Exploring the Factors Influencing the Adoption of Wrist-Worn Wearable Devices for Well-Being Monitoring Among End Users

In monitoring individual health, wearable technologies, especially wrist-worn wearable devices, play a crucial role by actively collecting and displaying fundamental wellness-related data such as steps, calories, skin temperature, heart rate, and sleep patterns. Promoting their widespread acceptance is key for improving overall well-being, benefiting both individuals and society. Employing the Technology Acceptance Model (TAM), the Model of PC Utilization (MPCU), and the Innovation Diffusion Theory (IDT), this paper introduces a novel research model that identifies functional determinants (perceived usefulness, perceived value), social determinants (brand name, social image, perceived prestige), and privacy-related factors (health information sensitivity, perceived privacy risk) influencing the adoption of wrist-worn wearable devices. The study utilizes a survey on end users for data collection, and Structural Equation Modeling is employed to analyze significant factors affecting adoption. The findings reveal that functional aspects significantly impact adoption, particularly when supported by social elements. Privacy considerations emerge as a crucial factor influencing adoption. This research contributes to the field by expanding the spectrum of factors influencing the adoption of wrist-worn wearable devices beyond mere functionality and offers managerial and societal implications.