Understanding IoT wearable adoption: a TAM-TTF perspective

Purpose The purpose of this research is to identify the key determinants influencing the adoption of IoT-enabled wearable devices in India. The study aims to offer suggestions for the integration of IoT in the Indian market, highlighting user perceptions, technological attributes and task-related requirements. Design/methodology/approach This study adopts an empirical research methodology using a quantitative approach to explore the adoption of IoT wearable devices in India. The research integrates the technology acceptance model (TAM) and task-technology fit (TTF) frameworks. Data were collected through structured questionnaires from a sample of 114 respondents and analysed using structural equation modelling facilitated by SMARTPLS software. Findings The research used an integrated TAM-TTF model. The TTF construct was significantly affected by connectivity, lifestyle and healthcare factors. The model accounts for 76.4% of the variance in behavioural intention and 93.4% in TTF. Research limitations/implications The primary limitation of this study is the use of convenience sampling, which may limit the generalizability of the findings. Furthermore, the research does not explore additional external factors such as cost, data privacy concerns or cost-benefit ratios, which could impact adoption. Practical implications The findings offer practical lessons for IoT device manufacturers and technology developers. Focusing on the alignment of IoT devices with user requirements, particularly in terms of connectivity, lifestyle integration and health-care needs, can enhance adoption. Manufacturers of health-care IoT devices should prioritize perceived usefulness (health outcomes, real-time monitoring) over ease of use, as utility drives adoption more strongly. Social implications This research highlights the potential of IoT devices to transform health-care delivery, especially in emerging markets like India. The integration of IoT into health care can improve patient monitoring, enhance medical prognosis and reduce health-care costs, thus contributing to improved public health outcomes. Originality/value This study offers a novel integration of the TAM and TTF models in the context of IoT adoption in India. It identifies key factors – connectivity, lifestyle and health care – that influence user perceptions and adoption of IoT wearable devices. The research contributes to the growing body of knowledge on technology adoption in emerging markets and provides valuable insights for future innovations in IoT health-care devices.