Search Results (102)

This study examines the intention of Greek tourists who visit national touristic destinations to adopt Artificial Intelligence (AI) chatbots in the tourism sector. Using the UTAUT2 model as a framework, data were collected through a closed-ended questionnaire and analyzed with correlation and regression methods to identify the main drivers and barriers to this adoption. Results show that specific factors such as performance expectancy, hedonic motivation, and perceived innovativeness significantly and positively influence chatbot usage, emphasizing the role of usefulness, enjoyment, and innovation in shaping user acceptance. Conversely, factors such as inconvenience, habit, and difficulty of use negatively affect adoption, indicating the importance of overcoming usability challenges and resistance to change. These findings highlight the need for the development of accessible and engaging chatbot systems and underscore the value of continuous technological improvements. The study concludes that adopting AI-driven solutions can help tourism providers personalize services, improve operational efficiency, and enhance customer satisfaction, fostering sustainable competitiveness in the sector. Full article

Cultural heritage tourism is a vital part of Malaysia’s tourism sector, attracting visitors to iconic UNESCO sites like George Town and Melaka. However, these heritage sites face growing challenges from overcrowding and environmental degradation, which accelerate the deterioration of historic architecture and cultural artifacts. Preservation efforts often require site closures, which negatively impact tourist experiences and satisfaction. Thus, augmented reality (AR) offers a solution by supporting heritage management and preservation, allowing visitors to engage with virtual representations via mobile AR apps, thereby enhancing visitor engagement and travel experience. Despite global adoption, mobile AR apps often suffer from low user retention, with many users abandoning them shortly after downloading them. Understanding what drives continued usage is crucial for successful AR implementation. This study integrates the expectation confirmation model (ECM) and the unified theory of acceptance and use of technology 2 (UTAUT2) to examine the determinants affecting user’s experiential satisfaction and continued usage intention of mobile AR apps. An online survey of 450 domestic tourists in George Town and Melaka was conducted. Data analysis using structural equation modeling with SmartPLS 4.0 revealed that the integrated model offers a stronger predictive power and significantly outperforms ECM and UTAUT2 individually. The findings contribute valuable insights for researchers, app developers, tourism stakeholders, and policymakers. Full article

Student trust plays a pivotal role in shaping the future integration of artificial intelligence (AI) in higher education. This study investigates how AI Facilitating Conditions (FCs), Performance Expectancy (PE), and task type influence students’ System-like Trust (AST) and Human-like Trust (AHT) in AI and further examines the mediating role of human-like trust in fostering the willingness to continue AI-assisted learning. Drawing on valid data collected from 466 Chinese university students, we employed partial least squares structural equation modeling (PLS-SEM) in combination with artificial neural networks (ANN) to test the hypothesized relationships, mediating mechanisms and the relative importance of influencing factors. The findings indicate that AI facilitating conditions significantly enhance both system-like trust and usage intention; performance expectancy exerts a positive effect on both forms of trust, with particularly strong effects observed in subjective tasks. Moreover, system-like trust positively promotes human-like trust, and together, these dimensions jointly strengthen students’ intention to engage in AI-assisted learning. Results from the ANN analysis further highlight that performance expectancy, system-like trust, and facilitating conditions are the primary determinants of system-like trust, human-like trust, and usage intention, respectively. This study extends the application of interpersonal trust theory to the AI domain and offers theoretical insights for fostering more positive and effective patterns of AI adoption in higher education. Full article

As a pivotal carrier of emerging human–computer interaction technologies, artificial intelligence (AI) conversational agents (CAs) hold critical significance for research on the mechanisms of users’ continuance usage behaviour, which is essential for technological optimization and commercial transformation. However, the differential impact pathways of multidimensional perceived interactivity on continuance usage intention, particularly the synergistic mechanisms between technical and affective dual-path dimensions, remain unclear. This study investigates the personalized AI-based CAs project “Dialogue with Great Souls,” launched on a Chinese social platform, using survey data from 305 users. A hybrid approach combining partial least squares structural equation modelling (PLS-SEM) and artificial neural networks (ANN) was employed for empirical analysis. The results indicate that technical dimensions, such as control and responsiveness, are key factors influencing trust, while affective interactive dimensions, including communication, personalization, and playfulness, significantly affect social presence, thereby shaping users’ continuance usage intention. ANN results corroborated most PLS-SEM findings but revealed inconsistencies in the predictive importance of personalization and communication on social presence, highlighting the complementary nature of linear and nonlinear interaction mechanisms. By expanding the interactivity model and adopting a hybrid methodology, this study constructs a novel framework for AI CAs. The empirical findings suggest that developers should strengthen socio-emotional bonds in anthropomorphic interactions while ensuring technical credibility to enhance users’ continuance usage intention. This research not only advances theoretical perspectives on the integration of technical and affective dimensions in agent systems but also provides practical recommendations for optimizing the design and development of AI CAs. Full article

This study, based on the Decomposed Theory of Planned Behavior (DTPB), constructs and validates a systematic model to explore the key drivers influencing consumers’ continuous usage intention of sustainable Ready-to-Drink (RTD) beverage packaging. The model includes perceived value and social normative paths, introducing perceived sustainability (PS) and perceived value fit (PVF) as moderators to reveal the role of contextual perceptions in green consumption decision-making. Empirical results show that all conventional path hypotheses (H1–H6) are supported. Among the moderating effect hypotheses, H7b, H9a, and H10c are not supported, while the rest hold. Theoretical implications include the following: Perceived Usefulness (PU) and Perceived Enjoyment (PE) significantly and positively influence consumer satisfaction (SA), consistent with the Expectation Confirmation Model (ECM). Both external influence (EI) and interpersonal influence (II) significantly enhance subjective norms (SN), aligning with TPB theory. Self-efficacy (SE) and facilitating conditions (FA) positively affect perceived behavioral control (PBC), consistent with the DTPB model. Satisfaction, subjective norms, and perceived behavioral control significantly predict continuous usage intention (UI), with satisfaction showing the strongest effect, highlighting the importance of positive initial experiences for green behavior continuation. Full article

Against the backdrop of the low-altitude economy, with the widespread application of drones in sports scenarios, the driving mechanism of users’ long-term usage intention has become a key issue in technology adoption research. To investigate the critical factors influencing the continuous use of drone products by sports-involved populations, this study builds a factor model for users’ continuous use of drones. It is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, integrating the UTAUT2 model and specific user needs in sports scenarios. Both traditional structural equation modeling (SEM) and Bayesian structural equation modeling (BSEM) are employed for empirical testing. Through the analysis of 297 valid questionnaire responses, it is found that the Bayesian approach yields a better fit. Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Safety and Environmental Compatibility all exert significant positive impacts on users’ continuous usage intention, with Effort Expectancy having the most prominent influence. On this basis, service strategies for drone brands are proposed to support product design and service provision. This study preliminarily indicates that Bayesian analysis possesses advantages and potential in this field. Meanwhile, the factor model for users’ long-term drone usage can meet the development needs in sports scenarios, and it has strong feasibility as a design model for users’ long-term drone usage. Full article

With the increasing application of digital interactive installations in museums, their role in enhancing audience engagement and cultural dissemination effectiveness has become prominent. However, ensuring the sustained use of these technologies remains challenging. Based on distributed cognition and perceived value theories, this study investigates key factors influencing users’ continuous usage of digital interactive installations using the Capital Museum in Beijing as a case study. A theoretical model was constructed and empirically validated through Bayesian Structural Equation Modeling (Bayesian-SEM) with 352 valid samples. The findings reveal that perceived ease of use plays a critical direct predictive role in continuous usage intention. Environmental factors and peer interaction indirectly influence user behavior through learner engagement, while user satisfaction serves as a core mediator between perceived ease of use and continuous usage intention. Notably, perceived usefulness and entertainment showed no direct effects, indicating that convenience and social experience outweigh functional benefits in this context. These findings emphasize the importance of optimizing interface design, fostering collaborative environments, and enhancing user satisfaction to promote sustained participation. This study provides practical insights for aligning digital innovation with audience needs in museums, thereby supporting the sustainable integration of technology in cultural heritage education and preservation. Full article

The rapid growth of mobile financial services provides significant opportunities for enhancing digital financial inclusion among older adults. However, elderly consumers often lag in adoption and sustained usage due to psychological barriers (e.g., technology anxiety) and factors related to prior experience and comfort with technology (e.g., technology familiarity). This study investigates how technology anxiety and technology familiarity influence elderly consumers’ continuance intention toward mobile banking, while examining age as a moderator by comparing younger older adults (aged 60–69) and older adults (aged 70+). Using data from an online survey of 488 elderly mobile banking users in South Korea, we conducted hierarchical regression analyses. The results show that technology anxiety negatively affects continuance intention, whereas technology familiarity positively enhances sustained usage. Moreover, age significantly moderated these relationships: adults aged 70+ were notably more sensitive to both technology anxiety and familiarity, highlighting distinct age-related psychological differences. These findings underscore the importance of targeted digital literacy initiatives, age-friendly fintech interfaces, and personalized support strategies. This study contributes to the fintech literature by integrating psychological dimensions into traditional technology adoption frameworks and emphasizing age-specific differences. Practically, fintech providers and policymakers should adopt tailored strategies to effectively address elderly consumers’ unique psychological needs, promoting sustained adoption and narrowing the digital divide in financial technology engagement. Full article

As social robots become increasingly integrated into everyday life, understanding the factors that influence users’ long-term continuance intention is essential. This study investigates how various features of MOCCA, a social robot equipped with episodic memory, affect users’ continuance usage intention through perceived trust and parasocial interaction, within the framework of the Stimulus–Organism–Response (SOR) theory. A structural model incorporating key perceived features (intimacy, morality, dependency, and information privacy risk) was tested with survey data from 285 MOCCA users and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that intimacy and morality positively influence both trust and parasocial interaction, while information privacy risk exerts a negative effect. Dependency significantly reduces parasocial interaction but does not significantly impact trust. These findings highlight the importance of balancing human-like qualities, ethical responsibility, perceived autonomy, and privacy protection in social robot design to foster trust, enhance user engagement, and support long-term adoption. This study provides theoretical, managerial, and practical insights into the field of human–robot interaction (HRI) and contributes to the broader acceptance of social robots in everyday life. Full article

Recent advancements in virtual reality (VR) technology have introduced a new paradigm in exhibition culture, with digital storytelling emerging as a crucial component supporting this transformation. Particularly in virtual exhibitions, digital storytelling serves as a key medium for enhancing user experience and maximizing immersion, thereby fostering continuous usage intention. However, systematic research on the structural influence of VR-based digital storytelling on user experience remains insufficient. To address this research gap, this study examines the impact of key components of digital storytelling in VR—namely, interest, emotion, and educational value—on presence, immersion, enjoyment, and continuous usage intention through path analysis. The results indicate that interest, emotion, and educational value all have a significant positive effect on presence. Furthermore, while interest and emotion positively influence immersion, educational value does not show a statistically significant effect. Presence, in turn, has a positive effect on immersion, enjoyment, and continuous usage intention, while immersion also positively influences enjoyment and continuous usage intention. Finally, enjoyment was found to have a significant positive effect on continuous usage intention. This study empirically validates the effectiveness of digital storytelling in virtual exhibition environments, offering valuable academic and practical insights. Theoretically, it contributes to the field by elucidating the complex and hierarchical relationships among three core factors—interest, emotion, and educational value—and their impact on user experience. Practically, the findings provide strategic guidelines for designing virtual exhibitions that maximize user immersion and satisfaction, reaffirming the importance of storytelling content that emphasizes interest and emotion. Full article

Despite the rapid advancements in payment technologies, cash continues to play a significant role in modern society. This phenomenon presents a unique area of analysis, particularly within metropolitan societies such as those in the Jakarta metropolitan area in Indonesia. The present study aimed to investigate cash usage in the Jakarta metropolitan area by analyzing two cases: (1) cash usage in physical stores, and (2) intention to continue to use cash in daily activities. To this end, two analytical techniques were employed: logistic regression and structural equation modeling (PLS-SEM). These techniques were implemented using data from 400 respondents residing in the Jakarta metropolitan area. The results of the study indicate a preference for cash over digital payments in transactions among a significant proportion of the respondents. The determinant analysis further identified several factors influencing cash usage in physical stores, including education, employment status, and the number of bank accounts. Furthermore, this study identified attitudes toward behavior, subjective norms, and satisfaction as variables affecting the intention to continue using cash in Indonesian society. Full article

Different academic disciplines approach the concept of materials from varying perspectives, and exploring these diverse interpretations can reveal new avenues for creative expression. While scientific analysis offers important insights into the transformation of materials, artistic and humanistic frameworks provide complementary lenses that enrich our understanding. In the context of artistic creation, the intentional and thoughtful use of materials is crucial, often producing unexpected and profound effects that engage audiences on multiple levels. The deep connection between artists and their materials is fundamental for preserving and transmitting cultural values. As the exploration of material transformation within art continues to evolve, it opens up a wealth of creative opportunities. However, significant challenges remain, particularly in evaluating whether transformed artworks truly resonate with audiences and in developing robust criteria for assessing the process of material transformation. This study tackles these challenges by employing a two-phase evaluation framework, focusing on four pairs of paintings reinterpreted as ceramic artworks, with feedback gathered from 389 online participants. The results demonstrate that artworks crafted from diverse materials are accessible to a wide range of viewers, providing valuable insights into the artistic process and broadening perspectives on material usage in art. While artistic creation remains a subjective endeavor, future research should aim to identify consistent patterns in audience reception and further explore the expressive potential of various materials in artistic practice. Full article

The South Korean AI market has grown significantly, yet while chatbot adoption is well-studied, sustained use remains underexplored. This study surveyed 250 financial institution chatbot users in South Korea in February 2024, using SPSS and R to investigate quality effects on intention of continuous usage. Results showed that social presence, response accuracy, assurance, and interactivity positively influenced expectation confirmation. In contrast, responsiveness, reliability, and usability had no significant effect, while security negatively impacted frequent users, reflecting trust concerns. These findings guide financial institutions in enhancing chatbot retention through interactivity and trust. Conducted in a pre-generative AI context, this study suggests future longitudinal research to address evolving AI technologies and user behaviors. Full article

This study explores the psychological impact of dating app usage on the mental health of LGBTIQA+ individuals in Southeast Europe, focusing on key factors such as anxiety, cyberbullying, perceived security, and self-confidence. Data were collected through an online survey administered to a representative sample of active dating app users within the LGBTIQA+ community, enabling a comprehensive analysis of how these factors influence users’ emotional states, attitudes, and behavioral intentions related to dating app use. The findings reveal that, while dating apps provide important opportunities for social connection and support, they also pose significant risks. Cyberbullying was identified as a prominent issue, strongly associated with heightened anxiety, reduced self-confidence, and increased fear. Anxiety also showed a negative association with perceived security. Among the examined factors, fear and pleasure emerged as significant predictors of LGBTIQA+ users’ attitudes toward dating apps, which in turn influenced their intention to continue using them. The results underscore the need for enhanced security features and inclusive design practices that prioritize the psychological well-being of LGBTIQA+ users. By addressing these challenges, dating app developers and policymakers can create environments that support healthier interactions and promote more positive experiences for marginalized users. Full article

Massive Open Online Courses (MOOCs) have become increasingly prevalent in higher education, with the COVID-19 pandemic further accelerating their integration, particularly in developing countries. While MOOCs offered a vital solution for educational continuity during the pandemic, factors influencing students’ sustained engagement with them remain understudied. This longitudinal study examines the factors influencing learners’ sustained engagement with ThaiMOOC, incorporating demographic characteristics, usage log data, and key predictors of adoption and completion. Our research collected primary data from 841 university students who enrolled in ThaiMOOC as a mandatory curriculum component, using online surveys with open-ended questions and post-course usage log analysis. Logistic regression analysis indicates that adoption intention, course content, and perceived effectiveness significantly predict students’ Actual Continued Usage (ACU). Moreover, gender, prior MOOC experience, and specific usage behaviors emerge as influential factors. Content analysis highlights the importance of local language support and the desire for safety during the COVID-19 pandemic. Key elements driving ACU include video design, course content, assessment, and learner-to-learner interaction. Full article