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Mobile technology has become increasingly common in recent years with its booming development across the globe, leading to the gradual adoption of mobile health, which can reduce the risk of caregivers being infected. The widespread use of mobile health has brought many benefits to the healthcare industry, including increased efficiency for frontline caregivers and a better patient–physician relationship. However, it also presents some challenges. This study aimed to examine caregivers' behavior intention to use mobile technology in medical practice with a unified theory of acceptance and the use of technology two model. Satisfaction and self-efficacy were included as external variables and mobile technology identity as a moderator variable. A total of 281 valid questionnaires were collected from the nursing staff, and a structural equation model was used to test the hypotheses of this study. The results of the study showed that (1) self-efficacy had a significant effect on satisfaction and effort expectancy, (2) effort expectancy significantly affected performance expectancy, (3) performance expectancy and satisfaction had significant effects on behavior intention, and (4) mobile technology identity moderated the relationship between satisfaction and behavior intention. These results could inform medical institutions and facilities in launching mobile technology policies and education or training programs. [ABSTRACT FROM AUTHOR]

To explore the influencing factors of college students' learning intention to online teaching videos during the pandemic, this study considered 696 college students from Huangshan University in China. The T -test and ANOVA were utilized to analyze gender, grade, and discipline on college students' learning intention, and the regression analysis was utilized to explore four aspects including performance expectancy, effort expectancy, social influence, and facilitating conditions on college students' learning intention. The results indicate the following: first, using descriptive analysis, it is observed that college students did not exhibit a positive learning attitude toward online teaching videos during the pandemic. Second, the t test and one-way analysis of variance indicate that grades between freshmen and seniors significantly influence the learning intention of college students to online teaching videos, whereas genders and disciplines do not. Third, through regression analysis, it is observed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence college students' learning intention to online teaching videos. This study stipulates the following research proposals: resource construction, the optimization of the online teaching environment, advanced technology and psychological counseling. It is expected that the findings will provide references for studies on online teaching resources and online learning. [ABSTRACT FROM AUTHOR]

With rapid aging and the spread of chronic diseases, public eHealth services are helpful tools to monitor their physiological situations and develop healthy behaviors. However, the studies on older adults adopting public eHealth services have been relatively limited. We propose a modified United Theory of Acceptance and Use of Technology (UTAUT) model, considering the unique adoption patterns of older people. Our study shows that older adults adopting patterns are influenced first by social influence (SI) and facilitating conditions (FC), then influenced by performance expectancy (PE) and effort expectancy (EE). This model includes two moderating effects of performance expectancy (PE) and effort expectancy (EE) between two external constructs of social influence (SI), facilitating conditions (FC), and older adults' behavioral intention (BI) to adopt public eHealth services. A dataset of 510 questionnaires was collected on the use of a self-monitoring telecare device (Babybot) in Hsinchu City, Taiwan. The results demonstrate that SI and FC positively influence older adults' adoption of public eHealth services. Furthermore, PE positively moderates the relationship between FC and BI, while EE positively moderates the relationships between FC and BI, and between SI and BI. The findings reveal that PE and EE moderate SI and FC in affecting older adults' adoption of public eHealth services. This modified UTAUT model provides insights into the unique factors that drive older adults' adoption behavior. This study offers valuable policy and managerial implications for promoting older adults' adoption of public eHealth services. [ABSTRACT FROM AUTHOR]

This study uses a modified UTAUT model to examine behavioral factors influencing mobile banking services' (MBS) adoption in China. Despite the abundance of smart mobile phones, the uptake of mobile banking among the population remains low. To address this issue, this study integrates four variables--perceived financial cost, awareness, technology infrastructure support, and government regulations--into the UTAUT framework to explore their impact on driving the adoption of MBS. Based on convenient sampling techniques, it uses 567 valid responses collected through a self-administered questionnaire and applies multiple regression analysis methods for data analysis using SPSS-26 software. Results indicate that performance expectancy, effort expectancy, perceived financial cost, and awareness are significant drivers of behavioral intention to use MBS in China. Technological infrastructure support positively influences performance expectancy, and individuals' intent to use and adopt MBS in China. Government support significantly drives the individual's behavioral intention to use and adopt MBS. Furthermore, behavioral intention to use MBS significantly predicts its adoption in China. The practical and academic ramifications of MBS on the growth and development of sustainable mobile banking systems are presented. [ABSTRACT FROM AUTHOR]

This work aims to investigate the cultural and psychological factors that significantly affect teachers' intention to accept VR technology and use it long-term in their classes in elementary and secondary schools. The extended unified theory of acceptance and use of technology (UTAUT2) model effectively measured such factors in this context. We conducted a questionnaire survey with 351 elementary and secondary school teachers in four provinces in China and analyzed their responses utilizing Partial Least Squares (PLS) technique. The results of this work showed that performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation significantly impacted continued usage intention. However, the habit did not promote continued usage intention. Based on the results, research on VR classroom application guidance and teachers' professional development with VR technology applications should be strengthened. Meanwhile, increasing the publicity of integrating VR technology into classroom teaching, creating a favorable climate for VR technology adoption, and enhancing the fun of VR technology can also contribute to teachers' continued VR technology usage intention in classroom teaching. [ABSTRACT FROM AUTHOR]

Because healthcare systems in developing nations are underfunded and unequal, practitioners must understand how telemedicine may be widely introduced and sustained. Unfortunately, telemedicine adoption receives less attention and there is limited knowledge regarding the interfering influence of patient engagement, satisfaction, and individual innovativeness. Consequentially, the current study seeks to investigate the factors that influence patients' behavioral intentions toward telemedicine, while acknowledging engagement and satisfaction as mediators and personal innovativeness as a moderator. A questionnaire instrument was used to reach telemedicine users in Bangladesh, and finally, 305 samples were curated and explored applying structural equation modeling in AMOS software. The empirical results show that information quality, performance expectancy, engagement, and satisfaction are strong stimulators of behavioral intention toward telemedicine, whereas functionality, information quality, and performance expectancy drive satisfaction and engagement. One of the worthy findings of this study is that engagement and satisfaction play a significant mediating function, while personal innovativeness plays a moderating role, in influencing behavioral intention toward telemedicine. Confirming engagement and satisfaction as mediators and innovativeness as a moderator adds originality to this research, and overall will help to reduce healthcare bias prejudice among marginalized people in developing countries like Bangladesh. [ABSTRACT FROM AUTHOR]

This study examines the factors influencing Vietnamese journalists' adoption of Artificial Intelligence in journalism. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, it hypothesizes that performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, regulatory support, and technology affinity and incorporating additional trust, regulatory support, and technology affinity have significant impacts on journalists' adoption of technology. Questionnaires were administered to 238 journalists in the context of the Vietnamese press. The findings showed the significant impact of performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, regulatory support, and technology affinity on journalists' adoption of AI in journalism. These results expand the UTAUT framework and offer a more comprehensive understanding of technology adoption in journalism. Practically, the study provides valuable insights for practitioners and policymakers in the journalism industry. Understanding the determinants of journalists' adoption can inform the development of targeted interventions, training programs, and regulatory frameworks to facilitate the integration of AI technologies into journalistic practices. However, the study has limitations, and future research should replicate the findings in diverse cultural and organizational contexts while considering additional moderating factors. [ABSTRACT FROM AUTHOR]

The use of technology to provide contextual information for decision-making has been a long-standing practice. The study aims to identify the antecedents influencing tourists' use of context-aware applications. It employs the Unified Model of Electronic Government Adoption (UMEGA) and the Expectation Confirmation Model (ECM) to investigate tourists' behaviors in the use of Personal Locator Beacons (PLBs) during the pre-adoption and post-adoption stages at the Mole National Park in Ghana. Data was analyzed using Smart PLS 3.0 software. The findings suggest that pre-adoption performance expectancy, motivational needs, and personal situation significantly affect tourists' pre-adoption intentions to continue using context-aware applications. In addition, information recommendation, service quality, confirmation expectation, and satisfaction influenced continued use and recommendation. However, social influence and enjoyment experience did not significantly impact tourists' behavioral intentions. The findings contribute to theory by integrating components of the two models (UMEGA & ECM) and delving into the antecedents of users' decision-making processes. [ABSTRACT FROM AUTHOR]

Chatbots are increasingly applied in various contexts including helping professions, such as organizational and life coaching. Coaching facilitates individual wellness, behavioral change, and goal attainment in a reflective, non-directive manner, and is considered one of the fastest-growing professions. The use of knowledge imparting service chatbots have been studied; however, the application of chatbots in coaching has received scant research attention, raising the question about which factors and moderating effects play a role in the adoption of reflective, non-directive coaching chatbots. In this study, we applied a modified Unified Theory of the Acceptance and Use of Technology (UTAUT) model to determine factors and moderating effects of age and gender that influence the adoption of a goal-attainment coaching chatbot. Partial least squares structural equation modeling (PLS-SEM) was used for the analysis of a cross-sectional UTAUT survey (n = 226). Performance expectancy, social influence, and facilitating conditions had significant roles as direct determinants of intent to use the coaching chatbot. Gender moderated performance expectancy and age showed a moderation tendency on effort expectancy. This study on non-directive, reflective chatbots in the organizational, and life coaching domains contributes to our understanding of how to design chatbots aimed at helping people find their own answers. [ABSTRACT FROM AUTHOR]

With the e-Government, the state-stakeholder relationship has gained a different dimension. This opened the door for public services that are participatory, affordable, transparent, efficient, quick, and flexible. The factors that affect the adoption and utilization of e-Government projects, which are implemented at significant expense, must be identified. Differences in acceptance and use of e-Government projects depend on country factors. Thus, this study aims to determine the factors affecting the acceptance and use of the Northern Cyprus E-Government Project by survey method. The study has a distinctive quality because there hasn't been a thorough investigation in this area in Northern Cyprus. In addition, the data obtained at the end of the study will contribute to the literature on e-government applications and use in developing countries. The study was based on UTAUT and LISREL and SPSS package programs were used for data analysis. Structural equation models were used to analyze the findings in the study. The findings showed that every component had a positive impact on the participants' intention to utilize. The major factors were found to be performance expectancy, effort expectancy, and trust in the Internet. Plain Language Summary: With the e-Government, the state-stakeholder relationship has gained a different dimension. This opened the door for public services that are participatory, affordable, transparent, efficient, quick, and flexible. The factors that affect the adoption and utilization of e-Government projects, which are implemented at significant expense, must be identified. Differences in acceptance and use of e-Government projects depend on country factors. Thus, this study aims to determine the factors affecting the acceptance and use of the Northern Cyprus E-Government Project by survey method. The study has a distinctive quality because there hasn't been a thorough investigation in this area in Northern Cyprus. In addition, the data obtained at the end of the study will contribute to the literature on e-government applications and use in developing countries. The study was based on UTAUT and LISREL and SPSS package programs were used for data analysis. Structural equation models were used to analyze the findings in the study. The findings showed that every component had a positive impact on the participants' intention to utilize. The major factors were found to be performance expectancy, effort expectancy, and trust in the Internet. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the behavioral intention to adopt blockchain technology (BC) in Pakistan's operation and supply chain management. A conceptual framework is developed by extending the unified theory of acceptance and use of technology (UTAUT) model, incorporating technology readiness, technology affinity, and trust. The model was empirically examined using 198 responses from an online survey directed by a Pakistan operation and supply chain professionals. The proposed model is tested using Smart PLS. The empirical results suggest that BC adoption is positively influenced by facilitating condition, social influence, effort expectancy, technology readiness, and technology affinity, while performance expectancy and trust negatively influence BC to adopt. This research contributes to the advancement and stimulation of blockchain technology acceptance behavior in supply chains and significant managerial implications that could be more meaningful for developing economies. [ABSTRACT FROM AUTHOR]

Followed by the fast developments in Internet of Things (IoT), artificial intelligence (AI) technologies, utilizing cloud architecture and big data, have been integrated into various aspects of our daily lives. Such an integration results in high levels of convenience, comfort, and energy savings. Deploying such new technologies benefits the elevator industry as well. Intelligent elevator with energy control schemes can improve the energy efficiency of eco-friendly applications. The purpose of this study is to examine the factors that affect the intelligent elevator adoption of Taiwanese people using the extended unified theory of acceptance and use of technology (UTAUT 2) model, which considers factors such as environmental consciousness, artificial intelligence optimism, attitude, and perceived quality. A well-structured face-to-face survey is performed to obtain data from the consumers living in central Taiwan. The data acquired are analyzed via structural equation modeling using the partial least squares method. The analysis results indicate that attitude, habit, performance expectancy, effort expectancy, and perceived quality are important factors that affect the behavioral intentions of consumers when adopting new technologies, such as an intelligent elevator. However, facilitating conditions adversely affect the behavioral intentions. In addition, environmental consciousness and artificial intelligence optimism are crucial factors that affect performance and effort expectancies, whereas the latter two contribute positively to attitude. The findings of this study supplement existing literature regarding the behavioral intentions for adopting intelligent elevators. Finally, the theoretical and practical significances of this research study are discussed. [ABSTRACT FROM AUTHOR]

This systematic review evaluates the application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in higher education, analyzing 162 SSCI/SCI-E articles from 2008 to 2022. It reveals a predominant focus on student participants from Asia and North America. Mobile learning tools are the most studied technologies. Surveys continue to be the top data gathering method, while structural equation modeling is preferred for analysis. The Technology Acceptance Model is combined most with UTAUT. UTAUT testing shows performance expectancy has the strongest sway on behavioral intention. Additionally, the review underscores nuanced variances in the impact of UTAUT factors between higher education and general contexts. The study calls for future UTAUTapplications must promote inclusive research spanning diverse groups, mixed methodologies and theoretical perspectives. This comprehensive approach is imperative to fully understand technology adoption patterns in higher education and enable context-specific integration strategies. [ABSTRACT FROM AUTHOR]

Blockchain and cryptocurrencies are transformative fintech breakthroughs that infiltrate the financial sector; however, they have many drawbacks and limits. Consumers have shown an insufficient level of acceptance of these innovations. This paper elucidates the main reasons for the effective growth of a cryptocurrency from user behavior. The objective is to determine what factors influence consumers' intentions to engage in blockchain-based cryptocurrency dealings. Considering the complexity of emerging technologies, this paper applied an integration model which assumes various external elements such as financial literacy, performance expectancy, facilitating conditions, effort expectancy, awareness, trust, design, and social influence. Smart PLS3 has been used. The most critical determinant of a cryptocurrency's growth is "design." On the other hand, "design" affects effort expectancy positively, and social influence affects trust. Awareness, performance expectancy, financial literacy, and effort expectancy significantly affect intentions to use cryptocurrency. It's worth mentioning that it is the first research to examine Pakistani customers' perceptions of Bitcoin and their ability to partake. As a result, it is intended to serve as a base for potential research in this area. [ABSTRACT FROM AUTHOR]

To explore the influencing factors of college students' learning intention to online teaching videos during the pandemic, this study considered 696 college students from Huangshan University in China. The T-test and ANOVA were utilized to analyze gender, grade, and discipline on college students' learning intention, and the regression analysis was utilized to explore four aspects including performance expectancy, effort expectancy, social influence, and facilitating conditions on college students' learning intention. The results indicate the following: first, using descriptive analysis, it is observed that college students did not exhibit a positive learning attitude toward online teaching videos during the pandemic. Second, the t test and one-way analysis of variance indicate that grades between freshmen and seniors significantly influence the learning intention of college students to online teaching videos, whereas genders and disciplines do not. Third, through regression analysis, it is observed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence college students' learning intention to online teaching videos. This study stipulates the following research proposals: resource construction, the optimization of the online teaching environment, advanced technology and psychological counseling. It is expected that the findings will provide references for studies on online teaching resources and online learning.

This study investigated the factors determining the behavioral intention of young Saudi entrepreneurs to use crowdfunding to finance their small enterprises. The capacity of behavioral intention to predict the use behavior of crowdfunding platforms was also assessed. Partial least squares-based structural equation modeling method (PLS-SEM) was used to analyze responses collected from 270 young Saudi entrepreneurs (qualified students) attending the Community College of Abqaiq in Saudi Arabia, which is affiliated with King Faisal University. The unified theory of acceptance and use of technology (UTAUT) with extensions of three constructs was employed. The findings revealed that performance expectancy, social influence, perceived trust and perceived risks predicted the behavioral intention of young Saudi entrepreneurs to use crowdfunding platforms to finance their small enterprises, whereas effort expectancy, facilitating conditions and trialability had no significant predictive effect on the same behavioral intention. It was further reported that behavioral intention could also predict the use behavior of young Saudi entrepreneurs on crowdfunding platforms. The overall results indicated that the model explained 55.4% of the variance in behavioral intention and 38.3% of the variance in use behavior of young Saudi entrepreneurs. [ABSTRACT FROM AUTHOR]

Academic self-efficacy is identified as one of the strongest predictors of students' academic performance. However, few studies have explored the factors that influence students' academic self-efficacy in a blended learning environment. By developing a comprehensive model, this study investigates the main factors that influence students' academic self-efficacy in blended learning from the personal, interpersonal, and environmental perspectives. The relevant information was acquired through a questionnaire survey. The participants included 366 college students at a university in central China. Hierarchical regression analysis shows that intrinsic motivation, extrinsic motivation, instructor support, performance expectancy, and facilitating conditions are significant predictors of students' academic self-efficacy in blended learning. The findings expand the understanding of students' academic self-efficacy in technology-enhanced learning environments and provide valuable insights that could help to improve the appropriateness of instructional design in blended learning courses. [ABSTRACT FROM AUTHOR]

E-learning platform (ELP) provides economic and efficient channels to share and learn knowledge online without time and location restrictions. Earlier studies have identified determinants that impact students’ intention to use new technologies in different learning contexts, yet few have tried to investigate the effect of students’ satisfaction of basic psychological needs during the adoption process. Based on the framework of UTAUT2, this study has tested the mediating role of satisfaction of basic psychological needs to better comprehend the relationships between the antecedents and intention. The partial least square structural equation modeling was used for data analysis, findings indicate that performance expectancy, learning value, hedonic motivation, and habit significantly impact students’ willingness to adopt ELP for college English study. As for the mediating effect of students’ satisfaction of basic psychological needs, it fully mediates the relationship between effort expectancy, facilitating conditions, and intention while partially mediating the relationship between performance expectancy, learning value, hedonic motivation, habit, and intention. The study aids in grasping the key factors to increase students’ adoption of ELP and offers recommendations to increase students’ participation, learning efficiency, and their satisfaction of basic psychological needs for competence, autonomy, and relatedness during college English study with ELP.

This study uses a modified UTAUT model to examine behavioral factors influencing mobile banking services’ (MBS) adoption in China. Despite the abundance of smart mobile phones, the uptake of mobile banking among the population remains low. To address this issue, this study integrates four variables—perceived financial cost, awareness, technology infrastructure support, and government regulations—into the UTAUT framework to explore their impact on driving the adoption of MBS. Based on convenient sampling techniques, it uses 567 valid responses collected through a self-administered questionnaire and applies multiple regression analysis methods for data analysis using SPSS-26 software. Results indicate that performance expectancy, effort expectancy, perceived financial cost, and awareness are significant drivers of behavioral intention to use MBS in China. Technological infrastructure support positively influences performance expectancy, and individuals’ intent to use and adopt MBS in China. Government support significantly drives the individual’s behavioral intention to use and adopt MBS. Furthermore, behavioral intention to use MBS significantly predicts its adoption in China. The practical and academic ramifications of MBS on the growth and development of sustainable mobile banking systems are presented.

Research has been limited on what factors may make customers feel uncomfortable with using electronic payment systems. The purpose of this research study was to develop a model that analyzed the dimensions of the unifiB01;ed theory of acceptance and use of technology (UTAUT) with extra structures to understand how gender can affect whether consumers decide to embrace cashless payment systems in Thailand. Accordingly, 416 valid answers were submitted by banking customers utilizing the survey instrument. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed to kick off the process of creating a measurement model. Structural equation modeling (SEM) was then used to pinpoint the most pressing factors that prevent people from embracing online banking systems. The purpose of this research was to develop a technology acceptance model with extra structures to understand how attitudes and perceived risks affect people's decision-making process as to whether they embrace cashless payment systems in Thailand (i.e., innovativeness). In the second stage, we used a neural network model to rank the importance of various SEM-derived predictions. The results demonstrate a robust association between Internet banking and the value barrier, the risk barrier, and the image barrier. The only factor that indicated any kind of negative influence on whether people chose to use Internet banking was the conventional barrier. Remarkably, the image barrier affected Internet banking adoption more than the risk barrier or the no-frills alternative. Furthermore, according to the data, men experienced greater challenges than women. The findings of this study may help financial institutions create offerings that entice customers to conduct financial dealings with them online. The banking industry could immensely benefit from this research since it may lead to changes in the laws that govern banking and could ultimately enhance customer service and online services. Plain Language Summary: The purpose of this research was to develop a model that would examine a study that used the technology acceptance model with extra structures to understand how attitudes and perceived risk affect people's decisions to embrace cashless payment systems in Thailand (i.e., innovativeness). There were 416 valid answers collected from bank customers utilizing the survey instrument. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed to kick off the process of creating a measurement model. Then, structural equation modeling (SEM) was used to pinpoint the most pressing factors preventing people from adopting online banking of this research was to develop a model that would examine a study that used the technology acceptance model with extra structures to understand how attitudes and perceived risk affect people's decisions to embrace cashless payment systems in Thailand (i.e., innovativeness). There were 416 valid answers collected from bank customers utilizing the survey instrument. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed to kick off the process of creating a measurement model. Then, structural equation modeling (SEM) was used to pinpoint the most pressing factors preventing people from adopting online banking. In the second stage, we used the neural network model to rank the importance of various SEM derived predictions. The results demonstrate a robust association between Internet banking and the value barrier, the risk barrier, and the image barrier. [ABSTRACT FROM AUTHOR]

Mobile technology has become increasingly common in recent years with its booming development across the globe, leading to the gradual adoption of mobile health, which can reduce the risk of caregivers being infected. The widespread use of mobile health has brought many benefits to the healthcare industry, including increased efficiency for frontline caregivers and a better patient–physician relationship. However, it also presents some challenges. This study aimed to examine caregivers’ behavior intention to use mobile technology in medical practice with a unified theory of acceptance and the use of technology two model. Satisfaction and self-efficacy were included as external variables and mobile technology identity as a moderator variable. A total of 281 valid questionnaires were collected from the nursing staff, and a structural equation model was used to test the hypotheses of this study. The results of the study showed that (1) self-efficacy had a significant effect on satisfaction and effort expectancy, (2) effort expectancy significantly affected performance expectancy, (3) performance expectancy and satisfaction had significant effects on behavior intention, and (4) mobile technology identity moderated the relationship between satisfaction and behavior intention. These results could inform medical institutions and facilities in launching mobile technology policies and education or training programs.

Because healthcare systems in developing nations are underfunded and unequal, practitioners must understand how telemedicine may be widely introduced and sustained. Unfortunately, telemedicine adoption receives less attention and there is limited knowledge regarding the interfering influence of patient engagement, satisfaction, and individual innovativeness. Consequentially, the current study seeks to investigate the factors that influence patients’ behavioral intentions toward telemedicine, while acknowledging engagement and satisfaction as mediators and personal innovativeness as a moderator. A questionnaire instrument was used to reach telemedicine users in Bangladesh, and finally, 305 samples were curated and explored applying structural equation modeling in AMOS software. The empirical results show that information quality, performance expectancy, engagement, and satisfaction are strong stimulators of behavioral intention toward telemedicine, whereas functionality, information quality, and performance expectancy drive satisfaction and engagement. One of the worthy findings of this study is that engagement and satisfaction play a significant mediating function, while personal innovativeness plays a moderating role, in influencing behavioral intention toward telemedicine. Confirming engagement and satisfaction as mediators and innovativeness as a moderator adds originality to this research, and overall will help to reduce healthcare bias prejudice among marginalized people in developing countries like Bangladesh.

Blockchain and cryptocurrencies are transformative fintech breakthroughs that infiltrate the financial sector; however, they have many drawbacks and limits. Consumers have shown an insufficient level of acceptance of these innovations. This paper elucidates the main reasons for the effective growth of a cryptocurrency from user behavior. The objective is to determine what factors influence consumers’ intentions to engage in blockchain-based cryptocurrency dealings. Considering the complexity of emerging technologies, this paper applied an integration model which assumes various external elements such as financial literacy, performance expectancy, facilitating conditions, effort expectancy, awareness, trust, design, and social influence. Smart PLS3 has been used. The most critical determinant of a cryptocurrency’s growth is “design.” On the other hand, “design” affects effort expectancy positively, and social influence affects trust. Awareness, performance expectancy, financial literacy, and effort expectancy significantly affect intentions to use cryptocurrency. It’s worth mentioning that it is the first research to examine Pakistani customers’ perceptions of Bitcoin and their ability to partake. As a result, it is intended to serve as a base for potential research in this area.

The COVID-19 pandemic has significantly impacted global society and economies, prompting a shift in online consumer purchasing behavior (OCPB). This study aims to explore the evolving typologies of OCPB in the context of post-pandemic retail transformations. Utilizing data from a leading Chinese e-commerce platform, this study employed data mining techniques and the Bidirectional Encoder Representations from Transformers (BERT) model to analyze OCPB typologies. The BERT model, known for its advanced multi-task capabilities, demonstrated high reliability in classifying OCPB into three distinct types, as evidenced by robust performance metrics including accuracy, precision, recall, and F1-score. However, the BERT model alone did not fully capture the nuanced concept of OCPB typology. To address this, this study integrated grounded theory to further delineate OCPB typologies, identifying key dimensions such as social and economic adaptation, product attributes, and user experience. Our findings offer a comprehensive understanding of OCPB typologies and provide valuable insights for retailers navigating the post-COVID-19 landscape. This research not only contributes to the academic discourse on consumer behavior but also offers practical guidance for enhancing retail strategies in a rapidly changing environment. Plain language summary: Online consumer purchasing behavior typology The COVID-19 pandemic has changed the way people shop online. This study looks at how online shopping habits have evolved since the pandemic started, focusing on different types of shopping behaviors. We used information from a big online shopping site in China and special computer programs to study these behaviors. Our research found three main types of online shopping behaviors. However, to get a deeper understanding, we also looked at why people shop the way they do, considering factors like how they adapt socially and economically, what they think about the products, and their shopping experience. Our findings help us better understand online shopping habits and offer advice to stores on how to improve their online selling strategies in the new normal after the pandemic. This study is useful for both researchers interested in consumer behavior and for businesses looking to adapt to changes in how people shop. [ABSTRACT FROM AUTHOR]

Chatbots are increasingly applied in various contexts including helping professions, such as organizational and life coaching. Coaching facilitates individual wellness, behavioral change, and goal attainment in a reflective, non-directive manner, and is considered one of the fastest-growing professions. The use of knowledge imparting service chatbots have been studied; however, the application of chatbots in coaching has received scant research attention, raising the question about which factors and moderating effects play a role in the adoption of reflective, non-directive coaching chatbots. In this study, we applied a modified Unified Theory of the Acceptance and Use of Technology (UTAUT) model to determine factors and moderating effects of age and gender that influence the adoption of a goal-attainment coaching chatbot. Partial least squares structural equation modeling (PLS-SEM) was used for the analysis of a cross-sectional UTAUT survey ( n = 226). Performance expectancy, social influence, and facilitating conditions had significant roles as direct determinants of intent to use the coaching chatbot. Gender moderated performance expectancy and age showed a moderation tendency on effort expectancy. This study on non-directive, reflective chatbots in the organizational, and life coaching domains contributes to our understanding of how to design chatbots aimed at helping people find their own answers.

Artificial Intelligence (AI) tools are having a significant impact on the field of education, particularly when used by educators. This study aims to explore the acceptance of AI tools among university-level educators. Researchers adapted the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model to the Chinese educational context and surveyed 402 university educators. The findings revealed several predictors related to educators’ behavioral intention to use AI tools in teaching including performance expectancy, effort expectancy (which emerged as the strongest predictor), and hedonic motivation. Additionally, the study showed that the predictors of actual AI tool usage are facilitating conditions, habit (identified as the strongest predictor), and behavioral intention. Notably, the study found that gender, age, and experience did not have a moderating effect. This study contributes to the existing body of evidence on AI tool acceptance among university educators and holds implications for their training and professional development.

With the rapid development of e-commerce, Online shopping has not only brought convenience to people’s lives, but also accelerated the explosion of express delivery. As a device that provides 24-hr self-service pickup and delivery services, smart lockers are increasingly accepted by more and more express delivery companies and consumers. However, in rural China, there are few outlets and low usage rates for express delivery cabinets. Especially for the elderly, the use and acceptance of smart lockers are significantly lower. Therefore, how to improve the usage intention of intelligent express delivery cabinets has become a problem that needs to be solved in the development process of smart rural areas. This study develops a theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT), and conducts empirical testing to determine the key factors affecting the willingness of rural Chinese consumers to use smart lockers. This study used a questionnaire survey method to collect data, and a total of 240 valid questionnaires were collected. The partial least squares (PLS) method was used to measure and test the research hypotheses. The results indicate that performance expectancy, facilitating conditions, price value and technology anxiety have a positive impact on consumers’ intention to use. There is no significant relationship between effort expectancy and social influence and users’ behavioral intention to use smart lockers. The results of this study will help enrich UTAUT, provide valuable information for enterprises, and contribute to the implementation of smart villages strategies.

This study developed and empirically tested a model to predict the factors affecting patients’ behavioral intentions to use a mobile health education website. It explored the behavioral intention to use a mobile health education website from the perspective of consumers by extending the Unified Theory of Acceptance and Use of Technology 2 model with the addition of mobile self-efficacy (M-SE), use motivation, and mobile literacy as moderators. For this purpose, variance-based structural equation modeling was used to analyze data collected from a sample of 1,649 patients at a hospital in Taoyuan, Taiwan. Partial least squares regression was used for model and hypothesis testing. The results revealed that (1) performance expectancy, effort expectancy, social influence, facilitating conditions, and habit were key predictors of the behavioral intentions of patients to use a mobile health education website; (2) M-SE had positive associations with effort expectancy; (3) use motivation was a significant determinant of both performance expectancy and effort expectancy; and (4) mobile literacy had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings serve as a reference for the promotion of mobile health education in hospitals.

This study investigated students' flow states and attitudinal beliefs in a social media-mediated e-commerce entrepreneurship education (EE) context that mediates the entrepreneurial intention-behavior relationship by a structural equation model using the theory of planned behavior (TPB) and the flow theory. This study collected questionnaire data from students to examine the conceptual model. Such learning environments enhanced students' perceived behavioral control, increased their flow experience, improved attitudes toward social media-assisted entrepreneurial learning, and facilitated the intentions, which led to learning behavior performance achievement in a digital economy. Notably, the flow and attitudes constructs mediated the linkage between students' perceived entrepreneurial feasibility and the intention-behavior relationship in the social media-assisting EE context. This study contributed to theory by emphasizing the importance of digital entrepreneurial learning in facilitating prospective entrepreneurs' TPB cognitions, by identifying the mediation effects of learners' flow and attitudes on the intention-behavior relationship, and by adding the flow concept into the TPB to understand the mechanism through which EE influences students' exploratory behavior. The findings highlighted EE practices in computer-mediated environments that facilitate students' active and meaningful learning for flow experience and attitude enhancement, which likely increases their entrepreneurial intentions and behavior in a digital business environment. [ABSTRACT FROM AUTHOR]

This study aims to analyze the research performance of 38 OECD countries in the last 10 years. For this purpose, the research performance of these countries was analyzed using multi-criteria decision-making (MCDM) methods with the productivity and publication impact data of 38 countries. The analyses were conducted both normal data and also with adjusted data based on the population and income level of the countries. Firstly, the importance level of research performance criteria was determined by three different MCDM methods. Using the weight values obtained from these methods, countries were ranked by three different MCDM methods used for ranking purposes. According to the results of the study, the publications in the highest cited 1% were determined as the most important and distinctive criterion. Secondly, the criterion expressing the relative impact of publications on the world was determined as the second most important criterion. In the analyses conducted without normalizing the data, USA showed the highest research performance. In the analyses conducted by considering the population of the countries, Switzerland showed the highest research performance. In the analyses conducted by taking into account the income level of the countries, Estonia has the highest research performance. As R&D expenditures, development level of countries and international collaboration increased, research performance of countries increased. However, with the increase in domestic collaboration, there has been a decrease in research performance. In addition, this research has shown how to use MCDM in the measurement of research performance by using objective methods with different backgrounds. [ABSTRACT FROM AUTHOR]

With the rise of "Internet + Education," blended learning has become a new trend in higher education. This study aims to explore how behavioral willingness and self-efficacy affect the learning effect of college students in this new learning mode. The Unified Theory of Acceptance and Use of Technology (UTAUT2) was used to construct a theoretical model, and data on the blended learning effectiveness of 167 college students from a university in Southwest China were collected through questionnaires, and the theoretical assumptions and model were verified using Structural Equation Modeling (SEM) in Smart PLS software. It was found that in blended learning, performance expectation, effort expectation, hedonic motivation and facilitation all significantly and positively affect college students' behavioral intention of blended learning, which in turn positively affects the effect of blended learning, among which hedonic motivation is a more important influencing factor in the behavioral intention of blended learning. Self-efficacy also has a significant positive effect on blended learning effects. Finally, the study proposes countermeasures for teaching improvement from three aspects: teachers' teaching design, students' motivation and behavior, and optimization of e-learning platform content and function. [ABSTRACT FROM AUTHOR]

The study aims to examine the degree of Sustainable Digital Financial Inclusion (SDFI) of women workforce of Banking sector and IT sector. Banking sector imparts the knowledge of Digital Banking (DB), and IT sector develops DB applications. This research is motivated by the void left by previous researchers in understanding the determinants of Digital Banking Adoption Intention (DBAI) by female employees; as their digital inclusivity influences the DFI of common women. The study uses UTAUT2 model and PLS-SEM was applied on the 257 responses collected through structured questionnaires. Results show that female bankers have higher SDFI as compared to female ITemployees due to mediation of DBAI between Drivers influencing DB and SDFI. The study contributes by clubbing the technological and financial sector. The study suggests the higher management of Banks and IT firms for recruitment and training of women personnel in DB adoption and DB application development, respectively. [ABSTRACT FROM AUTHOR]

Mobile shopping (m-shopping) adoption has been significantly touted in the contemporary era; however, the adoption of m-shopping is still under shadow in many developing countries. The aim of this study is to discover the impact of device system quality on m-shopping adoption among university students with the support of UTAUTand UTAUT2 theories. The study employed PLS-SEM (symmetric) and fsQCA (asymmetric) analysis simultaneously using survey data from 530 respondents who are primarily university students. PLS-SEM results found positive significant relation between device system quality and m-shopping adoption. The study contributes with an extention of earlier studies that combine PLS-SEM (symmetric methods) and fsQCA (asymmetric methods). The study is limited among the university students that may affect the generalizability of the study. The casual recipes in this research aid policymakers to achieve their strategic objectives in implementing positive m-shopping behavior among the university students. [ABSTRACT FROM AUTHOR]

This study explores the adoption of cryptocurrency, specifically Bitcoin, in the Philippines. The authors argue that current behavioral prediction models, such as TRA, TPB, and TAM, do not adequately account for the affective constructs of decision-making when high monetary stakes are involved. To address this gap, the authors propose an integrative model that accounts for financial decision-making processes, risk constructs, and population-specific behavioral strategies. The study used a quantitative-based research design and involved 684 university students from one of the major state universities in the Philippines. The findings show that perceived usefulness, attitude toward cryptocurrency, self-efficacy, and descriptive norms significantly influenced the intention to adopt cryptocurrency. Overall, the study confirms the direct influence of instrumental attitude, knowledge of cryptocurrency, descriptive norm, risk tolerance, ease and difficulty, and control on an individual's intention to use cryptocurrency. The study contributes to exploring a less studied Philippine consumer base and provides empirical findings and insights into Bitcoin adoption in developing Asian economies. [ABSTRACT FROM AUTHOR]

Technology brings tremendous changes in education because it is a system that automates all educational institutions and academic performance. Therefore, the study examines the effect of technology's system, information and service quality on faculty, operational and university performance. To explore the more contextual factors, this study empirically and theoretically tested a proposed model by the D&M theory of IS among UAE universities. The study employed mixed-method research using a sequential explanatory research design. Using a designed survey questionnaire, the study targeted 512 faculty members and conducted 10 semi-structured face-to-face interviews with faculty members of 27 UAE universities. The results reported that system, information, and service quality significantly influenced faculty performance. In addition, system quality strongly affects faculty performance, which is the most necessary part of successful technology implementation. Faculty performance significantly influences operational and university performance; surprisingly, it has the strongest influence on operational performance. In turn, operating performance has a significant impact on university performance. The study further identified four contextual factors, that is, external, individual, organizational, and technical. The study put the novel ideas by contributing performance-level measures that support Delone and Mclean's IS success model to successfully operationalize the university's actual performance. The research uniquely extends the D&M IS success model to assess technology implementation success at individual, operational, and organizational levels within UAE universities, touching previously unexplored areas of post-implementation evaluation. University management in the UAE should prioritize enhancing service, system, and information quality to bolster faculty performance, leading to improved operational and overall organizational outcomes. [ABSTRACT FROM AUTHOR]

Despite the booming market of fresh food, the fresh e-commerce platform holds only a limited market share, owing to the lack of habitual usage of these platforms. This article explores the determinants of purchase intention when using a fresh e-commerce platform. The integrated technology acceptance model (Unified Theory of Acceptance and Use of Technology [UTAUT]) is employed as the framework. A questionnaire survey was conducted and is analyzed using the structural equation model. We find that both performance expectancy and social influence have a significantly positive effect on consumers’ purchase intention using fresh e-commerce platforms, while perceived risk has a significantly negative effect. Perceived trust plays a mediating role between performance expectancy and purchase intention, social influence and purchase intention, as well as perceived risk and purchase intention. In addition, food safety awareness is a moderator between perceived trust and purchase intention.

This study tries to propose a unified model integrating the unified theory of acceptance and use of technology (UTAUT) model, task–technology fit (TTF) model, and user satisfaction to investigate the determinants that affect university students’ continued intention of using massive open online courses (MOOCs). Based on the data of a survey on 464 respondents, structural equation modeling is adopted to assess the model. The results reveal that performance expectancy, effort expectancy, social influence, and user satisfaction are the crucial predictors of university students’ continued intention. TTF has an indirect influence on continued intention through user satisfaction. Performance expectancy is affected both by effort expectancy and TTF. Facilitating conditions do not directly influence continued intention; however, they present indirect influences in that they play a mediating role for user satisfaction. The findings help researchers and practitioners to attain a better understanding of university students’ continued usage intention of MOOCs. The implications and limitations of this study are also described.

Motivation and anxiety are two crucial factors influencing learning outcomes, yet limited empirical research on expectancyvalue theory can be found within previous literature about Chinese undergraduate students studying English as a foreign language (EFL). Moreover, few studies have examined the interaction between motivation and skill-specific anxiety. Thus, the present study explored dimensions of task values of English learning, the relationship between expectancy, values and English language speaking anxiety (ELSA) among Chinese undergraduate EFL learners and their predictive power on spoken English proficiency. Two hundred twenty-three Chinese undergraduates completed a questionnaire about their spoken English proficiency, expectancy-value and ELSA items. The following results came to light: (1) task values in English learning had four facets; (2) different types of value were significantly positively correlated with each other, both expectancy and ELSA were significantly linked to cost value, and expectancy bore a significantly negative correlation with ELSA; (3) expectancy, ELSA and attainment and cost value separately predicted learning achievement, whereas only expectancy and value additively predicted learning achievement, where expectancy exerted a greater impact. These findings suggest that teachers should guide students to aim high and provide more opportunities for spoken English practice. [ABSTRACT FROM AUTHOR]

The fundamental of prioritizing employees' career satisfaction is an essential agenda of an organization. Referring to the concept of career satisfaction in Malaysia, employees who are satisfied with their careers can influence organizational success and contribute to effective organizational performance. Thus, considering the aim of the present research, this study examines the mediation effect of psychological empowerment on the relationship between perceived organizational support and career satisfaction among operators at one manufacturing company in Johor. A cross-sectional survey was conducted by distributing questionnaires to 248 respondents, with only 202 returned. Later, the collected feedback was loaded into SPSS software for descriptive statistical analysis. Next, SmartPLS software was utilized to evaluate the inferential statistic to test the projected hypotheses. The result indicated that psychological empowerment could mediate the relationship between perceived organizational support on career satisfaction. Several recommendations were enclosed to the respective organization and future researchers to cater to the studied problems. [ABSTRACT FROM AUTHOR]

The use of technology to provide contextual information for decision-making has been a long-standing practice. The study aims to identify the antecedents influencing tourists’ use of context-aware applications. It employs the Unified Model of Electronic Government Adoption (UMEGA) and the Expectation Confirmation Model (ECM) to investigate tourists’ behaviors in the use of Personal Locator Beacons (PLBs) during the pre-adoption and post-adoption stages at the Mole National Park in Ghana. Data was analyzed using Smart PLS 3.0 software. The findings suggest that pre-adoption performance expectancy, motivational needs, and personal situation significantly affect tourists’ pre-adoption intentions to continue using context-aware applications. In addition, information recommendation, service quality, confirmation expectation, and satisfaction influenced continued use and recommendation. However, social influence and enjoyment experience did not significantly impact tourists’ behavioral intentions. The findings contribute to theory by integrating components of the two models (UMEGA & ECM) and delving into the antecedents of users’ decision-making processes.

This research paper examined the continued intention of college students to use DiDi mobile car-sharing services in China. The unified theory of acceptance and use of technology (UTAUT) was used as the theoretical framework while the data analysis was completed with SPSS. The results have demonstrated that performance expectancy, reliability, efficiency, and security and privacy were significant predictors of the continued intention to use mobile car-sharing services. Contrary to our expectations, effort expectancy was not a significant determinant of the continued intention to use mobile car-sharing services. In addition to these direct effects, the moderating impact of trust in the internet was also examined. The moderating analysis showed that trust in the internet showed no significant moderating impact on the relationship between performance expectancy, effort expectancy, reliability, efficiency, and security and privacy and the continued intention to use mobile car-sharing services. The implications of these findings are discussed.