Exploring the determinants of the user experience in P2P payment systems in Spain: a text mining approach
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Perea-Khalifi, David
Irimia-Diéguez, Ana I.
Palos-Sanchez, Pedro
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SpringerOpen
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Abstract
Purpose: This study aims to identify which determinants are responsible for impacting
the user experience of three peer-to-peer (P2P) payment services in the Spanish
market.
Design/methodology/approach: A sample of all online reviews (n = 16,048) published
in Google Play of three paytech apps—Bizum, Twyp, and Verse—was analyzed
using text mining and sentiment analysis.
Findings: A holistic interpretation of the seed terms included in each aspect allowed
to label them based on the preferences expressed by paytech app users in their
reviews. Six latent aspects were identified: ease of use, usefulness, perceived value, performance
expectancy, perceived quality, and user experience. In addition, the results
of the analysis suggest a positivity bias in the online reviews of fintech P2P app users.
Our results also show that online reviews of apps associated with banks or financial
institutions, such as Bizum (to a greater extent) or Twyp, show more negative emotions,
whereas independent apps (Verse) show more positive emotions. Moreover, the most
critical users are those of unidentified gender, while women remain in a more neutral
position, and men tend to express their opinions more positively regarding P2P payment
apps.
Practical implications: Paytech providers should analyze the problems faced by users
immediately after an encounter. By applying text mining analysis, service providers
can gain efficiency in understanding user sentiments and emotions without tedious
and time-consuming reviews.
Originality/value: This is a pioneering study on peer-to-peer (P2P) mobile payment
systems from the user’s perspective because it investigates the emotions and sentiments
that users convey through bank reviews.
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Perea-Khalifi, D., Irimia-Diéguez, A.I. & Palos-Sánchez, P. Exploring the determinants of the user experience in P2P payment systems in Spain: a text mining approach. Financ Innov 10, 2 (2024). https://doi.org/10.1186/s40854-023-00496-0
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Except where otherwised noted, this item's license is described as Atribución 4.0 Internacional







