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Identifying barriers of financial app usage and their impact on negative emotions, customer ratings and recommendation intention: a text-mining based approach

Sneha Das (FORE School of Management, New Delhi, India)
Arghya Ray (International Management Institute Kolkata, Kolkata, India)

Asia-Pacific Journal of Business Administration

ISSN: 1757-4323

Article publication date: 31 October 2024

122

Abstract

Purpose

Limited studies in the mobile payment segment have attempted at understanding the factors that resist customers from using financial apps or mobile payment services (MPSs). This study aims at identifying the barriers from online customer reviews and examine how these barriers affect customers’ negative emotions (anger, fear, sadness), customer ratings and recommendation intentions.

Design/methodology/approach

This study, divided into three phases, has adopted a text-mining based mixed-method approach on 14,043 reviews present in Google PlayStore or App Store pages about financial apps used in India.

Findings

Phase 1 identified barriers like, “bad user experience”, “UPI failure”, “trust issues”, “transaction delays” from the reviews. Phase 2 found that “bad user experience” and “UPI failure” trigger both “anger” and “sadness”. “Transaction delays” and “money lost in transaction” stimulate “fear”. From the IRT stance, in Phase 3 this study has found that barriers like, “transaction error”, “UPI failure” (usage), “bad user experience” (image) and “trust issues” (tradition) have a significant negative impact on both customer ratings and recommendation intention.

Originality/value

The current study contributes to the existing literature on MPSs by identifying barriers from user generated content. Additionally, this study has also examined the impact of the barriers on customers’ negative emotions and recommendation intention.

Keywords

Citation

Das, S. and Ray, A. (2024), "Identifying barriers of financial app usage and their impact on negative emotions, customer ratings and recommendation intention: a text-mining based approach", Asia-Pacific Journal of Business Administration, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/APJBA-10-2023-0522

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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