Search Results (209)

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

As ad-supported subscription models proliferate across over-the-top (OTT) media platforms, understanding the psychological mechanisms and perceptual factors that underlie consumers’ transition decisions becomes increasingly consequential. This study integrates the Uses and Gratifications framework with a contemporary motivation-based perspective to examine how users’ media consumption motivations and advertising attitudes predict intentions to adopt ad-supported OTT plans. Data were collected via a nationally representative online survey in South Korea (N = 813). The sample included both premium subscribers (n = 708) and non-subscribers (n = 105). The findings reveal distinct segmentation in decision-making patterns. Among premium subscribers, switching intentions were predominantly driven by intrinsic motivations—particularly identity alignment with content—and by the perceived informational value of advertisements. These individuals are more likely to consider ad-supported plans when ad content is personally relevant and cognitively enriching. Conversely, non-subscribers exhibited greater sensitivity to extrinsic cues such as the entertainment value of ads and the presence of tangible incentives (e.g., discounts), suggesting a hedonic-reward orientation. By advancing a dual-pathway explanatory model, this study contributes to the theoretical discourse on digital subscription behavior and offers actionable insights for OTT service providers. The results underscore the necessity of segment-specific advertising strategies: premium subscribers may be engaged through informative and identity-consistent advertising, while non-subscribers respond more favorably to enjoyable and benefit-laden ad experiences. These insights inform platform monetization efforts amid the evolving dynamics of consumer attention and subscription fatigue. Full article

The rapid development of generative artificial intelligence (AI) systems such as ChatGPT (GPT-4) could transform teaching and learning. Yet, integrating these tools requires insight into what drives students to adopt them. Research on ChatGPT acceptance has so far focused on university settings, leaving school contexts underexplored. This study addresses the gap by surveying 506 upper secondary students in Baden-Württemberg, Germany, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Performance expectancy, habit and hedonic motivation emerged as strong predictors of behavioral intention to use ChatGPT for school purposes. Adding personality traits and personal values such as conscientiousness or preference for challenge raised the model’s explanatory power only marginally. The findings suggest that students’ readiness to employ ChatGPT reflects the anticipated learning benefits and enjoyment rather than the avoidance of effort. The original UTAUT2 is therefore sufficient to explain students’ acceptance of ChatGPT in school contexts. The results could inform educators and policy makers aiming to foster the reflective and effective use of generative AI in instruction. Full article

Influencer marketing is estimated to reach USD 32.55 billion by the year 2025. The extant research on virtual vs. human influencers’ effectiveness has reported mixed results. Currently, research has yet to explore how consumption motivation and influencer gender (virtual vs. human) may differentially impact consumer behavior. Likewise, whether antecedent factors such as prior attitudes toward the brand may affect the perceived authenticity and attractiveness of influencers has rarely been investigated. To fill this research gap, the current study examined virtual vs. human influencers’ effectiveness utilizing a 2 (influencer type) × 2 (product type) × 2 (influencer gender) between-subject online experiment. Specifically, Airbnb (a recreational product) and NJM (an insurance product) were respectively designated as a hedonic and utilitarian brand. The findings (N = 468) demonstrated that while prior brand attitudes toward a hedonic product had no effect on perceived influencer authenticity, the opposite was true for a utilitarian product. No significant difference was shown in perceived authenticity and attractiveness between a male and female (virtual or human) influencer. Structural equation modeling suggested that perceived social similarity between a participant and an influencer positively impacted the perceived attractiveness and authenticity of influencers and purchase intention. Hedonic instead of utilitarian motivation was found to be a positive predictor of purchase intention. Full article

In this study, we extend the UTAUT2 model to explore the determinants of green purchase intention in Taiwan. By incorporating environmental concern, government support, and green trust, the model highlights how contextual and trust-based factors shape sustainable consumption. Based on 590 valid survey responses, analysis using covariance-based structural equation modeling reveals that performance expectancy, effort expectancy, social influence, price value, environmental concern, government support, and green trust all positively influence green purchase intention. Notably, green trust also mediates the relationship between the core UTAUT2 constructs and green purchase intention. In contrast, hedonic motivation and habit show no significant effects, suggesting that sustainable consumption has not become habitual or emotionally driven behavior in Taiwan. These findings emphasize the importance of rational evaluation, social context, and policy support in driving green behavior and offer practical implications for promoting sustainable consumption. Full article

We investigated the configurational conditions influencing primary and secondary school teachers’ behavioral intentions (BIs) and usage behavior (UB) in adopting digital learning tools by using fuzzy set qualitative comparative analysis (fsQCA) and Tobit analysis. Based on the extended unified theory of acceptance and use of technology (UTAUT2) and by integrating TPK, configurations that drive or hinder teachers’ use of digital tools were identified. The results revealed that BI formation is driven by the core combination of facilitating conditions (FC) and hedonic motivation (HM); the synergy of FC, HM, and TPK; and the interplay of TPK and HM. UB was significantly promoted by the combinations of H with BI and TPK with BI. Conversely, the low levels of H and BI, or H and TPK lowered the levels of UB. By integrating fsQCA and Tobit analysis, the complex and asymmetric effects in digital tool adoption were understood, and recommendations were proposed to develop differentiated support strategies based on these configurational findings. Full article

This study examines the psychological mechanisms underlying virtual reality (VR) tourism experiences through an integrated theoretical framework centered on flow experience and visit destination intention. Drawing upon flow theory, the research investigates how interactivity, perceived vividness, and telepresence influence flow experience and subsequently affect hedonic motivation and perceived visual appeal in VR tourism contexts. Using partial least squares structural equation modeling (PLS-SEM) analysis of data collected from 255 VR tourism users across major Chinese metropolitan centers, the study reveals that perceived vividness and telepresence significantly impact flow experience, while interactivity shows no significant effect. Flow experience demonstrates significant positive relationships with hedonic motivation and perceived visual appeal. Furthermore, hedonic motivation and perceived visual appeal significantly positively affect visit destination intention. The findings advance the theoretical understanding of VR tourism by illuminating the psychological pathways through which technological characteristics influence behavioral intentions. These results offer practical implications for destination marketers and VR tourism developers in designing more effective virtual experiences that enhance destination visit intentions. Full article

With the rapid development of digital technology, the use of digital learning resources has become increasingly widespread and is now an integral part of higher education. However, there is a lack of research on engineering students’ behavioral intention to use digital resources and their digital literacy. This study, which is based on two waves of longitudinal survey data from 422 Chinese engineering students, employs the unified theory of acceptance and use of technology 2 (UTAUT2) model to systematically analyze the factors influencing engineering students’ behavioral intention to use digital learning resources and explore the longitudinal relationship between this intention and digital literacy. The results show that engineering students’ behavioral intention to use digital learning resources positively predicts their digital literacy. Effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit are positively related to engineering students’ behavioral intention, whereas performance expectancy and price value do not have significant effects. The findings extend the application of the UTAUT2 model in the context of digital education and reveal a longitudinal link between the use of digital learning resources and digital literacy. This provides theoretical support and practical guidance for optimizing digital learning environments, enhancing digital literacy in engineering students, and improving the design of teaching resources in higher education, contributing to the development of engineering education in China in the digital age. Full article

Generative artificial intelligence tools, such as Microsoft Copilot, are transforming the teaching of programming by providing real-time feedback and personalized assistance; however, their impact on learning, motivation, and cognitive absorption remains underexplored, particularly in university settings. This study evaluates the effectiveness of Microsoft Copilot compared to instructional videos in teaching web programming in PHP, implementing a quasi-experimental design with 71 industrial engineering students in Chile, divided into two groups: one using Microsoft Copilot and the other following instructional videos, with pre- and post-tests applied to measure knowledge acquisition while surveys based on the Hedonic-Motivation System Adoption Model (HMSAM) assessed cognitive absorption (enjoyment, control, immersion, curiosity) and technology acceptance (perceived usefulness, ease of use, and intention to adopt). The results show that, while both methods improved learning, students who used instructional videos achieved greater knowledge gains, higher levels of curiosity, and a stronger intention to continue using the technique, suggesting that instructional videos, by providing structured explanations and reducing cognitive load, may be more effective in the early stages of programming learning. In contrast, AI tools could be more beneficial in advanced stages where students require adaptive feedback, providing empirical evidence on the comparative effectiveness of AI-based and video-based instruction in teaching programming and highlighting the importance of balancing structured learning with AI-driven interactivity, with the recommendation that educators integrate both approaches to optimize the learning experience, using videos for initial instruction and AI tools for personalized support. Full article

Introduction: Obesity is a global health problem requiring effective interventions to achieve weight loss and maintain it in the long term. A major challenge for clinicians is weight regain (WR), defined as progressive weight gain following successful weight loss. WR is affected by multiple factors, including psychological traits linked to specific brain alterations. Understanding these mechanisms is crucial in developing strategies to prevent WR and to ensure effective weight control. Objectives: This narrative review aims to gather current findings on the psychological and neurobiological determinants of WR and to discuss the interplay between these factors. Methods: A literature search was conducted on PubMed, Medline, and Web of Science for English-language studies published between December 1990 and November 2024. Results: WR is driven by interconnected psychological and neurobiological factors that influence eating behavior and the regulation of body weight. Certain personality traits and emotional patterns are associated with specific changes in brain activity, which together affect vulnerability to WR. Although distinct mechanisms can be identified, the complexity of homeostatic and nonhomeostatic appetite control suggests that no single factor predominates. Conclusions: This review highlights the dynamic interplay between psychological and neurobiological predictors of WR. However, due to the narrative nature of this review, the focus on selected determinants, and the limited quality and size of the available studies, further research is needed to comprehensively understand causality and to improve relapse prevention strategies. Full article

Considering the rapid increase in mobile payment usage, numerous big tech companies have added mobile payment to the primary services that their platforms offer. However, extant research predominantly treats this added service as a standalone offering and investigates user adoption and behavior for this service independent of the primary services. Recognizing this gap in the literature, this study considers the added service as part of an extended ecosystem and examines different motivations for using the primary service. Therefore, this study examines how different motivations for using social networking services (SNSs) shape trust in the extended payment service and ultimately influence behavioral intentions. Drawing on the schema congruity theory, we conceptualize trust as a multidimensional construct—distinguished between cognitive and emotional trust—and explore the impact of trust in the primary service on the use of an added service. Specifically, we analyze survey data of 478 users of South Korea’s leading SNS. The results reveal that both hedonic and utilitarian motivations positively influence emotional and cognitive trust, which, in turn, drive behavioral intention. However, hedonic (utilitarian) motivation exerts a stronger effect on emotional (cognitive) trust. Overall, the findings enhance the knowledge regarding trust formation in extended service ecosystems and offer insights for tech firms integrating financial services into their platforms. Full article

Physical inactivity is a major global health risk, yet many fail to meet activity guidelines. Dog guardianship has been linked to increased physical activity, though the dog–guardian walking relationship remains understudied. This study applied the Actor–Partner Interdependence Model (APIM) to examine how guardians’ and dogs’ dual-process constructs influence walking behaviour. A sample of 127 Canadian dog guardians reported their walking habits, hedonic motivation, and expectations (Time 1) for themselves and their dogs, with follow-up walking behaviour assessed after three weeks (Time 2). Structural equation modelling revealed significant covariation in dog–guardian walking (r = 0.38, p = 0.03), supporting APIM. Guardians’ hedonic motivation (β = 0.37, p = 0.02) and expectations (β = 0.38, p = 0.02) predicted both human and dog walking. Findings confirm that guardians are the primary drivers of walking, suggesting interventions targeting guardian motivation and expectations may enhance physical activity in both humans and dogs, benefiting health. Full article

With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to explore the key factors influencing consumer purchase intentions for AIBE-recommended products in the context of the metaverse. We conducted an online survey with 302 Generation MZ consumers who have purchasing experience, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for in-depth data analysis and model evaluation. Additionally, we performed Multi-Group Analysis (MGA) to reveal differences among various occupations and generations. The findings indicate that attractiveness (ATT), anthropomorphism (ANT), and interactivity (INT) significantly influence hedonic motivation (HM) and social presence (SP). Furthermore, authenticity (AUT) positively affects both SP and trust in AIBEs (TAI). Consumer purchase intention (PI) is significantly impacted by SP but is not directly influenced by HM and TAI. Notably, technology readiness (optimism and innovativeness) positively and significantly influences consumer PI but does not alter the potential moderating effects of HM, SP, and TAI. This study not only broadens and deepens the application of CAB theory but also elucidates the potential development of AIBEs in future metaverse research, providing practical implications and guidance for marketers to enhance consumer purchase intentions and boost product sales. Full article

This study aims to determine the effects of the variables within the UTAUT 2 model on the intention to use a Fully Electric Car. In this context, data were collected through survey forms from 401 white-collar workers who are considered to have a higher economic status. Initially, validity and reliability analyses were conducted on the scales used in the Smart PLS program, and subsequently, the hypotheses were interpreted using the results obtained from structural equation modeling. In this study, it was found that effort expectancy, social influence, perceived ease of use, hedonic motivation, and habit had a positive and significant impact on the intention to use electric vehicles. Performance expectancy has a negative and significant effect on the intention to use electric cars, while price has no significant effect. It was determined that the intention to use electric vehicles was found to mediate the relationship between perceived ease of use and actual usage behavior. This research can offer significant contributions to literature, particularly by examining the influence of habit on behavioral intention and the effect of hedonic motivation on electric vehicle usage intention. By testing the UTAUT 2 model in the context of electric vehicle acceptance, this study supports the universality and applicability of the model to various technologies. Emphasizing the role of variables such as hedonic motivation and habit in electric vehicle acceptance adds a new dimension to the UTAUT 2 model. Thus, it makes an important contribution to technology acceptance research. Full article

This study explores the public acceptance of autonomous vehicles (AVs) using the Unified Theory of Acceptance and Use of Technology 2 framework. Drawing on survey data from 1000 commuters in Seoul, South Korea, this study examines the influence of performance expectations, effort expectations, social influence, hedonic motivation, and facilitating conditions on the behavioral intention to adopt AVs. Structural equation modeling reveals that hedonic motivation (β = 0.56, p < 0.001), price value (β = 0.47, p < 0.001), and performance expectancy (β = 0.64, p < 0.001) are critical determinants of AV acceptance. Additionally, risk perception negatively impacts behavioral intention (β = −0.25, p < 0.001), while policy support (β = 0.51, p < 0.001) and facilitating conditions (β = 0.46, p < 0.001) demonstrate substantial positive influences. Demographic analysis highlights age and gender as significant moderators, with younger users prioritizing performance expectancy and being more sensitive to risk, while older users exhibit a shift from hedonic to utility-driven motivations as they age. Women exhibit greater sensitivity to policy support and economic factors, while men respond more strongly to environmental considerations. In addition, prior experience with advanced driver assistance systems amplifies the influence of enjoyment on facilitating conditions, whereas inexperienced users are more affected by perceived risks. These findings underscore the importance of tailored interventions that address demographic variations, enhance user satisfaction, and balance cost-effectiveness with safety assurances. This study provides insights into actionable strategies for policymakers and industry leaders to promote AV adoption and support the evolution of sustainable urban mobility systems. Full article