Mobile payments provide several benefits, for consumers and merchants alike. Yet, on a worldwide scale their usage is still low. Also, the barriers to mobile payment usage are still a rather unexplored topic in the literature, which is instead focused on adoption behavior. Accordingly, our objective is to investigate the factors that hinder, respectively, mobile payment usage and intention to use by consumers. The theoretical framework for our analysis integrates the Technology Readiness Index (TRI) into the Innovation Resistance Theory (IRT). To empirically assess the model, we gathered data on mobile payment usage in Italy through a web-based survey among 1,795 consumers. For the full sample, we find that the impact of the IRT barriers is different for actual use and behavioral intention to use. Also, and most importantly, once we segment consumers based on their TRI, we find yet other results. Specifically, the impact of the IRT barriers is different across the proposed clusters. This confirms that cluster analysis does indeed add value to the IRT.

Can cluster analysis enrich the innovation resistance theory? The case of mobile payment usage in Italy

Spinelli, Giulia;Gastaldi, Luca;
2024-01-01

Abstract

Mobile payments provide several benefits, for consumers and merchants alike. Yet, on a worldwide scale their usage is still low. Also, the barriers to mobile payment usage are still a rather unexplored topic in the literature, which is instead focused on adoption behavior. Accordingly, our objective is to investigate the factors that hinder, respectively, mobile payment usage and intention to use by consumers. The theoretical framework for our analysis integrates the Technology Readiness Index (TRI) into the Innovation Resistance Theory (IRT). To empirically assess the model, we gathered data on mobile payment usage in Italy through a web-based survey among 1,795 consumers. For the full sample, we find that the impact of the IRT barriers is different for actual use and behavioral intention to use. Also, and most importantly, once we segment consumers based on their TRI, we find yet other results. Specifically, the impact of the IRT barriers is different across the proposed clusters. This confirms that cluster analysis does indeed add value to the IRT.
2024
Mobile payments
Innovation Resistance Theory
Technology Readiness Index
Cluster analysis
Consumer behavior
Italy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1278213
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