Segmenting the non‐adopter category in the diffusion of internet banking

For a new technology‐based product or service at an early stage of diffusion, it is likely that only a small subset of consumers have adopted it. When non‐adopters still comprise the majority of the target populations, describing all non‐adopters as a homogeneous population may be inaccurate and inappropriate. It is important to be able to identify differences, not only between adopters and non‐adopters, but also among non‐adopters, the latter providing a means of identifying the consumer segments likely to be profitable in the future. The first objective of this paper is to demonstrate the appropriateness of further segmenting the non‐adopter category based on motivations (intentions) to adopt internet‐banking by those who are “persistent non‐adopters” and those who are likely “prospective adopters”. The second objective of this paper is to further the understanding of the adoption process of internet banking by examining a range of diffusion factors that affect consumers’ adoption behavior.

This study identifies three adopter segments, persistent non‐adopters, prospective adopters, and adopters, in the diffusion of internet banking services based on individuals’ intentions to adopt internet banking and their actual adoption behavior, using the data collected by the Graphic, Visualization, & Usability Center and Georgia Tech Research Corporation. Selective adoption factors (i.e. perceived attribute importance of internet banking, perceived risk, compatibility with existing banking services, and compatibility with the internet and computer technologies) were used to predict individuals’ adoption status through multinomial logit modeling.

It was found that further segmenting the non‐adopter category revealed meaningful differences between prospective adopters and persistent non‐adopters. This study reflects that the previous research practice of bifurcating adoption categories (adoption versus non‐adoption) is oversimplified. The two qualitatively different segments, prospective adopters and persistent non‐adopters, should not be lumped together in the diffusion of internet banking.

This study provides comparison profiles of the three adopter categories and discusses marketing implications for segmentation.