Computer Science, Information Technology and Telecommunications

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Browsing Computer Science, Information Technology and Telecommunications by Subject "Activity trackers (Wearable technology)"

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    Users’ behavioural intention model of using smart wellness wearables in Malaysia
    (Universiti Teknologi Malaysia, 2019) Niknejad, Naghmeh
    Internet of Things (IoT) has attracted policymakers and academics’ attention as the next generation of digital revolution. In many developing countries, including Malaysia, rapid social and economic growth has spurred the emergence of chronic diseases as a significant public health challenge. Practitioners and researchers believe that physical inactivity and an unhealthy lifestyle will lead to these diseases. Nowadays, smart wellness wearables are considered a hot topic in the healthcare context to encourage individuals to have a healthier lifestyle and be responsible for their own health. Despite the important role of smart wearables in healthcare, limited number of researches have investigated some critical factors or empirically examined a limited number of important factors from the technology perspective. Therefore, a comprehensive model to explain users' intention to use smart wellness wearables is strongly needed. Accordingly, to identify potential factors that influence individuals’ intention toward smart wellness wearables usage, a comprehensive and systematic literature review was conducted. The research developed a unified model based on Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Valuebased Adoption Model (VAM) including extra factors of perceived health increase and perceived trust. A quantitative approach was applied to examine fifteen hypotheses of the proposed model by surveying 254 smart wellness wearables’ users in Malaysia. The survey data were analyzed using Partial Least Square Structural Equation Modeling (PLS-SEM) technique. The results indicated that perceived enjoyment, effort expectancy, performance expectancy, and perceived fee had a significant influence on perceived value, while perceived privacy did not have any significant impact on perceived value. Moreover, the results revealed that effort expectancy, performance expectancy, perceived enjoyment, perceived fee, perceived health increase, perceived trust, social influence, and perceived value had significant effects on intention to use smart wellness wearable devices while facilitating conditions and intention to use did not have any significant relationship. Theoretically, these results have enhanced the understanding of multiple factors that influence behavioural intention for using smart wellness wearables. The research findings contribute to the Information Systems research field by providing a holistic research model for researchers and practitioners for increasing users’ intention to use smart wellness wearables.