PREDICTING USER ADOPTION OF DIGITAL PAYMENT PLATFORMS: A QUANTITATIVE ANALYSIS BASED ON UTAUT

This study investigates the influence of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Condition on Behavioral Intention to use the OVO digital payment system in Indonesia. Utilizing a quantitative approach with regression and T-test analysis, data were collected from 150 respondents representing various age groups and genders. The analysis reveals that all four independent variables significantly and positively affect users’ behavioral intention to adopt and continue using OVO. Performance Expectancy has the strongest influence, followed by Facilitating Condition, Social Influence, and Effort Expectancy. These findings confirm that users are more likely to adopt OVO when they perceive it as useful, easy to use, socially supported, and adequately facilitated by infrastructure. The study provides important implications for fintech developers, policymakers, and marketers to enhance user adoption through targeted strategies tailored to these key determinants. Keywords: Behavioral Intention, Digital Payment System, Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition

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Publication Details

Journal
KINDAI
Published
2025-08-01
DOI
https://doi.org/10.35972/kindai.v21i2.2437
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

PREDICTING USER ADOPTION OF DIGITAL PAYMENT PLATFORMS: A QUANTITATIVE ANALYSIS BASED ON UTAUT

M. Andri Radiany
KINDAI
Technology Adoption and User Behaviour
article

PREDICTING USER ADOPTION OF DIGITAL PAYMENT PLATFORMS: A QUANTITATIVE ANALYSIS BASED ON UTAUT

M. Andri Radiany
article en

Abstract

This study investigates the influence of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Condition on Behavioral Intention to use the OVO digital payment system in Indonesia. Utilizing a quantitative approach with regression and T-test analysis, data were collected from 150 respondents representing various age groups and genders. The analysis reveals that all four independent variables significantly and positively affect users’ behavioral intention to adopt and continue using OVO. Performance Expectancy has the strongest influence, followed by Facilitating Condition, Social Influence, and Effort Expectancy. These findings confirm that users are more likely to adopt OVO when they perceive it as useful, easy to use, socially supported, and adequately facilitated by infrastructure. The study provides important implications for fintech developers, policymakers, and marketers to enhance user adoption through targeted strategies tailored to these key determinants. Keywords: Behavioral Intention, Digital Payment System, Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition

KINDAIVol. 21(2)
Universitas Patria Artha (ID)
Openalex Percentile: Top 80%
Technology Adoption and User Behaviour
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PREDICTING USER ADOPTION OF DIGITAL PAYMENT PLATFORMS: A QUANTITATIVE ANALYSIS BASED ON UTAUT — M. Andri Radiany · KINDAI (2025) | TGRS Research Map | TGRS