This research aims to determine the key antecedent factors in consumers\u27 adoption of and their intention to recommend smartwatch wearable technology. The proposed research model combines the current technology acceptance and innovation diffusion theories with perceived aesthetic and perceived privacy risk to explain individuals\u27 smartwatch adoption and subsequent recommendation to other people. Based on a sample of 299 completed individual online surveys, the research employed partial least squares (a variance-based analysis method) for the model and hypotheses testing. The results showed some similarities as well as differences from the previous literature. The study found that performance expectancy, habit, and perceived aesthetic were the main predictors of smartwatch adoption. Compatibility was the antecedent factor of performance expectancy, and innovativeness directly influenced user adoption and effort expectancy. Consequently, user smartwatch adoption usually led to recommendation
