Dimensiones latentes en la adopción de ChatGPT en la universidad: modelo CHASSIS

This study investigates the factors influencing user satisfaction (US) and continuous usage intention (UI) of the digital banking platform in Indonesia. Utilizing a quantitative research approach, structural equation modeling (SEM) via SmartPLS was employed to analyze data from 376 users. The study integrates key constructs, including Task-Technology Fit (TTF), System Quality (SQ), Performance Expectancy (PE), US, and UI, into a comprehensive model. The findings confirm that TTF, SQ, PE, and US significantly influence UI. Specifically, higher TTF and SQ directly enhance PE (path coefficient = 0.871, t-value = 92.895) and US (path coefficient = 0.798, t-value = 47.957), positively impacting UI. Performance Expectancy emerged as a stronger predictor of UI (path coefficient = 0.559, t-value = 12.800) compared to the US (path coefficient = 0.245, t-value = 5.229), underscoring the critical role of perceived performance benefits in driving continuous usage. All five hypotheses were supported: TTF positively affects UI (path coefficient = 0.250, t-value = 7.154); SQ positively influences PE and US; PE positively impacts UI; and US positively affects UI. The Sobel test results indicated that PE significantly mediates the relationship between SQ and UI (Z = 12.60), and US also significantly mediates this (Z = 5.19). The R-squared values indicate the explanatory power of the model: PE (0.758), UI (0.956), and US (0.637), demonstrating that the model explains a substantial portion of the variance in these constructs. The study contributes to the literature by validating the integrated model, extending existing models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), and highlighting the importance of technical and perceptual factors in technology adoption. Practically, the results offer actionable insights for digital banking providers. Enhancing TTF and maintaining high SQ are crucial for fostering positive user experiences and encouraging continuous usage. Providers should also emphasize the performance benefits of their platforms to improve PE and UI. Despite its contributions, the study has limitations, including sample size and reliance on self-reported data, which may affect generalizability. Future research could expand the sample size, incorporate objective usage data, and explore additional factors such as social influence and facilitating conditions. Overall, the study provides a robust framework for understanding user behavior in digital banking and offers practical strategies for improving user satisfaction and retention in the industry.

This paper mainly discusses the impact factors of users' willingness and behavior to use online e-waste recycling platform. After analyzing domestic and abroad online e-waste platforms, and the integrated technology acceptance and usage model, perceived risk theory, this paper puts forward five factors that will affect the intention and behavior of that platform, namely: performance expectancy, effort expectancy, social factors, perceived risk, and marketing stimulation. Meanwhile, direct experience and indirect experience may have a moderating effect on the influencing factors. On this basis, this paper puts forward the framework of each factor and their impact on user's intention and behavior. Then, the scale of research variables is developed. In this paper, a total of 255 samples were collected and analyzed by descriptive statistics, reliability and validity analysis and structural equation modeling. The empirical results show that performance expectancy, effort expectancy, marketing stimulation will have a positive impact on the user's recycling intention, and perceived risk will have a negative impact on the user's recycling intention. Direct experience of users will have a significant moderating effect on effort expectancy, perceived risk, and marketing stimulation on the path of the user’s recycling intention, while the indirect experience doesn’t moderate the path of the user’s recycling intention. After that, this paper does a case study of the website huishoubao.com and offers suggestions to online e-waste platforms like huishoubao.com based on the case and the conclusion this paper draws up above. In practice, studying online recycling behavior of consumers and exploring how to encourage consumers to use online e-waste recycling platform can help obtain economic benefits for customers, stabilize the supply of e-waste products for legal recycling and processing enterprises, and to protect the environment. In theory, this paper makes up for the blank of the factors that influence the user's intention and behavior of online e-waste recycling platforms, and makes a further study on the moderating variables.

This paper adopts a technology acceptance model used for studying Robot’s acceptance and focuses on the acceptance of robotic technologies. Despite a wide range of studies on the acceptance and usage of robotics technologies in different fields, there is lacuna of empirical evidence on the acceptance of robotics technologies in the educational context. We contribute to the scholarship on robotics technologies in an educational context, by using qualitative semi-structured interviews, and proposing a research model to empirically explore the main factors affecting the acceptance of robotics technologies, and particularly among university students. We contribute to practice by offering insights on users' expectations and intentions toward the potential use of robot services to both robot developers, and educational institutions alike. The results revealed a potential impact of effort expectancy, performance expectancy, social influence, and facilitating conditions on the intention behavior towards using robots as academic advisors. Additionally, an emergent dimension (i.e. emotions) was found to have an influence on the behavioral intentions, via its proposed impact on performance and effort expectancies. Overall, social characteristics of robots ought to be considered when investigating their acceptance, specifically when used as social entities in a human environment.

The prospective relationship between a-priori intentions for and patterns of e-cigarette use among adults who smoke cigarettes

PurposeThis paper aims to compare the psychometric properties of the Research Motivation Scale (RMS) from faculty in schools of education in American research universities to previous findings on this scale when administered to science, technology, engineering and mathematics (STEM) faculty.Design/methodology/approachThis study was an exploratory, quantitative study using survey research methods, and utilizing confirmatory and exploratory factor analyses and statistical tests of population differences.FindingsResults indicate an adequate fit to a previously found three-factor structure. However, a new four-factor model, accounting for 47 per cent of the variance, was identified as a better fit: failure avoidance, intrinsic reward – satisfaction, intrinsic reward – joy and extrinsic reward. The overall reliability for the entire measure was 0.76. Intrinsic motivation and failure avoidance were rated statistically more important by education faculty than STEM faculty.Research limitations/implicationsAs an exploratory study and because of the chosen research approach, generalizations may be limited and further research in this area is recommended.Practical implicationsThis study contributes to the literature on RMS with data from education faculty. Results support conceptual frameworks regarding faculty outcomes and professional growth, and suggest ways faculty may be encouraged to increase research productivity.Social implicationsThis paper includes implications for societal support for research institutions by modeling factors that affect faculty motivations to produce research and thereby increase institutional productivity.Originality/valueThis study builds on conceptual frameworks, explores the use of the RMS with education faculty and compares faculty motivation to conduct research across disciplines.

Purpose – The purpose of this paper is to investigate market-contextual variations in consumers’ self-service technology (SST) usage intentions. Design/methodology/approach – Applications of the unified theory of acceptance and use of technology support the exploration of antecedents of usage intention for SSTs in two market contexts, through a survey among Taiwanese and Austrian college students. The cross-cultural nature of the study suggested the need for factor analyses to evaluate measurement equivalence. A Chow-Test confirmed structural stability, followed by regression analysis and independent samples t-tests to confirm the hypotheses. Findings – Substantial differences arise across market contexts that shape usage intentions. In a collectivistic, emerging market context (Taiwan), performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness significantly influence usage intention. In an individualistic, advanced market context (Austria), only performance expectancy and social influence have significant impacts on usage intention. Personal innovativeness moderates only the relationship between performance expectancy and usage intention. Practical implications – The findings suggest that usage intention is subject to the market environment in which the technology is introduced. Consumers are influenced by the local and institutional-cultural environment. Originality/value – Globalization has accelerated the launch of retail services innovations. It is imperative to understand consumers’ usage intentions from a global perspective. This study advances SST research by analyzing and comparing adoption behavior in an advanced vs emerging market setting.

Behavior intention of animation usage among university students

The purpose of the current study is to propose discriminated management strategies for mobile learning environments after observing the effects of mobile self-efficacy on performance expectancy and effort expectancy, the social influence on intention of use, and the effects of facilitating conditions and intention of use on learners ' actual use of mobile learning by adding mobile self-efficacy to the UTAUT model proposed by Venkatesh et al. (2003). We established hypotheses to determine whether mobile self-efficacy, performance expectancy, effort expectancy, social influence, and facilitating conditions affect intention of use and whether intention of use affects actual use. Results showed that when mobile self-efficacy and performance expectancy is higher, so is the intention of using mobile learning services. It was confirmed that the factors had significant indirect effects on the actual use by mediating the intention of use and that the intention of use directly affected actual use. However, the current research reported that effort expectancy, social influence, and facilitation conditions did not have significant effects on the intention of using mobile learning services. These results will contribute substantially to the design of effective mobile learning environments.

IntroductionThough technologies for individualization appear to benefit primary school students’ learning, studies suggest that their integration remains sparse. Technology acceptance research has largely focused on exploring teachers’ general acceptance of educational technologies, although factors might predict usage intentions differently depending on the specific usage purpose of an educational technology. Digital learning platforms for individualized practice are comparably challenging and complex to use and so far, predictors of primary school teachers’ intention to integrate such technologies into lessons are largely unknown. Meanwhile, research on teachers’ technology acceptance generally lacks comparability due to the absence of a shared theoretical model and usage purpose specification.MethodsIn a sample of 272 German primary school teachers, this study aims to identify predictors of teachers’ acceptance of digital learning platforms for students’ individualized practice in consideration of the unified theory of acceptance and use of technology (UTAUT). To ensure a shared understanding, teachers were provided with a video which specified the addressed usage purpose. Regarding teachers’ usage intention, the explanatory power of the standard UTAUT predictors was investigated and compared with an extended UTAUT model accounting for seven additional context-specific predictors.ResultsThe standard UTAUT significantly explained teachers’ usage intention, with performance expectancy, effort expectancy, and the availability of the necessary technical infrastructure showing significant associations with intention. However, neither a significant nor meaningful increase in explained variance was observed for the extended UTAUT model.DiscussionResults suggest that the standard UTAUT model is sufficient in explaining teachers’ usage intention and that its extension by context-specific predictors provides no added value. Acceptance facilitating interventions should therefore target performance and effort expectancy as well as the availability of technical infrastructure. Thus, underlining that successful implementation of complex educational technologies should consider both, individual and structural factors.

Background: Technological developments have triggered a transformation in the implementation of electronic medical records (RME) in Indonesia, in line with regulations that require the implementation of RME in all health service facilities by the end of 2023. Although it has been proven to increase efficiency and reduce medical errors, the implementation of RME faces challenges such as infrastructure readiness and risk factors cultural. Purpose: To identify factors that influence the success of RME implementation, including performance expectations and the use of RME in health facilities in Indonesia. Method: The design of this research is quantitative, observational analytical type with a cross-sectional approach. The population of this study were employees of Community Health Centers in Kediri Regency. The probability sampling technique using a random sampling approach obtained a sample of 336 employees in 33 Community Health Centers and SmartPLS 2.9.8 was used to test the hypothesis. The variables used in this research are: performance expectancy (X1), effort expectancy (X2), Readiness for Change (Z), and Usage Intention (Y). Results: The results of the research show that there is a direct influence of performance expectancy, effort expectancy, and Readiness to Change on Usage Intention with P = 0.000. Individual Change Readiness Mediates performance expectancy and effort expectancy on Usage Intention, which has a significant effect with a P value of 0.001. Conclusion: This research concludes that new insights into the critical role of change readiness as a mediator between technology acceptance factors and behavioral intentions.

Although factors influencing adoption of technology-enabled banking has been studied by many researchers, the construct perceived usefulness had been analysed as a single construct. Moreover, the measurement of perceived usefulness by researchers does not discuss sub-dimensions or sub-factors, which could contribute to perceived usefulness associated with a particular technological innovation. This article empirically examines the influence of various factors on user attitude and intention towards adopting mobile banking. Based on focus-group discussion and personal interview with bankers, technology acceptance model (TAM) and studies on technology adoption, we propose a mobile banking adoption model in Indian context. We also examine the impact of demographics on user attitude and intention. Exploratory factor analysis (EFA) on a sample of 367 respondents resulted in seven factors which were found to be reliable. Confirmatory factor analysis demonstrated significant convergent and discriminant validity. Logistic regression equation was used to estimate the degree of correct prediction of user attitude and intention towards mobile banking adoption. Perceived trust, perceived ease of use (PEOU), perceived lifestyle compatibility, perceived efficiency and perceived convenience significantly impacted user attitude. However, user attitude was not found to differ significantly between demographic variables. Similarly, perceived trust, PEOU, perceived lifestyle compatibility and perceived efficiency were found to positively and significantly affect user intention. User intention was found to significantly vary across demographic groups based on gender and household income.

Genetics plays a crucial role in the field of medicine, offering numerous applications. However, health professionals often have insufficient knowledge in this area. Therefore, it is essential to provide appropriate genetics education during university studies. This study aimed to assess the knowledge and attitudes towards genetic testing among final-year medical students at a public university in Ecuador. A cross-sectional study was conducted involving final-year medical students from a public university in Ecuador. The third version of the Genetic Literacy and Attitudes Survey was administered between April and May 2022. The study examined sociodemographic characteristics, genetic knowledge, and attitudes towards genetic testing. The study included 153 medical students, of which 58.2% identified as female. Most participants fell within the age range of 22 to 25 years old (85.0%). Regarding genetic knowledge, three-quarters of the participants (75.2%) demonstrated intermediate proficiency, while only 9.80% possessed a high level of knowledge. Attitudes towards the clinical and therapeutic applications of genetics, scientific advancements, access to conventional medicine, and other related topics were found to be appropriate. The findings suggest that most final-year medical students at a public university in Ecuador have intermediate genetic knowledge and hold appropriate attitudes towards genetic testing. However, higher education institutions should conduct a comprehensive analysis and restructure their curricula to better prepare students for the medical and technological challenges of the 21st century.

This research investigates the factors influencing the adoption of voice assistants (VAs) in online shopping among young Vietnamese consumers. Drawing from the literature on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the research explores performance expectancy (PE), facilitating conditions (FC), price value (PV), and habit (H) as key predictors of the intention to use (IU) VAs. We hypothesize that these factors, especially PE, PV, and H, significantly impact users' intentions to utilize VAs for shopping. Using a quantitative approach with a sample of 210 respondents, the research employs survey data collected through Google Forms. Analysis was conducted using SPSS and AMOS software for Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM). The findings reveal that PE, PV, and H are significant determinants of IU, while FC showed no substantial impact. These results underscore the importance of VAs in delivering high value at low cost, facilitating easier and more efficient shopping experiences. The implications of this research highlight the growing role of AI in shaping e-commerce, encouraging marketers to integrate VAs into their strategies to enhance consumer engagement and satisfaction.

Purpose – Blockchain technology, which has the characteristics of credibility, security, integrity and decentralization, has brought innovation to internet platforms that mediate peer to peer transactions, as well as changes to the contents distribution services. Blockchain-based copyright distribution platforms can solve problems which have been articulated on prior internet social networks: increased market dominance of platform business because of centralization with no reward to creators who upload on platforms, and lack of fairness, such as unfair profit distribution between the copyright holder and businesses. With this background, the current research confirmed the factors that affect the intention of usage and behaviors, targeting potential users of blockchain-based copyright distribution platforms. Research design, data, and methodology – Centered around the UTAUT2 Model, the research model was designed with 'Perceived Security' added as Construct, and 'Age' and 'Knowledge Level' added as moderating variables. For data, 607 responses were collected by an online survey, and 601 responses were included in the final analysis. We analyzed the research model and sample by using SPSS 23.0 and AMOS 23.0 on the collected responses. Results – First, results of research on whether Constructs make positive effects on Intention of use is: social influence, facilitating conditions, habit, and perceived security had positive effects on intention of use, and performance expectancy, effort expectancy, hedonic motivation, and economic value did not. Second, results of the research on whether facilitating condition, habit, and intention of use made an impact on using behaviors, it was shown that only habit and intention of use made positive effects. Third, in two groups divided by age above or under 40, group effort expectancy, intention of use, habit, and intention of use had controlling effects, and facilitating condition, intention of use, perceived security, and intention of use had effects in both groups. Conclusions – The research shows that no matter how great a blockchain-based platform is, if advantages of blockchain are not proved in various industries and utilized in real life like the internet, blockchain-based distribution systems will develop slowly. Rather than a short-term inducement emphasizing technology, there is a need for a strategic approach that can foster the environment.

Purpose: The purpose of this study is to explore whether higher educational institutes' e-learning programs on Facebook groups enhance Students' intention to use (IU) E-learning Programs or not by identifying influential determinants. By drawing on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Theory of Reasoned Action (TRA), and Student Engagement (SE) theory, this study assessed the role of SE in e-learners’ IU on Facebook perspectives. Methodology: This research applies quantitative research methodology using non-probability purposive sampling of a total of 211 higher secondary to post-graduate students in higher educational institutes, private and public universities in Bangladesh who are familiar and associated with e-learning programs of Facebook groups. Structural equation modeling (SEM) and mediation analysis as the data analysis method have been implemented by applying Co-Variance Structural Equation Modeling (CB-SEM). Findings: The result reveals that perceived ease of use (PEOU) and perceived usefulness (PU) from TAM, and social influence (SI) from the UTAUT model significantly affecting students' intention to use (IU) Facebook groups, with the strong effect of mediation of students' engagement (SE), except for the insignificant impact of hedonic motivation (HE). Practical Implications: Following the studies' implications and future recommendations, educators and e-learning providers should make Facebook groups more effective and enjoyable by integrating engagement with educational usage. Originality/Value: The originality of this study is in extending the four separate theories and models in enhancing students' future use of Facebook groups for e-learning programs, with the engagement level as a mediator in 'Meta.' Limitations: The present study employs a non-probability sampling method without the consideration of cross-cultural concerns and socio-demographic factors, focusing on other social media. Drawing on these issues, future academics should approach PLS-SEM, LISREL, and workable moderating variables.