Journal Press India^®

Author Details ( * ) denotes Corresponding author

This study examines the factors influencing the adoption of banking chatbots among mobile banking customers of three major Indian banks—State Bank of India (SBI), ICICI Bank, and HDFC Bank—using the Technology Acceptance Model (TAM) and Necessary Condition Analysis (NCA). Data from 300 chatbot users, collected via street intercepts in urban and semi-urban India from January to March 2025, were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and NCA. Results confirm that Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) significantly drive Behavioral Intention (BINT), which in turn predicts Customer Adoption (CA). NCA reveals BINT and PEOU as necessary and sufficient conditions, while PU is necessary but not sufficient beyond a threshold. Mediation analyses highlight partial roles for BINT and PEOU. Findings align with prior research while extending TAM to the Indian context, offering practical insights for enhancing chatbot design and adoption. Limitations include the cross-sectional design and focus on three banks, suggesting avenues for longitudinal and cross-cultural research.

Keywords

Banking chatbots; Technology acceptance model; Necessary condition analysis; Mobile banking; India

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