Investigating Style Satisfaction in Online Fashion Apparel Shopping Across Generations using Multigroup Structural Equation Modeling: A Comprehensive Study

Abstract

Online shopping has emerged as a widely adopted activity on the internet, demonstrating substantial growth in recent years, albeit not yet realizing its full potential. The internet has provided new opportunities for organizations to effectively engage with both current and potential customers. Websites play a crucial role in facilitating customers to seamlessly explore, compare, and conduct online purchases of various products and services, with a notable emphasis on fashion apparel.
This study aims to identify the diverse factors influencing customer satisfaction with online shopping for fashion apparel across different age groups. Utilizing a Likert Scale format with five options (SA= strongly agree 5, A= agree 4, U= undecided 3, D= disagree 2, SD= strongly disagree 1), the questionnaire comprises two sections. The first section captures demographic information, while the second delves into four factors through 21 questions. Conducted via Google Forms, distributed through email and WhatsApp, the survey targeted respondents aged 18 and above, mentally sound, engaged in online shopping, and residing in Purba Midnapore. Employing stratified random sampling, the population was segmented into smaller groups. Out of 700 collected responses, 60 were discarded due to incomplete information, resulting in a dataset of 640.
Factor analysis, facilitated by SPSS21 (IBM Corporation), was employed to identify constructs. Confirmatory factor analysis, conducted using AMOS 20 (IBM Corporation), further elucidated the variables and their alignment within specific factors. Four factors— perceived quality, perceived benefit, perceived price, and perceived safety—were identified for each age group. In summary, the model has achieved a commendable level of goodness of fit.