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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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This paper fills an important gap related to employee perceptions of teleworking during and after the COVID-19 pandemic. Drawing on the work/family border and task-technology fit theories, we propose and empirically test a new model using data collected from 483 employees. Our findings suggest that social well-being, work-family balance and task-technology fit during the pandemic are positively related to teleworking performance. In addition, teleworking performance during the pandemic affects employees' intention to continue to telework and career engagement after the pandemic. Also, we offer evidence of the impact of the moderating effect of factors contributing to the digital divide in this context. Our findings contribute to the teleworking literature, by proposing a model which provides insights into employees' perceptions of teleworking during the pandemic and how this affects their intention to telework and career engagement after the pandemic. Our research has multiple implications for employers, policy makers and technology developers.
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Extended Reality (XR) technologies such as head-mounted displays are deemed beneficial for the collaboration of co-located as well as distributed people. As such, XR technologies appear particularly promising for supporting distant and hybrid teaching which became highly relevant during the Covid-19 pandemic. Despite the potential awarded to such technologies, practical applications are still very rare. In order to investigate the impediments to the practical adoption of XR technologies, the respective systems should be evaluated in real-world settings. Existing evaluation tools are, however, not suited for this purpose. In this paper, we explain why today's evaluation tools such as questionnaires, observation, and performance measurements are not sufficient for evaluating long-time, exploratory, and collaborative tasks that are typical in educational settings. To address this gap, we follow a top-down approach: Based on an existing model of user acceptance, we specify the variables that are to be optimized by HCI research and outline the potential of wearable-based measuring instruments to quantitatively assess these parameters. Eventually, we point out related research gaps that should be addressed by future research.
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Augmented reality is gaining popularity in a variety of disciplines, particularly in educational environments. Distance learning has become a reality in the aftermath of the Covid-19 epidemic. It is already in use worldwide, and education using augmented reality technology will assist learners in absorbing learning information in a more creative state of mind than ever before. There has been little study into the adoption of augmented reality in developing countries. As a result, understanding the characteristics of augmented reality adoption is critical for encouraging and motivating students to use this incredibly creative and effective form of technology in the continuous adaptation of the distance educational process after the covid 19 epidemic. In light of this, the authors combined UTUAT2 and Task-Technology Fit theories. The study has targeted undergraduate students at Al-Ain University in the United Arab Emirates to gather the data. Purposive sampling procedures were employed to gather a valid sample of 534 questionnaires for this investigation. Finally, the acquired data were analyzed using the Partial Least Square Structural Equation Model (PLS-SEM). The results revealed that technology characteristics, performance expectancy, effort expectancy, hedonic motivation, and task technology fit have a significant and positive effect on behavioral intention. In addition, the findings indicated that task technology fit partially mediated the effect of technology characteristics, performance expectancy on behavioral intention. The findings of this study will contribute more useful knowledge to the literature, resulting in a greater understanding of the characteristics and behaviors of Augmented reality after covid 19 pandemic implementation in developing countries. © 2023 Eskisehir Osmangazi University. All rights reserved.
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Telemedicine's growth during the COVID-19 pandemic exposed digital and health disparities in U.S. communities. Public health advocates suggest disparities in healthcare access may be mitigated through free or low-cost broadband. However, prior research shows that many factors influence patient adoption of information technologies;therefore, increasing access to broadband alone is insufficient. This paper advances a patient-centered model of telemedicine (TM) adoption supported by qualitative interview data. The model illustrates that patient adoption of TM is driven by a complex sociotechnical system comprised of technology factors, structural factors underlying the provider's provision of TM, and individual patient factors. Findings highlight the importance of the physical place of the TM visit, the need for experienced TM healthcare workers and technology support for patients, the impact of provider-mandated technology on task-technology fit (TTF), and the strength of the patient-provider relationship. These factors affect patient perceptions of TTF and ultimately TM adoption.
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PurposeCOVID-19 has galvanized educational institutions to rapidly adopt technology-enhanced learning (TEL) environment where students are required to use and manage a diverse set of information and communication technologies (ICTs). Using the Transactional Theory of Stress, the authors investigate the impact of a TEL environment on students' stress, cognitive appraisal and coping. The authors also explore how the TEL environment impacts students' learning satisfaction and performance.Design/methodology/approachA survey using Qualtrics was developed to collect the data from 275 undergraduate students. The authors used the Partial Least Squares (PLS) through SmartPLS for instrument validation and testing of the structural model. The reflective-formative model was applied as the measures used to evaluate the first-order constructs are unidimensional, and the second-order construct has a formative measurement.FindingsStudents experienced technology-related stress due to ICT use. The negative appraisal such as harm and threat leads to emotion-focused coping among students, while the constructive appraisal such as positive and challenge leads to problem-focused coping. Emotion-focused coping was found to negatively impact learning satisfaction, while problem-focused coping was found to positively impact satisfaction. The authors also found that students with a higher level of experience with online and hybrid classes, higher confidence in computer usage and lower anxiety are better equipped to deal with technostress.Research limitations/implicationsThis study provides the first comprehensive technostress model in the IS literature that uses formative modeling to explain technostress creators and inhibitors and emotion-focused coping and problem-focused coping, as was intended by the Transactional Theory of Stress. The result allows for rethinking TEL environment by drawing attention to strategies that can reduce technological complexity and uncertainty. For future research, it may be helpful to perform a longitudinal or experimental study to obtain rigorous causal inference. Originality/valueThere is limited research on the impact of technostress in the field of higher education. Also, technostress has been used inconsistently in Information Systems research, with the majority of research focusing on technostress creators and inhibitors only. This research incorporates all the constructs of the original theory adding new knowledge to the IS literature about the nature and causes of stress created by the use of technology.
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Purpose: Mobile learning has emerged as one of the main methods for training and academic activities in the present era. It is, also, highly relevant in the wake of the COVID-19 pandemic whereupon digitization of mobile learning has made it possible for many students to continue with their education. This study investigated attitudes and intentions towards the adoption of mobile learning in vocational education. Design/methodology/approach: This is a quantitative study based on cross-sectional empirical data. In targeting vocational students throughout Pakistan, the study used a survey questionnaire with a convenience sampling method. From the responses to the questionnaire, 320 samples were used to obtain the study outcomes. Findings: The structural equation modeling's (SEM) findings reveal that learning autonomy (LA), mobile device self-efficacy (MDSE), task-technology fit (TTF), perceived ease of use (PEOU), perceived usefulness (PUS) and perceived enjoyment (PE) have a positive and significant effect on mobile usage attitudes (MUA) and intentions to adopt mobile learning (ITAML). Moreover, this study's findings confirm, also, MUA's predictive power on ITAML. Practical implications: Further, this study's findings encourage individuals to use mobile devices to properly promote knowledge in society. In addition, this study's findings support vocational institutions' operators' and policymakers' development of online education and training strategies to resist the complications arising from the transmission of COVID-19. Moreover, this study's findings open new doors when conducting similar research studies on students' perceptions and learning behaviors. Originality/value: The empirical investigation of attitudes and intentions to adopt mobile learning in the context of COVID-19 helps potential adopters to test the likely behaviors. [ FROM AUTHOR] Copyright of Education + Training is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Five hundred survey responses on consumer acceptance of autonomous delivery robots (ADRs) were collected because the pandemic has increased the emphasis on contactless deliveries, spurring some interest in ADRs to perform last-mile deliveries in urban cities. To examine consumers' intention to adopt ADRs, a comprehensive theoretical model grounded on the Health Belief Model and Task-Technology Fit Model was presented and structural equation modeling was applied to examine the survey data. The analysis revealed that the constructs from both theories have significant effects on outcome expectations and task-technology fit. Additionally, outcome expectations and task-technology fit are strong predictors of consumers' intention, as indicated by their direct and indirect effects. Thus, this study enriches existing research by interpreting consumers' intention to adopt ADRs through health and technology perspectives. It also provides practical implications and policy recommendations for urban planning and design. © 2022 Elsevier Ltd
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The COVID-19 pandemic resulted in the hurried adoption of e-learning with no proper need analysis to inform the design and subsequent evaluation of students' performance in e-learning in medical education. Consequently, several studies evaluating performance in e-learning in medical education do so by conducting pre-Test and post-Test with no defined framework or model to guide the evaluation. This makes the findings from these studies subjective and biased since factors that possibly impact students' performance were neither considered in the design of the course nor measured and reported in the evaluation studies. We, therefore, introduce an essential pedagogical e-learning concept by developing a framework to inform the design and evaluation of students' performance in e-learning in medical education via the thoughtful fusion of the Task-Technology Fit Model and the Kirkpatrick Evaluation Model. Our hybrid framework was piloted at the University of KwaZulu-Natal, Durban, South Africa and findings emphasize the need for alignment between learning tasks, technology infrastructures, individual traits, and contextual limitations of students as key factors in determining how well students perform in the classroom and their clinical practices at work. This study advances the body of knowledge by providing a well-brainstormed and intricately designed framework to guide the design of courses and evaluation of student's performance in an e-learning context in medical education. © 2022 IEEE.
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Cutting-edge technologies are changing the operations of urban last-mile delivery. In particular, innovative technologies, such as delivery drones, have shown promising results in commercial applications. When considered alongside the ongoing pandemic, contactless technologies have become even more important to the daily lives of consumers in highly urbanized areas. This study investigates underlying factors influencing consumers' acceptance of drone delivery in urban cities amidst the COVID-19 pandemic. To this end, a model was created by fusing the technology acceptance model, task–technology fit, and privacy calculus theory. Four hundred and fifty survey responses were analyzed using structural equation modeling. The findings suggested that perceived usefulness, attitude, and perceived privacy risks directly influence consumers' behavioral intentions. In addition, perceived ease of use, task characteristics, technology characteristics, task–technology fit, and privacy concerns indirectly impact consumers' behavioral intention. This study offers an insightful perspective on consumers' perception of urban last-mile delivery drones while providing insights into urban transport planning and regulation of drone delivery services. © 2023 Elsevier Ltd
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PurposeWith the outbreak of the COVID-19 pandemic, online assessment has become the dominant mode of examination in higher education institutions. However, there are contradictory findings on how students perceive online assessment and its impact on their academic performance. Thus, the purpose of this study is to evaluate the potential impact of online assessment on students' academic performance.Design/methodology/approachThis study proposes a research model based on the task-technology fit theory and empirically validates the model using a survey from students in the UK. In addition, the study conducted four experiments based on paper-based and online assessments and analysed the data using paired sample t test and structural equation modelling.FindingsThe findings show that the use of online assessment has a positive impact on students' academic performance. Similarly, the results from the experiment also indicate that students perform better using online assessments than paper-based assessments.Practical implicationsThe findings provide crucial evidence needed to shape policy towards institutionalising online assessment. In addition, the findings provide assurance to students, academics, administrators and policymakers that carefully designed online assessments can improve students' academic performance. Moreover, the study also provides important insights for curriculum redesign towards transitioning to online assessment in higher education institutions.Originality/valueThis study advances research by offering a more nuanced understanding of online assessment on students' academic performance since the majority of previous studies have offered contradictory findings. In addition, the study moves beyond existing research by complementing assessment results with the views of students in evaluating the impact of online assessment on their academic performance. Second, the study develops and validates a research model that explains how the fits between technology and assessment tasks influence students' academic performance. Lastly, the study provides evidence to support the wide use of online assessment in higher education.
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With the COVID-19 pandemic, the importance of home health care to manage and monitor one's health status in a home environment became more crucial than ever. This change raised the need for smart home health care services (SHHSs) and their extension to everyday life. However, the factors influencing the acceptance behavior of SHHSs have been inadequately investigated and failed to address why users have the intention to use and adopt the services. This study aimed to analyze the influential factors and measure the behavioral acceptance of SHHSs in South Korea. This study adopted the integrated model of the unified theory of acceptance and use of technology (UTAUT) and task-technology fit (TTF) to understand the behavioral acceptance of SHHSs from users' perceptions and task-technology fit. Multiple-item scales were established based on validated previous measurement scales and adjusted in accordance with SHHS context. Data from 487 valid samples were analyzed statistically, applying partial least square structural equation modeling. The results indicated that the integrated acceptance model explained 55.2% of the variance in behavioral intention, 44.9% of adoption, and 62.5% of the continuous intention to use SHHSs, supporting 11 of the 13 proposed hypotheses. Behavioral intention was positively influenced by users' perceptions on performance expectancy, effort expectancy, social influence, and functional conditions. Task-technology fit significantly influenced performance expectancy and behavioral intention, validating the linkage between the two models. Meanwhile, task characteristics were insignificant to determine task-technology fit, which might stem from complex home health care needs due to the COVID-19 pandemic, but were not sufficiently resolved by current service technologies. The findings implied that the acceptance of SHHSs needs to be evaluated according to both the user perceptions of technologies and the matching fit of task and technology. Theoretically, this study supports the applicability of the integrated model of UTAUT and TTF to the domain of SHHS, and newly proposed the measurement items of TTF reflecting the domain specificity of SHHS, providing empirical evidence during the pandemic era in South Korea. Practically, the results could suggest to the planners and strategists of home health care services how to promote SHHS in one's health management.
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COVID-19 , Home Care Services , Humans , COVID-19/epidemiology , Pandemics , Republic of Korea , TechnologyABSTRACT
This study aims to investigate patients’ behavioral intention toward the adoption of contactless healthcare applications in the post- COVID-19 pandemic era. Therefore, the study model extends the unified theory of acceptance and use of technology (UTAUT) with the task technology fit (TTF) model, personal innovativeness, and avoidance of personal interaction to determine patients’ intention to adopt contactless healthcare applications for medical purposes. A research questionnaire was conducted on Jordanian citizens in a voluntary environment. In response, 383 valid questionnaires were retrieved. The study model is empirically analyzed with structural equation modeling (SEM). Findings of the structural model imply that was jointly predicted by UTAUT constructs, TTF, and API and explained substantial variance R2 78.4% in user behavior to adopt contactless healthcare applications. The current research contributes to theory by extending the UTAUT with the TTF model, API, and PI and enriching information systems literature in the context of users’ intention to adopt e-health technology. Practically, this research suggests that healthcare services providers should focus on IT fitness including internet-enabled devices and the number of facilities to operate the healthcare applications which in turn boost individual confidence towards the adoption of contactless healthcare technology. This research develops a unique model that examines user behavior towards the adoption of contactless healthcare technology to improve the healthcare industry. The findings of this research provide an answer on how to recover from COVID-19 repercussions on the healthcare sector while using such applications. Moreover, this study provides guidelines for clinical management through a virtual setting and guides health consultants, applications developers, and designers to design user-friendly applications for e-healthcare purposes. © 2022, IFIP International Federation for Information Processing.
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Due to the COVID-19 epidemic, ordering food online has become very popular. This study used a structural equation model to analyze the indicators that influence the decision to order food through a food-delivery platform. The theory of planned behavior and the technology acceptance model were both used, along with a new factor, the task-technology fit (TTF) model, to study platform suitability. Data were collected using a questionnaire given to a group of 1320 consumers. The results showed that attitudes toward on-line delivery most significantly affected the behavioral intentions of the consumers, followed by subjective norms. Among attitudes, perceived ease of use was the most significant, followed by perceived usefulness and trust. The study's results revealed that TTF had the most significant impact on perceived ease of use, followed by perceived usefulness. This means that, if a food-ordering platform is deemed appropriate, consumers will continue to use it, and business sustainability will be enhanced.
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Purpose: Mobile learning has emerged as one of the main methods for training and academic activities in the present era. It is, also, highly relevant in the wake of the COVID-19 pandemic whereupon digitization of mobile learning has made it possible for many students to continue with their education. This study investigated attitudes and intentions towards the adoption of mobile learning in vocational education. Design/methodology/approach: This is a quantitative study based on cross-sectional empirical data. In targeting vocational students throughout Pakistan, the study used a survey questionnaire with a convenience sampling method. From the responses to the questionnaire, 320 samples were used to obtain the study outcomes. Findings: The structural equation modeling’s (SEM) findings reveal that learning autonomy (LA), mobile device self-efficacy (MDSE), task-technology fit (TTF), perceived ease of use (PEOU), perceived usefulness (PUS) and perceived enjoyment (PE) have a positive and significant effect on mobile usage attitudes (MUA) and intentions to adopt mobile learning (ITAML). Moreover, this study’s findings confirm, also, MUA’s predictive power on ITAML. Practical implications: Further, this study’s findings encourage individuals to use mobile devices to properly promote knowledge in society. In addition, this study’s findings support vocational institutions’ operators’ and policymakers’ development of online education and training strategies to resist the complications arising from the transmission of COVID-19. Moreover, this study’s findings open new doors when conducting similar research studies on students’ perceptions and learning behaviors. Originality/value: The empirical investigation of attitudes and intentions to adopt mobile learning in the context of COVID-19 helps potential adopters to test the likely behaviors. © 2022, Emerald Publishing Limited.
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In the Covid-19 pandemic, many students must study at home utilizing an E-learning system because of social alienation. The goal of this study is to analyze students' continued motivation to use the E-learning system during the Covid-19 pandemic using the Technology Acceptance Model (TAM) and the Theory of Task-Technology Fit (TTF). Both qualitative and quantitative methodologies were employed in this work. The qualitative approach's goal is to confirm and adopt the scale. In contrast, a quantitative study seeks to determine if students in the Covid-19 pandemic have a strong desire to use the E-learning system students will continue to utilize E-learning in the future, according to the research. They will continue to adopt E-learning due to its social influence, usefulness, and ease of use. Based on the findings, the research suggested numerous suggestions to enhance and promote E-learning for Vietnamese universities to further the development of Vietnamese education. © 2022 IEEE.
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Undoubtedly, due to the increasingly competitive pressures and the stride of varying demands, volatility and disturbance have become the standard in today's global markets. The spread of Covid-19 is a prime example of that. Supply chain managers are urged to rethink their competitive strategies to make use of Big Data Analytics (BDA), due to the increasing uncertainty in both demand and supply side, the competition among the supply chain partners and the need to identify ways to offer personalised products and services. With many supply chain executives recognising the need of 'improving with data', supply chain businesses need to equip themselves with sophisticated BDA methods/techniques to create valuable insights from big data, thus, enhancing the decision-making process and optimising the efficiency of Supply Chain Operations (SCO). This paper proposes the building blocks of a theoretical framework for understanding the impact of BDA on SCO. The framework is based on a Systematic Literature Review (SLR) on BDA and SCO, underpinned by Task-Technology-Fit theory and Institutional Theory. The paper contributes to the literature by building a platform for future work on investigating factors driving and inhibiting BDA impact on SCO.
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Extended Reality (XR) technologies such as head-mounted displays are deemed beneficial for the collaboration of co-located as well as distributed people. As such, XR technologies appear particularly promising for supporting distant and hybrid teaching which became highly relevant during the Covid-19 pandemic. Despite the potential awarded to such technologies, practical applications are still very rare. In order to investigate the impediments to the practical adoption of XR technologies, the respective systems should be evaluated in real-world settings. Existing evaluation tools are, however, not suited for this purpose. In this paper, we explain why today’s evaluation tools such as questionnaires, observation, and performance measurements are not sufficient for evaluating long-time, exploratory, and collaborative tasks that are typical in educational settings. To address this gap, we follow a top-down approach: Based on an existing model of user acceptance, we specify the variables that are to be optimized by HCI research and outline the potential of wearable-based measuring instruments to quantitatively assess these parameters. Eventually, we point out related research gaps that should be addressed by future research. © 2022, IFIP International Federation for Information Processing.
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The ongoing pandemic has transformed communication modes globally. Especially in the case of higher education, where countermeasures against coronavirus disease 2019 (COVID-19) have affected students' learning experience. This study emphasized the case of business simulation games, where critical factors were underlined to define learners' intention to use an online learning environment through the lens of task technology fit (TTF) as a theoretical stance. This study considered the statistical analysis of 523 students who attended the business simulation module online at the tertiary level of education. Findings conclude that flow experience is the most critical factor to define learners' perceived TTF in the case of an online learning experience. However, the learners' self-efficacy is significant enough to map learners' intentions to use an online environment for learning. The study discussed several theoretical and practical implications for learners' educators and policymakers.
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Purpose: COVID-19 has galvanized educational institutions to rapidly adopt technology-enhanced learning (TEL) environment where students are required to use and manage a diverse set of information and communication technologies (ICTs). Using the Transactional Theory of Stress, the authors investigate the impact of a TEL environment on students' stress, cognitive appraisal and coping. The authors also explore how the TEL environment impacts students' learning satisfaction and performance. Design/methodology/approach: A survey using Qualtrics was developed to collect the data from 275 undergraduate students. The authors used the Partial Least Squares (PLS) through SmartPLS for instrument validation and testing of the structural model. The reflective-formative model was applied as the measures used to evaluate the first-order constructs are unidimensional, and the second-order construct has a formative measurement. Findings: Students experienced technology-related stress due to ICT use. The negative appraisal such as harm and threat leads to emotion-focused coping among students, while the constructive appraisal such as positive and challenge leads to problem-focused coping. Emotion-focused coping was found to negatively impact learning satisfaction, while problem-focused coping was found to positively impact satisfaction. The authors also found that students with a higher level of experience with online and hybrid classes, higher confidence in computer usage and lower anxiety are better equipped to deal with technostress. Research limitations/implications: This study provides the first comprehensive technostress model in the IS literature that uses formative modeling to explain technostress creators and inhibitors and emotion-focused coping and problem-focused coping, as was intended by the Transactional Theory of Stress. The result allows for rethinking TEL environment by drawing attention to strategies that can reduce technological complexity and uncertainty. For future research, it may be helpful to perform a longitudinal or experimental study to obtain rigorous causal inference. Originality/value: There is limited research on the impact of technostress in the field of higher education. Also, technostress has been used inconsistently in Information Systems research, with the majority of research focusing on technostress creators and inhibitors only. This research incorporates all the constructs of the original theory adding new knowledge to the IS literature about the nature and causes of stress created by the use of technology. © 2022, Emerald Publishing Limited.