Investigating the drivers of internet banking adoption decision

Spiros P. Gounaris · Christos Koritos

160 citations0/0 files storedInternational Journal of Bank Marketing

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Technology Adoption and User Behaviour FinTech, Crowdfunding, Digital Finance Health, Technology, Consumer Behavior

Abstract

Purpose The paper seeks to compare, through empirical evidence, two widely adopted models (the Technology Acceptance Model (TAM) and the Diffusion of Innovations (DoI) model) to an underutilized one (Perceived Characteristics of the Innovation) in order to examine which is better in predicting consumer adoption of internet banking (IB), while investigating innovation attributes vis‐à‐vis other important predictors of adoption of innovations, such as consumer personal characteristics. Design/methodology/approach The data derive from both users and non‐users of IB through a web survey. The paper assesses the psychometric properties of the measures through confirmatory factor analysis and then employs logistic regression analysis in order to assess and compare the ability of the models to accurately predict consumer adoption of IB. Findings The paper finds that PCI performed significantly better than TAM and DoI in predicting consumer adoption of IB, whereas the addition of consumer demographics and psychographics further improved the predictive ability of the overall logit model. Research limitations/implications Limitations of the study include the non‐random nature of the IB non‐users sample, and the fact that this was a study of a single shopping context (i.e. banking). Non‐usability innovation characteristics are important predictors of consumer adoption of technologically based innovations. Bank managers should reconsider their segmentation and targeting strategies in the light of more refined as well as new segmentation criteria. Originality/value The PCI model has never been examined within online contexts. The paper also incorporates other non‐usability types of characteristics (i.e. social, psychological) into TAM and DoI, and identifies the moderating role of shopping context, between innovation characteristics and decision to adopt.

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2003User Acceptance of Information Technology: Toward A Unified View1 2019Diffusion of Innovations 1 1975Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research 1989User Acceptance of Computer Technology: A Comparison of Two Theoretical Models 2000A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

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2014Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service 2017The mediating role of hedonic motivation on the relationship between adoption of e-banking and its determinants 2011Cross-cultural examination of online shopping behavior: A comparison of Norway, Germany, and the United States 2014Innovation adoption attributes: a review and synthesis of research findings

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