Behavioural Intention to the Use of Mobile Banking in Kerala: An Application of Extended Classical Technology Acceptance Model
T. G. Saji, Deepa Paul
Abstract
T. G. Saji, Deepa Paul
Abstract
This research, using an extended version of classical technology acceptance model (TAM), investigates the factors influencing the adoption behaviour of mobile technology in banking. Survey data on 214 banking customers in Kerala were analysed under a structural equation modeling (SEM) framework and the results confirm the usefulness of TAM in predicting mobile banking adoption behaviour. The exogenous constructs from the original TAM, perceived usefulness (PU), and perceived ease of use (PEU) along with two additional constructs in the extended model, perceived credibility (PC) and perceived self-efficacy (PSE), emerged out as significant antecedents of the behavioural intention of customers, especially of an educated youth, towards the use of mobile technology in banking. Findings ultimately suggest that accurate and consistent identification of customers’ propensity to adopt technology banking provides strategic map to banks from emerging markets to grow in underserved markets, achieve omni-channel presence, and disrupt value chain components.
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This research, using an extended version of classical technology acceptance model (TAM), investigates the factors influencing the adoption behaviour of mobile technology in banking. Survey data on 214 banking customers in Kerala were analysed under a structural equation modeling (SEM) framework and the results confirm the usefulness of TAM in predicting mobile banking adoption behaviour. The exogenous constructs from the original TAM, perceived usefulness (PU), and perceived ease of use (PEU) along with two additional constructs in the extended model, perceived credibility (PC) and perceived self-efficacy (PSE), emerged out as significant antecedents of the behavioural intention of customers, especially of an educated youth, towards the use of mobile technology in banking. Findings ultimately suggest that accurate and consistent identification of customers’ propensity to adopt technology banking provides strategic map to banks from emerging markets to grow in underserved markets, achieve omni-channel presence, and disrupt value chain components.
Key concepts: Technology acceptance model, Mobile banking, Structural equation modeling, Usability, Credibility, Business, Marketing, Value (mathematics)