Predictive Modeling of Wearable Technology Adoption for Advancing Sustainability: An AI-Driven Approach

Abstract

This research aims to identify the essential background factors that influence consumers' perception of the adoption of wearable technology. Wearable technology is becoming popular across the world. Changing customer priorities and advancements in IoT accelerated the use of wearables. Smartwatches like devices with innovative features benefiting people for health and fitness monitoring. Consumers have started exploring it and the researcher is trying to assess whether wearable technology has a strong impact. Wearable technology is a powerful tool for increasing awareness about health in general. These devices have capabilities that enable evaluation and tracking of health and daily routine. The study explored the main predictors of smartwatch adoption using the Technology Acceptance Model (TAM) to analyze the behavioral intention. Based on an online survey of 90 individuals of different age groups, two hypothesis were statistically supported and show that perceived ease of use positively influences the adoption of wearable.  Perceived usefulness supports that consumers would like to use the technology if it is innovative and useful and it overall influences behavioral intention.  Hypothesis testing in the study used a variance-based analysis method. The research also revealed that the use of wearable technology in conjunction with health solutions helps to maintain quality of life. Wearables can reduce the healthcare burden associated with sedentary lifestyles. A healthier population can lead to lower healthcare costs and it promotes health and wellness that can indirectly contribute to a sustainable society. The research found this technology can be considered a current and next-generation technology.