-PPR → Perceived Usefulness/Perceived Trust → S-BI”. Using a large-scale survey of Generation Z users in mainland China (N = 754), data were analyzed via SPSS 26.0, including reliability and validity tests, regression analysis, and Bootstrap-based mediation analysis. The results indicate that AI-PPR not only has a significant positive direct effect on S-BI but also exerts strong indirect effects through perceived usefulness and perceived trust. Specifically, perceived usefulness accounts for 35.17% and perceived trust for 31.18% of the mediation, jointly constituting 66.35% of the total effect. The findings contribute theoretically by extending the boundary of purchase intention research, differentiating rational S-BI from emotion-driven impulse buying, and enriching the application of TAM in consumption contexts. Practically, the study highlights the importance for short-form video platforms and brand managers to enhance recommendation transparency, interpretability, and trust-building while pursuing algorithmic precision, thereby fostering rational spontaneous buying and achieving a balance between short-term conversions and long-term user value. Full article

As immersive technologies reshape how people experience identity, emotion, and loss, virtual memorialization is emerging as an important application of virtual reality. This study examines the psychological mechanisms influencing user intentions to engage in virtual memorialization by extending the Technology Acceptance Model (TAM) to incorporate Avatar Attachment and Social Identity theories. A survey of 437 participants with diverse experiences in virtual worlds and memorial practices was analyzed using structural equation modeling. The results show that Avatar Attachment (AA) and Social Identity (SI) significantly predict perceived usefulness (PU), Perceived Role Importance (PRI), and behavioral intention (BI), with PU and PRI mediating these effects. Perceived ease of use (PEOU) directly influences both PU and BI. Furthermore, perceived human-likeness (PHL) moderates the effect of AA on PU, indicating that anthropomorphic avatars enhance the perceived emotional value of memorialization. However, PHL does not moderate the AA–PRI pathway, suggesting that the salience of avatars in mourning contexts relies more on narrative identity than visual realism. This research advances the application of TAM in immersive environments and contributes to digital thanatology by highlighting the interplay between identity, emotion, and technology. The findings provide design implications for creating user-friendly and emotionally meaningful virtual memorial platforms within emerging VR ecosystems. Full article

The integration of Generative Artificial Intelligence (GenAI) tools, such as ChatGPT, into higher education has introduced new opportunities and challenges for students and lecturers alike. This study investigates the psychological, ethical, and institutional factors that shape the adoption of GenAI tools in Saudi Arabian universities, drawing on an extended Technology Acceptance Model (TAM) that incorporates constructs from Self-Determination Theory (SDT) and ethical decision-making. A cross-sectional survey was administered to 578 undergraduate students and 309 university lecturers across three major institutions in Southern Saudi Arabia. Quantitative analysis using Structural Equation Modelling (SmartPLS 4) revealed that perceived usefulness, intrinsic motivation, and ethical trust significantly predicted students’ intention to use GenAI. Perceived ease of use influenced intention both directly and indirectly through usefulness, while institutional support positively shaped perceptions of GenAI’s value. Academic integrity and trust-related concerns emerged as key mediators of motivation, highlighting the ethical tensions in AI-assisted learning. Lecturer data revealed a parallel set of concerns, including fear of overreliance, diminished student effort, and erosion of assessment credibility. Although many faculty members had adapted their assessments in response to GenAI, institutional guidance was often perceived as lacking. Overall, the study offers a validated, context-sensitive model for understanding GenAI adoption in education and emphasises the importance of ethical frameworks, motivation-building, and institutional readiness. These findings offer actionable insights for policy-makers, curriculum designers, and academic leaders seeking to responsibly integrate GenAI into teaching and learning environments. Full article

The use of generative artificial intelligence (GenAI) chatbots in brands is growing exponentially, and higher education institutions are not unaware of how such tools effectively shape the attitudes and behavioral intentions of students. These chatbots are able to synthesize an enormous amount of data input and can create contextually aware, human-like conversational content that is not limited to simple scripted responses. This study examines the factors that determine chatbot brand trust in the adoption of GenAI in higher education. By extending the Technology Acceptance Model (TAM) with the construct of brand trust, the study introduces a novel contribution to the literature, offering fresh insights into how trust in GenAI chatbots is developed within the academic context. Using the convenience sampling technique, a sample of 609 students from public universities in North Central and Southwestern Nigeria was selected. The collected data were analyzed via partial least squares structural equation modelling. The results indicated that attitudes toward chatbots determine behavioral intentions and GenAI chatbot brand trust. Surprisingly, behavioral intentions do not affect GenAI chatbot brand trust. Similarly, the perceived ease of use of chatbots does not determine behavioral intention or attitudes toward GenAI chatbot adoption but rather determines perceived usefulness. Additionally, the perceived usefulness of chatbots affects behavioral intention and attitudes toward GenAI chatbot adoption. Moreover, social influence affects behavioral intention, perceived ease of use, perceived usefulness and attitudes toward GenAI chatbot adoption. The implications of the findings for higher education institutions are that homegrown GenAI chatbots that align with the principles of the institution should be developed, creating an environment that promotes a positive attitude toward these technologies. Specifically, the study recommends that policymakers and university administrators establish clear institutional guidelines for the design, deployment, and ethical use of homegrown GenAI chatbots, ensuring alignment with educational goals and safeguarding student trust. Full article

This study explored how AI affects the sustainability of competitive advantage in the tourism and hospitality sector, with a particular focus on the mediating roles of digital culture and digital skills in the lens of the Technology Acceptance Model (TAM). Data were collected via a structured questionnaire distributed to a purposive sample of 488 managers and supervisors working in five-star hotels, travel agencies, and DMCs across Saudi Arabia. The findings revealed that AI has a significant direct effect on sustainable competitive advantage and also exerts strong positive effects on both digital culture and digital skills. In turn, both of these internal enablers significantly contribute to sustaining a competitive advantage. Mediation analysis further showed that both digital culture and digital skills partially mediate the relationship between AI and sustainable competitiveness. The study addresses a notable gap in tourism research by providing localized evidence from a market undergoing rapid transformation under Vision 2030, and, taken together, extends TAM to an organizational lens by demonstrating AI’s role in shaping culture and skills that underpin a durable advantage while pointing to actionable priorities—targeting high-value AI use cases, conducting capability audits, institutionalizing continuous learning through visible leadership and role-based upskilling, and embedding culture- and skills-oriented KPIs within AI governance. Full article

As self-service technologies (SSTs) such as kiosks become embedded in service infrastructure, understanding the socio-cognitive drivers of adoption has grown in importance. This study extends the Technology Acceptance Model (TAM) by integrating Digital Readiness (DR), Trust in Technology (TT), Perceived Usefulness (PU), and Perceived Barriers (PB) into a single framework, and tests it using structural equation modeling (SEM) with survey data from 750 kiosk users in China. TT emerges as the strongest direct predictor of intention to use (IU) and also increases PU while reducing PB. The deterrent effect of PB exceeds the positive effect of PU. DR promotes adoption indirectly by raising TT and PU and lowering PB, whereas its direct path to IU is negative, suggesting a tension between readiness and heightened expectations. Multi-group analyses show that non-digital natives and low-frequency users are more sensitive to trust-related factors, whereas digital natives and high-frequency users respond more to barrier reduction. These findings integrate trust and barrier perspectives into TAM and reconceptualize DR as an ambivalent antecedent. Practically, a segment- and journey-oriented design frame centered on trust and friction provides a common reference for aligning kiosk design, KPIs, and investment decisions across industries. Full article

As Generation Z increasingly dominates the consumer market, understanding their purchasing behaviour in online marketplaces has become crucial for businesses aiming to engage this digitally native and environmentally conscious demographic. The present study aims to explore Generation Z′s purchasing behaviour in e-commerce platforms through the lens of the Technology Acceptance Model (TAM), while incorporating additional factors such as sustainability and environmental awareness. A partial least squares structural equation modelling (PLS-SEM) analysis using WarpPLS 8.0 was conducted on a sample of 636 Generation Z respondents from Romania. The results suggest that online marketplaces can enhance consumer engagement by integrating eco-friendly practices and emphasizing sustainable product offerings. This research contributes to the e-commerce literature by extending the TAM framework and by providing valuable insights for businesses targeting environmentally conscious digital consumers. Full article

The progression of generative artificial intelligence (GenAI) has lowered the technical barriers for consumers to independently customize clothing. Its profit potential has driven fashion brands to adopt GenAI-based interactive customization services. However, the factors influencing consumers’ behavioral intention toward GenAI-supported clothing customization services (GAICCS) remain underexplored. In this study, an extended framework is constructed based on the Technology Acceptance Model (TAM), incorporating trust, perceived enjoyment, service quality, and social influence to examine their effects on behavioral intention across cognitive, affective, service, and social dimensions. A total of 692 valid responses were collected from Chinese consumers via convenience sampling. A multi-stage SEM-ANN analysis was conducted to test the model. The results show that perceived usefulness (β = 0.237, p < 0.001), perceived ease of use (β = 0.332, p < 0.001), social influence (β = 0.181, p < 0.001), and service quality (β = 0.093, p < 0.05) significantly enhance behavioral intention, with perceived ease of use being the most influential. Perceived ease of use and perceived usefulness also act as key mediators. Unlike previous studies, satisfaction showed no significant effect. This study underscores the importance of functional performance, social influence, and service quality in driving GAICCS adoption, providing theoretical insights and multi-level practical guidance for promoting GenAI in fashion contexts. Full article

This study investigated the factors influencing user acceptance of the Navigate on Autopilot (NOA) functionality in new energy vehicles in China. An extended Technology Acceptance Model (TAM) was developed, incorporating additional factors such as social influence, travel scenarios, price value, perceived trust and perceived risk. A questionnaire survey was conducted in Guangzhou, China, and 260 valid responses were obtained. Structural equation modeling (SEM) was used to analyze the relationships between the factors. The results indicated that perceived ease of use, perceived usefulness, travel scenarios, price value, and perceived trust had significant positive effects on attitudes towards NOA, whereas social influence and perceived risk did not. Attitude was the primary determinant of the behavioral intention to use NOA. The findings suggest that to enhance NOA acceptance, new energy vehicle companies should emphasize specific application scenarios, reduce technology costs, provide value-added services, and strengthen user trust in the technology. This study contributes to the understanding of NOA acceptance and provides practical insights into the promotion of driver assistance systems in the context of new energy vehicles in China. Full article

The main objective of this paper is to examine the factors influencing investor intention to adopt robo-advisory services in Saudi Arabia, with a particular focus on sustainability and platform interface quality (PIQ) within a socio-technical framework. Drawing on the Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), Value-Based Adoption Model (VAM), and Trust theory, the research integrates constructs such as Knowledge about Robo-Advisors (KRA), PIQ, Green Perceived Value (GPV), and Perceived Trust (PT). Data were collected through a structured questionnaire targeting financially active individuals, with 387 valid responses analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that KRA significantly influences Intention to Use Robo-Advisors (IURA) both directly and indirectly, through GPV and Relative Advantage (RA), with only marginal support observed for Perceived Usefulness (PU). PIQ strongly influences perceived ease of use (PEOU) and PU, contributing to IURA, while PT significantly moderates the effects of KRA and PIQ. Multi-group analysis (MGA) further highlights heterogeneity across age, education, and investment groups, underscoring the contextual nature of adoption. The study highlights the critical role of PT, PIQ, and GPV alignment in investor decision-making when engaging with robo-advisory platforms. It offers theoretical contributions by extending traditional adoption models through the inclusion of green value and interface quality, and practical implications for FinTech developers and policymakers aiming to build inclusive, trustworthy, and environmentally aligned robo-advisory platforms. Full article

The rise of financial technology (FinTech) has generated substantial research on its adoption by customers and the associated implications for traditional banks. This systematic review addresses two questions: (1) What factors enable or hinder consumer adoption of FinTech? (2) How does consumer adoption of FinTech affect the performance of traditional banks? Following the PRISMA guidelines, we screened and analyzed 109 peer-reviewed articles published between 2016 and 2024 in Scopus and Web of Science. The findings show that adoption is driven by economic incentives, digital infrastructure, personalized services, and institutional support, while barriers include limited literacy, perceived risk, and regulatory uncertainty. At the bank level, adoption enhances operational efficiency, customer loyalty, and revenue growth but also generates compliance costs, cybersecurity risks, and competition. Consumer adoption studies primarily employ the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), often extended with trust and privacy constructs. In contrast, bank performance research relies on empirical analyses with limited theoretical grounding. This review bridges behavioral and institutional perspectives by linking consumer-level drivers of adoption with organizational outcomes, offering an integrated conceptual framework. The limitations include a restriction of the retrieved literature to English publications in two databases. Future work should apply longitudinal, multi-theory models to deepen the understanding of how consumer behavior shapes bank performance. Full article

To promote the sustainable development of urban smart transportation systems, this study constructs a structural equation model (SEM) based on the Technology Acceptance Model (TAM), incorporating extended variables including social influence, environmental awareness, privacy concerns, and service similarity to investigate users’ behavioral intentions toward Mobility as a Service (MaaS). The research systematically examines key factors influencing user adoption behavior and their underlying mechanisms, providing theoretical foundations and practical guidance for optimizing MaaS system design and policy making. Using SEM as the core analytical framework, this study employs mediation analysis, moderation analysis, and multigroup comparison to empirically examine the direct and indirect effects among variables, as well as group heterogeneity. Data were collected through an online questionnaire survey, with Analysis of Variance (ANOVA) applied to identify the differential impacts of demographic and travel behavior characteristics on users’ intentions and related psychological constructs, thereby supporting precise user segmentation and evidence-based policy interventions. Key findings include the following: (1) Social influence, ease of use, and environmental awareness boost MaaS adoption, while privacy concerns hinder it. (2) Freelancers/self-employed weaken the positive effects of usefulness, ease of use, and social influence on adoption. (3) Service similarity and ease of use effects vary significantly between single-mode and multimodal commuters. The findings extend the theoretical boundaries of TAM and provide both theoretical and practical support for the development of sustainable urban transportation systems. Full article

Digital wallets (DWs) have experienced significant growth in recent years. Still, at the same time, there are substantial differences in the level of adoption of these financial technologies between EU Member States. This research investigates the key factors affecting the intention to use DWs by analyzing previous research and applying an extended Technology Acceptance Model. In total, 418 respondents from the Baltic states participated in the online survey in 2024. Using partial least squares–structural equation modeling (PLS-SEM), the analysis revealed that the factors studied, such as perceived usefulness, perceived ease of use, social influence, facilitating conditions, and perceived trust, significantly influenced users’ intent to use DWs for financial services. Perceived trust emerged as the strongest predictor, and social influence moderated perceived ease of use and facilitated conditions that impacted users’ intent to adopt DWs. This study provides important insights into the factors that shape users’ intentions to use DWs and the interactions between these factors. In addition, the extension of the TAM strengthened the theoretical framework for the study of DW adoption. Full article

This study explores the determinants of startup intention within the context of e-commerce platform-based startups in South Korea. We employ an extended technology acceptance model (TAM) that integrates individual, social, and entrepreneurial characteristics. A two-step analytical approach is applied, combining variable extraction through data mining and hypothesis testing using structural equation modeling. The results indicate that personal and social factors—such as entrepreneurial mindset and social influence—positively affect perceived usefulness, while job relevance and exposure to successful startup models enhance perceived ease of use. In contrast, security concerns and technological barriers negatively impact these relationships, posing critical obstacles to platform-based startups. This study extends the TAM framework to the platform-based startup context, offering theoretical contributions and proposing policy implications, including promoting digital literacy, developing entrepreneurial networks, and addressing security and regulatory issues. These insights offer a deeper understanding of how platform environments shape entrepreneurial behavior, providing practical guidance for startup founders, developers, and policymakers. Full article

This study dives into what drives people to use AR filters in the catering industry, focusing on the Hong Kong market. The main idea is to determine how “perceived value” shapes users’ intentions to engage with these filters. To do this, the research combines concepts from two popular models—the extended Technology Acceptance Model (TAM) and the Satisfaction–Loyalty Model (SLM)—to understand what influences perceived value. The survey data were then analyzed with Structural Equation Modeling (SEM) to see how perceived usefulness, enjoyment, satisfaction, and value connect to users’ intentions. The results showed that “perceived value” is a big deal—the main factor driving whether people want to use AR filters. Things like how useful or enjoyable the filters are and how satisfied users feel all play a role in shaping this perceived value. These findings are gold for marketing teams and AR developers, especially in the catering world. Combining TAM and the Satisfaction–Loyalty Model offers a fresh perspective on how AR technology influences consumer behavior. On top of that, it gives practical advice for businesses looking to make the most of AR filters in their marketing and customer experience strategies. Full article