Sustainable crowdsourced delivery: A study of technological, health, value, and trust antecedents of consumer loyalty

Crowdsourced delivery has various advantages over conventional delivery methods, including a decrease in emissions and road congestion. These benefits grow as consumer loyalty is established due to network externalities. This study seeks to identify the factors influencing customer loyalty to crowdsourced delivery through the unified theory of acceptance and use of technology, the health belief model, the perceived value theory, and the trust theory. First, a questionnaire was administered to 500 respondents in Singapore, and the data was analyzed using structural equation modeling. The findings show that technology and health belief constructs have direct impacts on the perceived value of crowdsourced delivery, while perceived value has direct and indirect effects on consumer loyalty through trust. Overall, this study contributes to the literature theoretically and practically by developing a paradigm for understanding the growth of customer loyalty to crowdsourced delivery from the perspectives of consumers and health beliefs. It also offers operators and policymakers concrete areas for improvement in resource allocation, security, and marketing to increase overall consumer loyalty to crowdsourced delivery. © 2023 The Authors

Digital transformation of healthcare during the COVID-19 pandemic: Patients' teleconsultation acceptance and trusting beliefs

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

Factors Influencing the decision to Utilize eTax Systems during the CoVId-19 Pandemic: The Moderating Role of Anxiety of CoVId-19 Infection

This study examines the usage of eTax systems using the unified theory of acceptance and use of technology (UTAUT) as a theoretical base. A quantitative methodology using partial least squares-structural equation modelling (PLS-SEM) was used to test the study model against data collected from 209 taxpayers who completed the research questionnaire. The outcomes of this study manifest necessary theoretical extension of the UTAUT model and practical contributions during the pandemic of COVID-19. The findings of this study reveal that the behavioral intention to use eTax systems is highly influenced by performance expectancy, effort expectancy, social influence, social isolation, and anxiety about technology. Similarly, the behavioral intention of eTax systems and anxiety of COVID-19 infection demonstrate a substantial association with the actual usage of eTax systems. Interestingly, the study's findings also show that the anxiety of COVID-19 infection moderates the association bounded by usage intention and actual use of eTax systems. Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Understanding the Patients’ Usage of Contactless Healthcare Services: Evidence from the Post-COVID-19 Era

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.

Determinants for Adoption of MOOCs from the Perspective of UTAUT

The growth of information and communication technology (ICT) coupled with cheaper internet charges and android and windows-based computing devices facilitate online learning. The scaling up of the online teaching and learning process helping both educators and learners has happened during covid-19. Students have been using various platforms for online learning according to their level of understanding and as per instructions given by their institutes. The present study aims to examine the adequacy of the Unified Theory of Acceptance and Use of Technology (UTAUT) as a base theory in an academic context for identification of the factors which impact academicians and students' behavioral intentions in the adoption of MOOCs. Studies have been conducted in developed countries but a detailed study where students' have undergone sufficient exposure to remote learning is now worthwhile. The cross-sectional study used a descriptive methodology to test hypotheses related to the interaction between dependent variable behavioral intention of UTAUT, with independent variables like facilitating conditions (FC), performance expectancy (PE), social influence (SI), and effort expectancy (EE). Data was gathered through a self-administered questionnaire designed using Questionpro. For data analysis, multiple linear regression (MLR) was carried out using SPSS software V23. The research model was found significant with an explanatory power of 39.8 %. The study found that PE and EE were significant influencers to academicians' and students' behavioral intention for MOOCs. SI and FC, on the other hand, were not found to be significant predictors. © 2022 IEEE.

Understanding Students' Behavioural Intentions To Use Social Media Learning In Education: A Utaut Model Approach

This paper seeks to examine students' behavioral intention to adopt social media learning in education through a unified theory of acceptance and use of technology (UTAUT) model based on data collected from 279 undergraduate students of different colleges of Delhi University, Delhi, India. The results revealed that students' behavioral intention to use social media learning in education is significantly affected by their perceptions about performance expectancy, effort expectancy, facilitating conditions, and Covid-19 induced social isolation but not by social factors. Out of four moderating variables, the impact of only one variable, i.e., area of residence is found to be most significant across all the relationships studied. Study results are important for the policymakers to incorporate social media tools as an essential part of their future policies for higher education in India, and by extension for educational levels as well. © 2021 IEEE.

User Satisfaction Analysis Model of Google Classroom for Online Lectures in COVID-19 Pandemic

Google Classroom is one of e-learning platform used for online lectures in COVID-19 (Coronavirus Disease) pandemic at Amikom Purwokerto University. As one of the most widely used e-learning platform, so it is interesting to evaluate the satisfaction of Google Classroom user for improvement purpose in the future. The methods used in this research are End User Computing Satisfaction (EUCS), Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Acceptance Model (TAM), and Human Organization Technology (HOT FIT). These methods used to determine user satisfaction level and compare the accuracy of four methods in measuring user satisfaction of Google Classroom application. The test analysis used is validity test, reliability, user satisfaction test, and Multiple linear regression test. The performances present that they are satisfied with Google Classroom application, the percentage of average value obtained from each method: EUCS of 77.57%, TAM by 80.33%, UTAUT by 72.35%, and HOT FIT by 78.34%. The accuracy comparison of four methods results shows that the best method used in measuring the user satisfaction level of Google Classroom applications is using Human Organization Technology (HOT FIT) method with average results of R-Square value is 28.22%. © 2021 IEEE

Online Learning and COVID-19 in Higher Education: The Value of IT Models in Assessing Students’ Satisfaction

In online learning, students’ 'fit' (or satisfaction) with necessary technologies has become a vital component in assessing their learning efficacy,especially during the COVID-19 pandemic. While current studies have notedthe impact of the curriculum, the instructor, and the learner, there is insufficientunderstanding of factors that predict students’ satisfaction with online learningduring the crisis [38]. Existing studies focus on pre-pandemic circumstances,where online learning was a minor part of the higher education (HE) paradigm.This study assesses HE students’ use (i.e. 'fit') with online learning via theirperception, behavioral intention, and satisfaction. By utilizing the InformationTechnology (IT) models of Task-Technology Fit (TTF) and Unified Theory ofAcceptance and Use of Technology (UTAUT), the study investigates if, fromstudents’ perspective, pedagogical theories are aligned with the IT models, using the quantitative survey method to gather input from students across variousdisciplines in a Singaporean university. Standard descriptive and correlationanalyses studied the link between factors and their influence on online learningsatisfaction. Significantly, the IT models are found to be valuable in assessingonline learning satisfaction. Recommendations arising from the study providehelpful strategic guidelines for future online learning, which apply to Singaporeand online learning design in general, particularly in this time of paradigmchange. © 2022,International Journal of Emerging Technologies in Learning. All Rights Reserved.

Technology Acceptance of MS Teams Among University Teachers During COVID-19

The choice of software for implementing online learning has always been one of the fundamental problems in education sciences. Efficiency and quality of education largely depend on the properties of the tool (software) that the teacher uses. The COVID-19 pandemic has led to the rise in numbers of users of e-learning tools. Decision makers had to choose which available product their corporation, university or school would use. After several months of widespread implementation of different e-learning software, users are ready to give an evaluation. The aim of this paper is to provide such evaluation on MS Teams, which can be obtained by applying Technology Acceptance Models. Among the set of Technology Acceptance Models developed in science and verified in practice, the Unified Theory of Acceptance and Use of Technology (UTAUT) deserves special attention due to its flexibility and large predictive power. We propose an enriched UTAUT model for MS Teams, which adds two new variables to the original: Product Superiority (PS) and System Comprehensiveness (SC). This paper presents the development of Technology Acceptance Models as a software evaluation method, followed by the presentation of hypotheses and description of the research method used. The research was carried out using the questionnaire distributed among university teachers from northern Poland. We present the analysis of the results along with the conclusions formulated on their basis. At the end, we highlight the interpretative limitations and indicate further research directions. © 2022, Springer Nature Switzerland AG.

Students' Perceptions of E-Learning Systems at the Jordanian Universities Through the Lens of E-Business Booming During the Coronavirus Pandemic

This paper investigates undergraduate students' perceptions and acceptance of e-learning systems at Jordanian universities. The framework of this study is guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) and DeLone and McLean Information System Success Model. The online questionnaire is used to collect data from 411 undergraduate students at Jordanian public and private universities. Partial Least Squares Structural Equation Modeling (PLS-SEM) is used to analyze the data. The findings suggest that (1) performance expectancy, facilitating conditions, and information quality have a significant, positive effect on the actual usage of e-learning systems, whereas system quality did not;(2) the usage of e-learning systems positively influences educational performance and students' satisfaction;(3) the impact of COVID-19 moderates the relationship between the use of e-learning systems and educational performance;and (4) face-to-face is the most favorable educational-learning approach, followed by blended and e-learning. Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.