9th Student Research Conference in Marketing (SRCM) - 2025

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Author: search.filters.author.Udara, S. W. I.Subject: search.filters.subject.AI Chatbots

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    The Impact of AI Chat Bot on User Experience in E-Commerce
    (Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Nimshan, E. S.; Udara, S. W. I.
    This study explores the impact of artificial intelligence (AI) chatbots on user experience in Sri Lankan e-commerce platforms, addressing key challenges such as limited personalisation, usability concerns, and trust deficits. The research builds on existing global literature while filling a gap in understanding AI adoption in Sri Lanka's unique socio-economic context. It identifies three independent variables namely; usability, personalisation and engagement, and trust, and evaluates their influence on user experience. The research employed a quantitative approach, using a survey distributed to 384 participants representing Sri Lankan e-commerce users. Data was collected via structured questionnaires, with Likert scale responses used to measure variables. Statistical techniques such as multiple linear regression and correlation analysis were applied to assess the relationships among variables and their impact on user experience. Descriptive and inferential statistics provided insights into the study's hypotheses. The results demonstrate strong positive correlations between usability (r = 0.831), personalisation and engagement (r = 0.802), and trust (r = 0.805) with user experience. Usability emerged as the most significant predictor (β = 0.405), followed by trust (β = 0.292) and personalisation and engagement (β = 0.213). An adjusted R-squared value of 0.772 suggests that the model explains 77.2% of the variance in user experience. These findings emphasise the importance of enhancing platform usability, fostering trust, and offering personalised interactions to improve user satisfaction. This study is limited by its reliance on self-reported data, which may introduce response bias. Additionally, the findings are specific to Sri Lanka’s e-commerce market and may not generalise to other regions with different digital infrastructures or consumer behaviours. Future research could incorporate qualitative methods or longitudinal designs to capture evolving user preferences. Theoretically, this study contributes to the body of knowledge by highlighting the interplay between usability, trust, and personalisation in shaping user experience. Practically, the findings offer actionable insights into e-commerce platforms, emphasising the need to invest in user-centric AI chatbot designs. Future research could explore the role of cultural factors and AI-driven innovations in enhancing digital consumer experiences.