Analysis of Experience using Shopee E-Commerce AI Features Among Young People with Modified TAM
Abstract
The use of Artificial Intelligence (AI) in e-commerce applications continues to experience rapid development, particularly in providing features that enhance personalization and provide a better shopping experience. However, there remains a challenge in understanding the extent to which experience in using AI features influences the level of usage of the Shopee application, especially among young people who are the largest user segment. This study aims to analyze the effect of experience using AI features on Shopee application usage using a modified Technology Acceptance Model (TAM) approach. The analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to examine the relationship between variables in the research model. A total of 11 hypotheses were proposed and empirically tested based on data obtained from 430 young respondents who are active Shopee users. The analysis results showed that all hypotheses were accepted, which means that experience using AI features plays a significant role in shaping perceptions of usefulness, user experience, and positive attitudes toward technology, which ultimately influence the intention and behavior of using e-commerce applications. These findings indicate the importance of developing AI features that are responsive and relevant to the needs of young users to improve loyalty and shopping experience. Thus, the practical implications of this research provide strategic input for e-commerce service providers in optimizing AI-based experiences to maintain competitiveness in the increasingly competitive digital market
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