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The COVID-19 pandemic has highlighted the need for higher education institutions to modernize and embrace the post-digital age. This study evaluates students' perspectives of utilizing MS Teams as a means of facilitating remote learning during the pandemic. The Technology Acceptance Model (TAM) was employed as the theoretical framework to examine students' views on self-efficacy, facilitating conditions, ease of use, usefulness, and intention to use. The results showcase positive views of MS Teams, with self-efficacy rated the highest among the five constructs, followed by ease of use, facilitating conditions, intention to use, and usefulness. Additionally, no significant differences were found in students' perceptions based on gender. MS Teams has proven to be a successful platform for delivering online learning and communicating, bridging the divide of distance and time in teaching and learning. As discussions about the future of higher education in the post-pandemic world have commenced among academia and university officials, it is crucial to consider the impact of COVID-19 on student learning and provide suggestions for a more sustainable and effective post-pandemic education. © 2023 IEEE.
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Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges. Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia. Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square - Structural Equation Modeling (PLS-SEM). Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults' behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults' Behavioral Intention to Use Telemedicine. Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine. © 2023 The Authors. Published by Universitas Airlangga.
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COVID-19 pandemic, the foodservice industry has had to modify the way it offers its services. The aim of this paper is to examine the drivers of intention to use and recommendation of online food delivery (OFD) using the SOR model, to analyze the perceived risk of COVID-19 and its relationship with the perceived risk for online purchase of OFD as well as to analyze the cultural effect between Spain and India. For this purpose, an online questionnaire was developed by obtaining a sample of 422 users and structural equation modeling (PLS-SEM) was used to determine which variables had a significant influence on the adoption of the OFD. The results confirm that attitude is the main antecedent of intention to use and recommendation, in contrast to the subjective norm relationships, where it was only confirmed by recommendation. This finding demonstrates how individuals' attitude toward intention and recommendation is more favorable than influence of third parties on decisions. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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Digital health interventions have become an essential component of every public health system since the COVID-19 pandemic. 'eSanjeevani OPD - Stay at Home OPD' is a telemedicine system that connects doctors and patients launched as part of the Ayushman Bharat project of the Indian government. This study analyses various factors affecting the intention to use eSanjeevani. A theoretical model integrating the health belief model and the theory of reasoned action was framed and empirically tested. Responses were collected using a survey questionnaire(n=248). A partial least square-structural equation modeling was used to analyze the linkages between the constructs. Perceived susceptibility and benefits were found to be the most contributing variables. Attitude has a significant mediating effect on the intention to use eSanjeevani. © 2023 IEEE.
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Introduction: Information and communication technology (ICT) usage has grown rapidly, with a significant rise following the occurrence of the COVID-19 pandemic. This study assesses the relationships among task-technology fit, sense of virtual community, and the continuous intention to use electronic government services (e-government). Methods: Through quantitative approach using surveys, a total of 390 data was obtained from registered citizens in Tripoli municipality during the pandemic. The data were analyzed using partial least square-structural equation modeling (PLS-SEM). Results: The mediating role of the unified theory of acceptance and use of technology (UTAUT) model was observed, which shows that task-technology fit, sense of virtual community, and the consideration of society and its development are essential factors for citizens to use ICTs. Systems should entail features that meet the needs of citizens, community-building elements, and satisfactory performance. The importance of e-government ICTs in community development, particularly in a fragile state such as Tripoli, Lebanon, is the highlight of the current results. This can be beneficial for governmental authorities in the region of the Middle East, helping them to increase communication effectiveness by implementing appropriate digital means for the public during a crisis. Community development is a highly effective aspect that governments can implement in their digital services to provide opportunities for learning, awareness, and social progress to the public.
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In order to trace the transmission of COVID-19, digital contact tracing (DCT) provides an enormous value for the public health. However, the acceptance of the German contact tracing app, the Corona-Warn-App (CWA), falls short of the expected coverage in the general public. Accordingly, this study focuses on investigating the influencing factors on the CWA's acceptance to demystify the missing puzzle and to face future pandemics. To assess this objective comprehensively, we investigate personality traits (guiding perception and behavior), subjective norm (expressing social influence), and trust in technology on acceptance variables. Our empirical results emphasize that besides the personality traits conscientiousness and agreeableness, perceived usefulness, subjective norm, and trust in technology play a vital role for engagement with the CWA. Our research offers starting points for the use of mobile health solutions, particularly in early epidemic stages. © 2022 IEEE Computer Society. All rights reserved.
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Purpose: The aim of this paper is to determine the differences in students' attitudes related to online and traditional teaching, then to determine the level of student satisfaction with online teaching, factors affecting it as well as to examine the problems students most often face during online teaching. Design/methodology/approach: The survey method is used to collect primary data. In the empirical research participate 312 students on the territory of the Republic of Serbia who used e-learning during the Covid-19 pandemic. Descriptive statistical analysis, paired samples t-test, reliability analysis, confirmatory factor analysis and structural equations modeling are applied in the paper. Findings: Research has shown that students are generally more satisfied with traditional than online teaching. Then, the analysis shows that professors' activities and the quality of e-learning have ? Significant positive effects on student satisfaction with online teaching, as well as on student motivation, then perceived usefulness has a positive impact on motivation and intention to use e-learning and student motivation has statistically significant effects on satisfaction with online teaching. The biggest shortcomings of online teaching are: monotonous teaching, lack of interaction with professors, lack of interaction with other students as well as lack of socialization. Originality/value: Although a large number of studies have studied e-learning and student satisfaction, this paper has studied e-learning in the specific conditions of the Covid-19 pandemic. Of particular value to this paper is the comparison of student satisfaction with online teaching during the pandemic and student satisfaction with traditional teaching. © 2023, Emerald Publishing Limited.
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COVID-19 related lockdowns forced students of higher education to receive education entirely online as a replacement for physical attendance in classrooms. This new situation caused students to discover the advantages and disadvantages of e-learning and influenced their satisfaction in using it and intention to use it. Consequently, this study revisits the intention to use and satisfaction-related theories based on pre-COVID conditions. This revisit was necessary because the evidence suggests that students' new situation has changed some determinants related to their satisfaction and intention to use. This situation warranted the simultaneous consideration of many dimensions when measuring user satisfaction and intention to use during the lockdown. This cross-sectional study developed an integrated model to measure students' satisfaction and its impact on intention to use e-learning. Structural equation modeling was used to conduct the empirical analysis. Nine hundred respondents from Malaysia and Saudi Arabia participated in this study. Students from Malaysia and Saudi Arabia showed marginal differences in their perceptions of e-learning. The findings showed changes in students' perceptions toward satisfaction and intention to use e-learning, which might be due to using e-learning exclusively. © 2022 Common Ground Research Networks. All rights reserved.
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Online food ordering (OFDO) services grew tremendously during the covid-19 pandemic due to rising health concerns and social distancing policies put in place. This research aims to examine the relationship between technology readiness level and intention to use OFDO services in Indonesia. Moreover, this research also incorporates the moderating effect of covid-19 pandemic. Surveys were distributed and data were analyzed using multiple regression. The results suggest that the driver variables (optimism and innovativeness) have significant positive effect on intention to use OFDO, while the inhibitor variables (insecurity and discomfort) have no significant effect on intention to use. Furthermore, the moderation of covid-19 situational effect shows significant results for all four variables. These findings suggest that OFDO services should brace themselves towards the end of the pandemic since the booster effect that it gets from the pandemic will soon be gone and they need to take extra measures to retain customers in the absence of the covid-19 pandemic. © 2022 IEEE.
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The world wide outbreak of the COVID-19 pandemic reconfigured various landscapes in higher education as various institutions, lecturers and students were forced to adopt e-learning. However, the successful adoption and acceptance of e-learning by both lecturers and students involved has not been discussed and measured. This study seeks to investigate the influence of both the lecturer and student self efficacy on behavoral intention to use e-learning during the pandemic in the context of the Technology Acceptance Model (TAM). Lecturer Self-Efficacy (LSE) and Student Self-Efficacy (SSE) were hypothesized to have a correlation with the perceived usefullness and perceived ease of use of e-learning systems as well as the attitude towards using those e-learning systems which resultantly influence the behavoural intention to use e-learning systems. A total of 362 questionnaires were received from both students and lecturers in Zimbabwe's two universities and two polytechnics. Structural Equation Modelling was utilized to test the hypothesized conceptual model. Reliability and validity checks were done to the model instrument. Results indicated that both LSE and SSE have a positive influence on perceived ease of use but however, both LSE and SSE revealed a negative influence on perceived usefullness. Results also indicated that both LSE and SSE have a positive influence on attitude towards use of e-learning systems. The findings of the study contribute to the literature by highlighting the influence of LSE and SSE in the adoption and acceptance of e-learning systems in higher education. © 2022 IEEE.
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Since COVID-19, social distancing has become common, and the demand for untact services has increased rapidly, resulting in an economic phenomenon centered on untact worldwide. Due to social distancing, the untact service area is expanding not only to shopping but also to online learning, home training, and telemedicine, and untact services are expected to expand to more diverse areas in the future. This study investigates four types of untact services: online lectures, online meetings related to work and study, online seminars, and online performances, and the effects of concerns about untact services on the intention of use have been examined using a path analysis model. As a result of the analysis, the perceived usefulness had a positive effect on the user's continuous intention to use untact services. However, depending on the type of untact service, it can be confirmed that the factors that affect the intention to continue using the service differ from each other. Practitioners can use the results of this study when designing untact services in the future. © 2023 by the authors.
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A COVID-19 pandemic struck a major section of the world's population in 2020, causing governments in various countries to put in place a range of tracking measures to identify and locate persons afflicted with the virus. While the government installs PeduliLindungi, a tracking application, there are always concerns over the reliability, personal information and data privacy recorded in the system. People might also be reluctant to use technology because of the ease of use. The purpose of this research is then to investigate the factors that have an impact on the likelihood that Indonesians will use the PeduliLindungi application. The UTAUT2 Theory was used as the overarching framework for this research. This theory takes into account a number of different aspects, some of which are performance expectancy, effort expectancy, social impact, an enabling environment, habit, and perceived privacy credibility. Purposive sampling, as well as a quantitative (survey) technique, were used in this study. In this technique, online questionnaires were issued to Indonesian residents who were aware of or had heard about the PeduliLindungi monitoring initiative, yielding 89 valid responses. The data show that the intention to use the PeduliLindungi application has a favorable and strong relationship with four variables. Social influence, facilitating conditions, habit, and perceived privacy credibility are examples of these characteristics. However, it was discovered that performance and effort expectations had no association with the intention to use the specific tracking instrument. This work adds to the field of media information technology studies by presenting the concept of perceived privacy credibility as a key construct for developing the UTAUT2 Theory in respect to the Internet of Things (IoT). This theory provides relevant ways for tracking suspicious patients for government authorities, medical professionals, and healthcare providers. © 2022 IEEE.
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This study aims to investigate the impact on Behavioral Intention and Actual use of Mobile Learning in the Higher Education (HE). The survey was conducted at Cihan University Erbil, and the data was collected by questionnaire. 207 valid questionnaires have been analyzed by Structural equation modelling (SEM). The results indicated that performance expectancy, Effort Expectancy, Facilitating Conditions, Hedonic Motivation, and Habit had a positive and significant impact on Behavioral Intention to use Mobile learning among the students. On the other hand, Social influence and Price Value had an insignificant impact on Behavioral Intention to use Mobile learning among the students. Besides that, the current study reported that behavioral intention directly impacts user behavior (UB). At the same time, facilitating conditions and Habit had an insignificant impact on user behavior. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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As chatbots become more advanced and popular, marketing research has paid enormous attention to the antecedents of consumer adoption of chatbots. This has become increasingly relevant because chatbots can help mitigate the fear and loneliness caused by the global pandemic. Therefore, unlike previous work that focused on design factors, we theorize that social presence serves a mediating role between consumer motivations (i.e., hedonic and utilitarian) and intention to use a chatbot service based on self-determination theory. Our results from a structural equation model (n = 377) indicate that hedonic (but not utilitarian) motivation significantly affects chatbots' social presence, ultimately influencing intention to use the chatbot service. We also found that fear of COVID-19 amplifies the effect of social presence on intention to use the chatbot service. In this dynamic, we found an additional moderated moderation effect of generational cohorts (i.e., baby boomers and Generations X, Y, and Z) in experiencing different levels of fear of COVID-19. Overall, our findings emphasize the importance of motivation-matching features for consumer adoption of chatbot services. Our findings also indicate that marketers may utilize the fear element to increase adoption of chatbot services, especially when targeting the young generations (e.g., Generation Z). © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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The COVID-19 pandemic boosted the digital transformation of many services, including healthcare, and access to medical care using teleconsultation has increased rapidly. Thus, a growing number of online platforms have been developed to accommodate patients' needs. This paper examines the factors that predict the intention to use medical teleconsultation by extending the unified theory of acceptance and use of technology (UTAUT2) with the three dimensions of trusting beliefs and self-efficacy. A survey was administered to patients who had used a teleconsultation platform during the pandemic period. As one of the largest studies to date, a sample of 1233 respondents was collected and analyzed using a partial least squares approach, often mobilized in the information systems (IS) domain. Furthermore, a deep analysis using all recommended metrics was performed. The results highlight the significance of trusting beliefs, and self-efficacy in the adoption of digital healthcare services. These findings contribute to both theory and practice in COVID-19 research. © 2022 Elsevier Ltd
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The Covid-19 epidemic has wreaked havoc on the global economy indeed, Malaysia was unavoidable from this. Nevertheless, this has created a new transformation and renovation for the FinTech industry to develop tremendously. The users of digital wallets are anticipated to grow and hastened the shift from physical payment to digital payment. Touch' n Go e-wallet is one of the FinTech innovation platforms that growing quickest rate ever in Malaysia's emerging market, owing to the upward demand for contactless payments throughout Southeast Asia due to the epidemic. The adoption of digital wallets only grew extensively during the Covid-19 pandemic periods in Malaysia. Hence, the main purpose of this study is to determine the predictors that influence the intention to use Touch' n Go e-wallet among Millennial in Malaysia, particularly during the Covid-19 endemic. This study has proposed to extend the TAM model (perceived usefulness, perceived ease of use) with perceived risk and satisfaction predictors. A sample of a total of 150 millennial in Malaysia who use Touch' n Go e-wallet to participate in the survey. Millennial account for approximately one-third of Malaysia's population and roughly 50 percent of the labour force in Malaysia. The hypotheses were further carried out by employing the ordinary least squares regression analysis. The findings revealed that among Malaysia's millennials, perceived ease of use and consumers satisfaction have a substantial impact on their desire to use Touch' n Go e-wallets app. In order to increase the usage rates of digital payments transaction, the digital wallet service providers in Malaysia must focus on the usability and potential risks that might occur during the transactions are held. More so, a good customer experience will lead to a satisfactory level in using the e-wallet of Touch' n Go. This empirical study provides a model for government to stimulate and foster digital payment in the coming years. © 2022 IEEE.
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M-government services have gained popularity recently, especially during the Covid-19 pandemic and advancements in mobile technology. However, providing the full range of government services on mobile devices is still in the early stages. Moreover, improving and expanding capacity and providing services requires understanding the factors influencing users' behavioral intentions to adopt this technology. This study investigates factors that directly affect the intention to use mobile government services by employing the technology acceptance model and two external factors, trust and social influence in Bahrain by utilizing artificial neural networks and structural equation modeling. Results indicate that the perceived usefulness and trust factors influence users' behavioral intention to use m-government services, followed by perceived usefulness and social influence. The results of the investigated model provide insights to various stakeholders, including the government and developers, to encompass additional security measures and awareness programs among users to achieve higher levels of mobile services usage. © 2022 IEEE.
ABSTRACT
COVID-19 related lockdowns forced students of higher education to receive education entirely online as a replacement for physical attendance in classrooms. This new situation caused students to discover the advantages and disadvantages of e-learning and influenced their satisfaction in using it and intention to use it. Consequently, this study revisits the intention to use and satisfaction-related theories based on pre-COVID conditions. This revisit was necessary because the evidence suggests that students' new situation has changed some determinants related to their satisfaction and intention to use. This situation warranted the simultaneous consideration of many dimensions when measuring user satisfaction and intention to use during the lockdown. This cross-sectional study developed an integrated model to measure students' satisfaction and its impact on intention to use e-learning. Structural equation modeling was used to conduct the empirical analysis. Nine hundred respondents from Malaysia and Saudi Arabia participated in this study. Students from Malaysia and Saudi Arabia showed marginal differences in their perceptions of e-learning. The findings showed changes in students' perceptions toward satisfaction and intention to use e-learning, which might be due to using e-learning exclusively.
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Covid-19 has accelerated the need and use of artificial Intelligence-based healthcare Chabots. Penetration of the internet, smartphone, computational capability and machine learning technology brings healthcare services close to the patients. The penetration of AI healthcare Chatbot technology worldwide is on the rise. However, the healthcare ecosystem in India is unique and poses challenges in the adoption of healthcare chatbots. The demographic characteristics, economic conditions, diversity, belief systems on health-seeking, and alternative medical practices play a role in accepting and using chatbots. In this study, we attempt to model the factors influencing the intention and the purpose of using the chatbot. Through a literature review, we identify the variables related to the adoption of healthcare chatbots. We then focus on the more relevant concepts to the Indian context and develop a conceptual model. Through cases and literature, we frame the propositions of the study. We look at the awareness of chatbot features, perception towards the chatbot, trust and mistrust of the healthcare system, the doctors and the chatbots, health-seeking behavior, and the belief in traditional, complementary, and alternative medicine prevalent in India. This study contributes by developing an initial conceptual model for healthcare chatbots adoption in the Indian context. In the future, we plan to operationalize the study and test the propositions through an elaborate survey to validate the model empirically. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Purpose>This study explores food delivery app users and technology acceptance model as a theoretical underpinning. This study thus investigated the determinants of usefulness, ease of use and intention to use for food delivery app service.Design/methodology/approach>The variables of delivery time, diverse menu, quarantine, review quality and ease of use are employed as determinants of usefulness. The antecedents of ease of use are easy registration and easy payment. This study also examined the association between ease of use, usefulness and intention to use. This study collected data using Amazon Mechanical Turk, and the number of valid observations for statistical analysis was 484. A structural equation model was used to test the hypotheses.Findings>Regarding the results, usefulness was positively affected by delivery time, quarantine, review quality and ease of use. Additionally, ease of use was positively impacted by easy registration and easy payment. Finally, this study showed that ease of use positively affects both usefulness and intention to use, and usefulness is positively associated with intention to use.Originality/value>This study contributes to the literature by ensuring the explanatory power of technology acceptance model for food delivery app.