Mobile Augmented Reality Service Performance for Interactive Product Visualization and Purchase Confidence
Year: 2026
Type: article
Abstract: The rapid advancement of mobile technology has significantly transformed digital commerce by creating more interactive, immersive, and user centered shopping experiences. Nevertheless, conventional mobile commerce applications still face challenges in delivering realistic product visualization, causing uncertainty among consumers during purchasing decisions. Augmented Reality (AR) technology has emerged as an innovative solution that enables users to interact with virtual products within real-world environments through mobile devices. This study aims to develop and evaluate a Mobile Augmented Reality Application for Interactive Product Visualization in order to enhance user experience, product understanding, and consumer confidence in mobile commerce platforms. The research employed a quantitative experimental approach through the design and implementation of an AR-based mobile application using Unity and ARCore technologies. Data collection was conducted through usability testing and questionnaire distribution involving users familiar with mobile shopping applications. The evaluation process focused on usability, interactivity, visualization quality, and user satisfaction. The results indicate that the implementation of AR technology product visualization accuracy, user engagement, and purchase confidence compared to conventional mobile interfaces. Furthermore, users perceived the application as more effective in supporting product exploration and reducing uncertainty before purchasing. This study also contributes to the achievement of the Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) by encouraging innovation in digital commerce technologies, and SDG 12 (Responsible Consumption and Production) by promoting informed purchasing decisions and may potentially contribute to reducing product returns. In conclusion, mobile AR applications demonstrate substantial potential to improve digital shopping experiences while supporting sustainable technological innovation within the mobile commerce ecosystem.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7204845917