Modeling the Relationships Between Internet Retailing Components to Advance Sales in the Apparel Industry

Abstract

This study aims to model the relationships between the components influencing Internet retailing in the apparel industry and their impact on sales growth. Using a mixed-methods research approach (qualitative and quantitative), data were collected through semi-structured interviews with 20 industry experts (until theoretical saturation was reached) and standardized questionnaires. Qualitative data analysis was conducted using qualitative content analysis with MAXQDA software, while quantitative data were analyzed using SPSS and SmartPLS software. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were employed to examine the relationships between components. The findings indicate that success in online apparel retailing requires simultaneous attention to 11 main components and 22 subcomponents, including user experience, pricing, product quality, customer service, digital marketing, logistics and timely delivery, trust and credibility, personalization and recommendations, branding and brand image, innovative technologies, and customer feedback. These components directly and indirectly influence customer satisfaction and sales growth. The results of this study can help apparel brands design and implement their strategies more effectively, thereby significantly increasing their sales. However, this research has limitations, such as focusing on a specific geographic region and the apparel industry. Additionally, given the rapid advancement of technologies such as artificial intelligence and virtual reality, future research is recommended to examine the impact of these technologies on Internet retailing.