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Understanding diffusion of information systems-based services: evidence from mobile banking services

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Purpose

The Bass model is widely used in the literature to capture the diffusion of innovations and shows excellent predictive power in the context of durable goods. However, the model's efficacy fades when services are the target of analysis. Services that users adopt and subsequently utilize regularly are regarded as a continuous process that entails the possibility of dis-adoption and re-adoption. These aspects are not accounted for in the traditional Bass model. Thus, this study extends the Bass model to information system (IS)-based services by taking into account the unique nature of service adoption: the possibility of dis-adoption and re-adoption.

Design/methodology/approach

The proposed hypotheses were empirically tested using a longitudinal study of mobile service usage over 18 months. The longitudinal design provides a stronger position than the typical cross-sectional survey to understand the dynamics and infer causality.

Findings

Results show that the inclusion of the dis-adoption and re-adoption rates in the Bass model significantly improves the explanatory power over the traditional Bass model.

Originality/value

Consumption of services delivered through IS has exponentially increased. However, understanding on the diffusion pattern of IS-based services is limited. Our study is the first to examine the effect of dis-adoption and re-adoption together in the innovation diffusion process. The study offers significant implications for researchers and practitioners. The extended Bass model can help service firms develop an accurate prediction about the number of adopters at different periods of time.
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Keywords: Diffusion model; Dis-adoption; Mobile banking; Re-adoption; Service diffusion

Document Type: Research Article

Affiliations: 1: Department of Information Systems, Coles College of Business, Kennesaw State University, Kennesaw, Georgia, USA 2: Department of Information Systems, College of Business, City University of Hong Kong, Kowloon, Hong Kong SAR, China

Publication date: April 10, 2020

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