A unified perspective on the factors influencing consumer acceptance of internet of things technology
By Lingling Gao, Xuesong Bai. 2014
472 citations recorded by the source corpus.
Purpose – With recent advances in internet technologies, internet of things (IoT) technology is having an increasing impact on our daily lives, and beginning to offer interesting and advantageous new services. The current research aims to develop and test an integrative model of factors determining consumers' acceptance of IoT technology. Design/methodology/approach – Based on technology acceptance model (TAM), the authors proposed an IoT acceptance model that consists of three technology factors (perceived usefulness, perceived ease of use, and trust); one social context factor (social influence); and two individual user characteristics (perceived enjoyment and perceived behavioral control). Data from 368 Chinese consumers were used to test the research model through the use of structural equation modeling. Findings – The results showed particularly strong support for the effects of perceived usefulness, perceived ease of use, social influence, perceived enjoyment, and perceived behavioral control. Howev...
Subfields: Information Systems and Management, Organizational Behavior and Human Resource Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/63226360da57c2934b51f4f76b53a03bfce98151
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In Information Systems and Management
In Organizational Behavior and Human Resource Management
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Citations in the corpus
- Machine Learning Based Intrusion Detection Systems for IoT Applications (2019, background): “These factors prevent global adoption of IoT, consequently slowing down its growth [30].”
- Point of adoption and beyond. Initial trust and mobile-payment continuation intention (2020, unknown): “Many other prior studies have invoked the benefits dimensions of the ISS model for mobile services, health infomediaries, and online shopping (e.g., Gao and Bai, 2014).”
- Understanding the Blockchain technology adoption in supply chains-Indian context (2018, background): “This is in line with most of the other studies (Amoako-Gyampah and Salam 2004; Lee 2009; Shih, Chen, and Chen 2012; Gao and Bai 2014; Kumpajaya and Dhewanto 2015; Rajan and Baral 2015; Bröhl et al. 2016).”