FACTORS INFLUENCING THE INTENTION TO USE MYSEJAHTERA APPLICATION AMONG MALAYSIAN CITIZENS DURING COVID-19: A PLS-SEM Analysis

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Technology Adoption and User Behaviour Mobile Health and mHealth Applications COVID-19 Digital Contact Tracing

Abstract

Many countries in the globe have experienced COVID-19 pandemic in the year 2020, and this has caused government to come out with various tracking applications to trace the individuals who get infected with the virus. However, with the implementation of the tracking application by the government, there always be issues related to the personal information and data privacy store in the system, which will make the citizens intent to use the technology or vice-versa. Hence, this study aims to examine the factorsinfluencing the intention to use MySejahtera application among Malaysian citizens. The study utilized Unified Theory of Acceptance and Use of Technology (UTAUT2) Theory to guide the study, where the determinants were performance expectancy, effort expectancy, social influence, facilitating conditions, habit, and perceived privacy credibility. Purposive sampling was employed in this study, where a quantitative (survey) method was used, in which online questionnaires were distributed to the Malaysian citizens who know or have heard about the MySejahtera tracking application which ultimately with generated 401 valid responses. The data were then analysed using Partial Least Squares Structural Equation Modelling through Smart-PLS 3.0. The results revealed that four (4) determinants (social influence, facilitating conditions, habit, and perceived privacy credibility) have a positive and significant relationship with intention to use MySejahtera application. However, performance expectancy and effort expectancy were found not to be significantly related to intention to use the particular tracking application. The study contributes to the media information technology scholarship by incorporated perceived privacy credibility as an important construct to further expand the UTAUT2 Theory in relation to the Internet of Things (IoT), which provide relevant strategies for government agencies, medical and healthcare practitioners to track on the suspected patients. Conclusion, implications, and suggestions for future study were also discussed.

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2015A primer on partial least squares structural equation modeling (PLS-SEM)1998The partial least squares approach for structural equation modeling.2021Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R 2014Consistent and asymptotically normal PLS estimators for linear structural equations 2020Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research 2018Partial least squares path modeling: Quo vadis?2013A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling 2021PLS-SEM STATISTICAL PROGRAMS: A REVIEW

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