Abstract
The advancement in wireless sensor and information technology has offered enormous healthcare opportunities for wearable healthcare devices and has changed the way of health monitoring. Despite the importance of this technology, limited studies have paid attention for predicting individuals’ influential factors for adoption of wearable healthcare devices. The proposed research aimed at determining the key factors which impact an individual's intention for adopting wearable healthcare devices. The extended technology acceptance model with several external variables was incorporated to propose the research model. A multi-analytical approach, structural equation modelling-neural network, was considered for testing the proposed model. The results obtained from the structural equation modelling showed that the initial trust is considered as the most determinant and influencing factor in the decision of wearable health device adoption followed by health interest, consumer innovativeness, and so on. Moreover, the results obtained from the structural equation modelling applied as an input to the neural network indicated that the perceived ease of use is one of the predictors that are significant for adoption of wearable health devices by consumers. The proposed study explains the wearable health device implementation along with test adoption model, and their outcome will help providers in the manufacturing unit for increasing actual users’ continuous adoption intention and potential users’ intention to use wearable devices.
Highlights
By the advancement of wireless sensor and information technologies, wearable healthcare devices have emerged as a new technology through which people can monitor their physiological conditions
E wearable health devices are considered as hardware and discover users’ important features by using mobile application and web software. ese wearable devices are considered as a type of hardware which understands the effective features through the Internet and mobile application which are cooperated by the data gathered with the devices
To fill the gaps in the existing literature, this study has proposed a new research model for the forecasting of individuals’ behavior intention and analyzing the key factors that influence the decision to the adoption of wearable healthcare devices. e originality of the model approached in this research revolves around the fact that, besides well-known predictors of new technology adoption, such as perceived usefulness and perceived ease of use, it includes factors such as health interest, perceived expensiveness, consumer innovativeness, and compatibility, which were examined in few studies
Summary
By the advancement of wireless sensor and information technologies, wearable healthcare devices have emerged as a new technology through which people can monitor their physiological conditions. E collected data from wearable devices can be used by consumers to manage their health conditions via smartphones or other mobile applications. The physical data monitored by a wearable device can be transmitted to hospitals for healthcare facilities. E wearable health devices are considered as hardware and discover users’ important features by using mobile application and web software. Ese wearable devices are considered as a type of hardware which understands the effective features through the Internet and mobile application which are cooperated by the data gathered with the devices. A recent survey by Lee and Lee [4] found that, for decreasing the medical cost, the wearable healthcare device is considered as the best solution. A recent survey by Lee and Lee [4] found that, for decreasing the medical cost, the wearable healthcare device is considered as the best solution. e research carried out by Roman et al [5] uncovered that wearable healthcare devices contributed to saving $305 billion medical cost in the United States alone
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