Exploring the Factors Influencing Continuance Intention to Use AI-enabled Smart Wearable Devices: A Stimulus-Organism-Response Perspective with Moderating Role of Technology Anxiety

With the rapid development of artificial intelligence (AI) technology, users' continuance intention to use AI-enabled smart wearable devices (AIWDs) has become an important research topic. This study, based on the Stimulus-Organism-Response (S-O-R) framework, constructs and validates a comprehensive model aimed at exploring the impact mechanism of the intelligent characteristics of AIWDs on users' continuance intention. The study focuses on analyzing the complex relationships between perceived intelligence, trust, attitude, satisfaction, and technology anxiety. By conducting partial least squares (PLS) structural equation modeling analysis on data from 562 respondents, the study tests the research hypotheses. The results show that perceived intelligence significantly enhances users' trust, satisfaction, and attitude, which play important mediating roles in the effect of perceived intelligence on continuance intention. At the same time, technology anxiety has a significant negative moderating effect on the relationship between satisfaction and continuance intention. This research not only expands the theoretical understanding of user behavior with AI-driven smart wearable devices but also provides practical guidance for developers and marketers on optimizing user experience, improving user engagement, and refining marketing strategies.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-24
DOI
https://doi.org/10.52783/jisem.v10i24s.3877
Citations
1
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
4.17
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article

Exploring the Factors Influencing Continuance Intention to Use AI-enabled Smart Wearable Devices: A Stimulus-Organism-Response Perspective with Moderating Role of Technology Anxiety

Feng Gao
1 citations
Journal of Information Systems Engineering & Management
Technology Adoption and User Behaviour
4.17
article

Exploring the Factors Influencing Continuance Intention to Use AI-enabled Smart Wearable Devices: A Stimulus-Organism-Response Perspective with Moderating Role of Technology Anxiety

Feng Gao
article en
1 citations

Abstract

With the rapid development of artificial intelligence (AI) technology, users' continuance intention to use AI-enabled smart wearable devices (AIWDs) has become an important research topic. This study, based on the Stimulus-Organism-Response (S-O-R) framework, constructs and validates a comprehensive model aimed at exploring the impact mechanism of the intelligent characteristics of AIWDs on users' continuance intention. The study focuses on analyzing the complex relationships between perceived intelligence, trust, attitude, satisfaction, and technology anxiety. By conducting partial least squares (PLS) structural equation modeling analysis on data from 562 respondents, the study tests the research hypotheses. The results show that perceived intelligence significantly enhances users' trust, satisfaction, and attitude, which play important mediating roles in the effect of perceived intelligence on continuance intention. At the same time, technology anxiety has a significant negative moderating effect on the relationship between satisfaction and continuance intention. This research not only expands the theoretical understanding of user behavior with AI-driven smart wearable devices but also provides practical guidance for developers and marketers on optimizing user experience, improving user engagement, and refining marketing strategies.

Journal of Information Systems Engineering & ManagementVol. 10(24s)
Openalex Percentile: Top 7%
Technology Adoption and User Behaviour
4.17
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Exploring the Factors Influencing Continuance Intention to Use AI-enabled Smart Wearable Devices: A Stimulus-Organism-Response Perspective with Moderating Role of Technology Anxiety — Feng Gao · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS