Extending Technology Continuance Theory: Investigating the Impact of AI Characteristics on Continuance Intention in AI Enabled Mobile Banking

Purpose–This study seeks to address the gap in research regarding the influence of artificial intelligence (AI) characteristics on users' continuance intention (CI) within mobile banking contexts. Despite the widespread adoption of AI as a transformative technology in mobile banking, there is limited systematic research employing Technology Continuance Theory (TCT) to examine the effect of AI features on users' CI towards AI-powered mobile banking applications. This research explores the roles of perceived intelligence and perceived anthropomorphism as key AI characteristics and their mechanisms in shaping CI. Design/methodology/approach–A quantitative methodology, using a cross-sectional survey design, was applied to collect data from 395 mobile banking users via structured questionnaires. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses. The model examines how perceived intelligence and anthropomorphism, mediated by confirmation, perceived usefulness, and perceived ease of use, influence user satisfaction (SAT) and attitudes, which ultimately enhance CI towards mobile banking. Additionally, the moderating effect of technology anxiety on the SAT-CI relationship was also tested. Findings–The results demonstrate that perceived intelligence and anthropomorphism positively impact users' confirmation, perceived usefulness, and ease of use, thereby strengthening SAT and fostering a positive attitude, which significantly boosts CI towards mobile banking applications. Additionally, perceived usefulness has a direct and substantial effect on CI. Technology anxiety was found to negatively moderate the SAT-CI relationship, with users exhibiting higher anxiety showing a weaker connection between SAT and CI. Research limitations/implications–The study is limited to a specific geographical area, which may limit the generalizability of the findings. Future research could replicate this study in other regions. Furthermore, the cross-sectional nature of the data restricts causal inferences, suggesting the need for longitudinal studies to validate the model. This research offers novel insights into the role of AI characteristics in influencing CI, which could guide future studies and inform the design of mobile banking services. Originality/value–This research is one of the first to systematically explore the impact of perceived intelligence and anthropomorphism within the TCT framework in mobile banking. It contributes to the theoretical understanding of mobile banking continuance intention and provides practical guidance for developers of AI-based applications aimed at improving CI and SAT. The findings highlight the importance of AI characteristics in enhancing users' satisfaction and continuance intention in mobile banking.

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Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-20
DOI
https://doi.org/10.52783/jisem.v10i3.6467
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Extending Technology Continuance Theory: Investigating the Impact of AI Characteristics on Continuance Intention in AI Enabled Mobile Banking

Shaofu Huang
Journal of Information Systems Engineering & Management
Big Data and Business Intelligence
article

Extending Technology Continuance Theory: Investigating the Impact of AI Characteristics on Continuance Intention in AI Enabled Mobile Banking

Shaofu Huang
article en

Abstract

Purpose–This study seeks to address the gap in research regarding the influence of artificial intelligence (AI) characteristics on users' continuance intention (CI) within mobile banking contexts. Despite the widespread adoption of AI as a transformative technology in mobile banking, there is limited systematic research employing Technology Continuance Theory (TCT) to examine the effect of AI features on users' CI towards AI-powered mobile banking applications. This research explores the roles of perceived intelligence and perceived anthropomorphism as key AI characteristics and their mechanisms in shaping CI. Design/methodology/approach–A quantitative methodology, using a cross-sectional survey design, was applied to collect data from 395 mobile banking users via structured questionnaires. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses. The model examines how perceived intelligence and anthropomorphism, mediated by confirmation, perceived usefulness, and perceived ease of use, influence user satisfaction (SAT) and attitudes, which ultimately enhance CI towards mobile banking. Additionally, the moderating effect of technology anxiety on the SAT-CI relationship was also tested. Findings–The results demonstrate that perceived intelligence and anthropomorphism positively impact users' confirmation, perceived usefulness, and ease of use, thereby strengthening SAT and fostering a positive attitude, which significantly boosts CI towards mobile banking applications. Additionally, perceived usefulness has a direct and substantial effect on CI. Technology anxiety was found to negatively moderate the SAT-CI relationship, with users exhibiting higher anxiety showing a weaker connection between SAT and CI. Research limitations/implications–The study is limited to a specific geographical area, which may limit the generalizability of the findings. Future research could replicate this study in other regions. Furthermore, the cross-sectional nature of the data restricts causal inferences, suggesting the need for longitudinal studies to validate the model. This research offers novel insights into the role of AI characteristics in influencing CI, which could guide future studies and inform the design of mobile banking services. Originality/value–This research is one of the first to systematically explore the impact of perceived intelligence and anthropomorphism within the TCT framework in mobile banking. It contributes to the theoretical understanding of mobile banking continuance intention and provides practical guidance for developers of AI-based applications aimed at improving CI and SAT. The findings highlight the importance of AI characteristics in enhancing users' satisfaction and continuance intention in mobile banking.

Journal of Information Systems Engineering & ManagementVol. 10(3)
Openalex Percentile: Top 88%
Big Data and Business Intelligence
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