Navigating the Trade-Off: An Extended UTAUT2 Model for Smart Wearable Adoption Among Millennials in the Age of Personalization and Privacy Concerns

Abstract

Smart wearable technologies are becoming an integral part of daily life, yet the key factors influencing adoption decisions among consumers remain underexamined. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the paper analyses smart wearable adaptation by considering the inclusion of Perceived Personalization as a fundamental advantage and Privacy Risk as a fundamental cost, with the test of Trust as the psychological process behind the personalization-privacy trade-off. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyze survey data obtained on 385 millennial smart wearable users. The results are partially in favor of UTAUT2. Behavioral intention is greatly increased by Effort Expectancy, Hedonic Motivation, Price Value and Social Influence but not by Performance Expectancy and Habit, which implies the possibility of functional utility being considered as a base expectation. Perceived Personalization has a positive and significant impact on behavioral intention and a positive, but not significant impact on Trust, whereas Privacy Risk has a negative impact on Trust. The model accounts 44 percent of the variation in behavioral intention. The research contributes to the literature on technology adoption by rebranding trust as an antecedent instead of a proximal factor influencing adoption in the smart wearable scenario and provides practical implications on balancing personalization and privacySmart wearable technologies are becoming an integral part of daily life, yet the key factors influencing adoption decisions among consumers remain underexamined. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the paper analyses smart wearable adaptation by considering the inclusion of Perceived Personalization as a fundamental advantage and Privacy Risk as a fundamental cost, with the test of Trust as the psychological process behind the personalization-privacy trade-off. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyze survey data obtained on 385 millennial smart wearable users. The results are partially in favor of UTAUT2. Behavioral intention is greatly increased by Effort Expectancy, Hedonic Motivation, Price Value and Social Influence but not by Performance Expectancy and Habit, which implies the possibility of functional utility being considered as a base expectation. Perceived Personalization has a positive and significant impact on behavioral intention and a positive, but not significant impact on Trust, whereas Privacy Risk has a negative impact on Trust. The model accounts 44 percent of the variation in behavioral intention. The research contributes to the literature on technology adoption by rebranding trust as an antecedent instead of a proximal factor influencing adoption in the smart wearable scenario and provides practical implications on balancing personalization and privacy