TY - JOUR
T1 - Exploring the Moderating Effect of Price on the Relationship between Intention and Use of Voice Assistants
AU - Usina-Bascones, Gabriel
AU - Carrion-Bosquez, Nelson
AU - Veas-Gonzalez, Ivan
AU - Garcia-Umana, Andres
AU - Ulloa-Meneses, Luis
AU - Guerra-Regalado, Wilson
AU - Velasco-Donoso, Andrea
AU - Samaniego-Arias, Mayra
N1 - Publisher Copyright:
© IEEE. 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This study aimed to identify the moderating effect of price on the relationship between usage intention and the actual use of voice assistants. A quantitative approach was adopted, with a correlational scope and non-experimental, cross-sectional design. The sample consisted of 329 participants from Generations X, Y, and Z residing in various cities across Ecuador, selected through non-probability convenience sampling. Data were collected using a self-administered questionnaire comprising 26 items, measured on a five-point Likert scale. The questions were adapted from previously validated studies in the field of technology acceptance. Reliability tests, confirmatory factor analysis, and structural equation modeling were conducted using SmartPLS 4 software. The results showed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influenced usage intention, which in turn had a direct impact on the actual use of voice assistants. Moreover, price positively moderates this relationship. Together, these findings offer an expanded theoretical model that addresses the previous gaps in the literature, providing a more comprehensive view of consumer behavior toward AI-based technologies.
AB - This study aimed to identify the moderating effect of price on the relationship between usage intention and the actual use of voice assistants. A quantitative approach was adopted, with a correlational scope and non-experimental, cross-sectional design. The sample consisted of 329 participants from Generations X, Y, and Z residing in various cities across Ecuador, selected through non-probability convenience sampling. Data were collected using a self-administered questionnaire comprising 26 items, measured on a five-point Likert scale. The questions were adapted from previously validated studies in the field of technology acceptance. Reliability tests, confirmatory factor analysis, and structural equation modeling were conducted using SmartPLS 4 software. The results showed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influenced usage intention, which in turn had a direct impact on the actual use of voice assistants. Moreover, price positively moderates this relationship. Together, these findings offer an expanded theoretical model that addresses the previous gaps in the literature, providing a more comprehensive view of consumer behavior toward AI-based technologies.
KW - Artificial intelligence
KW - Ecuadorian consumers
KW - UTAUT
KW - voice assistants
UR - https://doi.org/10.1109/ACCESS.2025.3598009
U2 - 10.1109/ACCESS.2025.3598009
DO - 10.1109/ACCESS.2025.3598009
M3 - Article
AN - SCOPUS:105013332388
SN - 2169-3536
VL - 13
SP - 143800
EP - 143812
JO - IEEE Access
JF - IEEE Access
ER -