Evaluating the Influence of UTAUT Factors on the Adoption of QR Codes in MSMEs: An Application of SEM and ANN Methodologies

In the past twenty years, there have been significant improvements in internet technology, leading to new services accessed through various web-based portals and applications. Mobile payments, often known as m-payments, have gained popularity because of the widespread use of smartphones and advancements in payment systems. The rise in smartphone adoption has facilitated the extensive utilization of QR codes for mobile payments. A substantial proportion of financial transactions are conducted using physical currency, QR codes provide a secure and traceable alternative for monitoring the movement of funds. Therefore, the purpose is to analyze factors influencing the use of QR payments and to assess the effectiveness of a dual-stage SEM-ANN approach in understanding these influences. This study employed a survey-based approach using a quantitative research design, with data collected from MSME owners in four major cities of Sindh. The survey, designed in English, Urdu, and Sindhi, was administered to 400 MSME owners. Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) analyses were conducted using SmartPLS-4 and SPSS-29. The findings reveal that Behavioral Intention (BI) to use QR codes is significantly influenced by Performance Expectancy (PE), Price Value (PV), Hedonic Motivation (HM), Habit, Social Influence (SI), and Facilitating Conditions (FC), with PE and PV being the most impactful. Therefore, QR service providers (financial and non-financial institutes) are required to speed up the performance of their QR codes to increase the use of QR.