Exploring the factors influencing the adoption of smart innovations: An integrated model of consumer behavior and purchase intention

Abstract

The use of smart technology has become an important topic in research on the Internet of Things (IoT), where consumer acceptance plays a key role in market success. This study explores the factors that affect the adoption of smart technologies and how these factors influence consumers’ intentions to purchase. The research is based on the Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), and Consumer Perceived Innovativeness (CPI), and it develops and tests an integrated framework. A quantitative survey was carried out with 101 participants, and the data were analyzed using structural equation modeling. The results show that perceived usefulness (PU), perceived ease of use (PEoU), compatibility, and consumer-perceived innovativeness increase the intention to purchase smart technologies, while perceived cost reduces this intention. Observability and trialability also have important indirect effects through PU and PEoU. This study adds to the existing research by presenting a comprehensive model for understanding consumer behavior in adopting smart technologies and offers practical recommendations for businesses to improve consumer engagement and adoption.