What question did this study set out to answer?

The study aims to identify factors that contribute to technological anxiety and affect customers' intentions to discontinue using AI-supported banking services.

January 22, 2026

Investigating the factors raising customers concern to continue using AI-supported customer care services of banks: a hybrid SEM-ANN approach

Puntos clave

The study aims to identify factors that contribute to technological anxiety and affect customers' intentions to discontinue using AI-supported banking services.
Quantitative research approach using purposive sampling
363 valid responses collected from Bangladesh
Comparative analysis using artificial neural networks (ANN) and partial least squares structural equation modeling (PLS-SEM)
Regression analysis to confirm hypotheses
Sensitivity analysis to identify key factors influencing customer concerns
Lack of empathy identified as the most influential factor in technological anxiety at 100%
Distrust and irrelevant information were significant concerns at 52.1% and 42%, respectively
Customer concerns about AI chatbot usage strongly impacted discontinuance intentions, with a 100% influence
Technological anxiety also played a significant role in discontinuance intentions at 67.6%
The findings indicate that enhancing empathy and trust can improve customer experiences with AI in banking.

Resumen

Purpose This study aims to examine factors that influence technological anxiety, usage concerns and subsequently discontinuance use intentions among banking customers, using the stressor–strain–outcome (SSO) framework. Design/methodology/approach Using a quantitative research approach and purposive sampling, 363 valid responses were collected from major cities in Bangladesh. A comparative analysis employing artificial neural networks (ANN) and partial least squares structural equation modeling (PLS-SEM) was conducted to enhance predictive accuracy, offering a robust and comprehensive understanding of the data. Findings Regression analysis using PLS-SEM confirmed that all proposed hypotheses were statistically significant. Sensitivity analysis with ANN identified lack of empathy as the most influential factor in technological anxiety (100%), followed by distrust (52.1%), irrelevant information (42%), privacy concerns (33.1%), perceived non-personalization cost (28.8%) and biased information (18.5%) (Model-A). Lack of empathy also emerged as the primary driver of customer concerns regarding artificial intelligence (AI) chatbot usage (100%), followed by technological anxiety (79.7%) (Model-B). Additionally, customer concerns about using AI chatbots (100%) had the strongest impact on discontinuance use intentions, with distrust (67.7%) and technological anxiety (67.6%) also playing significant roles (Model-C). Practical implications This study highlights the importance of empathy, relevant and unbiased information, personalization, privacy and trust in AI chatbots for banking. Banks can leverage these insights to enhance AI technology and alleviate customer anxiety, while governments can support policies that promote user-friendly digital banking services. Originality/value This study applies the SSO theory to examine the negative factors influencing behavior toward AI service technology. It investigates how technological anxiety and customer concerns affect discontinuance use intentions, aiming to uncover overlooked negative perceptions of AI-supported customer services in banking.

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