Factors influencing usage and loyalty for payment app customers in Saudi Arabia
Year: 2025
Type: article
Study design: Observational Study
Abstract: PURPOSE: The present study is intended to determine the factors influencing the acceptance and loyalty towards payment of mobile applications in the Kingdom of Saudi Arabia, focusing on perceived convenience, security, compliance, and trust. DESIGN/METHODOLOGY/APPROACH: This research study adopted a quantitative method by using a questionnaire and targeting mobile payment app users as well as business entrepreneurs in Saudi Arabia. The survey yielded 290 fully completed questionnaires from the participants. Partial least squares equation modeling (PLS-SEM) was used to analyze the data. FINDINGS: The present study highlights that users' trust in mobile payment applications is primarily influenced by their perceptions of convenience and security, significantly affecting customer loyalty and app usage frequency. Compliance was found to have a less pronounced impact on trust. RESEARCH LIMITATIONS/IMPLICATIONS: The study acknowledges the need for a diverse methodological framework in future research, including qualitative methods, to deepen understanding. PRACTICAL IMPLICATIONS: Insights are provided not only for FinTech companies but also for the policymakers, emphasizing the importance of user-centric design and supportive regulatory environments. SOCIAL IMPLICATIONS: The study's findings may lead to the progress of digital financial services that will allow parallel users' security, convenience, and trust needs, contributing to the broader acceptance and sustainability of these technologies. ORIGINALITY: This study offers a unique perspective by integrating technological advancements and demographic factors specific to Saudi Arabia, distinguishing it from prior research. It provides fresh insights into how convenience, security, and compliance influence user trust and loyalty within a rapidly evolving FinTech landscape.
Source: Acta Psychologica
Authors: Farooq Ahmad Bajwa, Jingtao Fu, Ishtiaq Ahmad Bajwa, Shabir Ahmad, Faiq Mahmood
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,670
OpenAlex ID: W4409133285