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

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/29644

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Exploring The Impact of Ai Chatbots on Brand Consideration in The Sri Lankan E-Commerce Industry: The Moderating Role of Consumer Emotions
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Neeliya, M. D. S.; Karunanayake, R. K. T. D.
This study investigates the influence of Artificial Intelligence (AI) chatbots on brand consideration within Sri Lanka’s rapidly expanding e-commerce sector. It examines how consumer interactions with AI-powered chatbots impact their brand evaluation and decision-making processes. Additionally, the study explores whether consumer emotions moderate the relationship between chatbot interactions and brand consideration, offering insights into the emotional dynamics of digital consumer engagement. A quantitative research methodology was adopted, utilizing an online survey distributed to a stratified random sample of 384 Sri Lankan consumers aged 20 to 45 years who had interacted with AI chatbots on e-commerce platforms within the past six months. The study incorporated primary data on consumer perceptions, attitudes, and behaviors related to chatbot interactions, supplemented by secondary data from academic literature and industry reports. Data analysis included descriptive statistics, correlation analysis, and regression analysis, conducted using IBM SPSS Statistics 25 Findings from the regression analysis reveal that AI chatbots account for 79.0% of the variance in brand consideration (B = 0.814, p < 0.05), confirming their substantial impact on consumer decision-making. However, the hypothesized moderating role of consumer emotions was not supported (B = 0.0004, p = 0.9851), indicating that chatbot interactions influence brand consideration independently of emotional factors. These results suggest that Sri Lankan e-commerce businesses should prioritize AI chatbots’ technical efficiency, reliability, and functionality rather than attempting to tailor chatbot interactions to consumer emotions. Businesses would benefit from developing AI chatbots that provide clear, consistent, and value-driven interactions rather than focusing on creating emotionally nuanced experiences. From a theoretical perspective, this study enhances the Customer-Based Brand Equity (CBBE) model by emphasizing AI chatbot interactions as a key driver of brand consideration. It also refines Brand Personality Theory, illustrating how AI chatbots can convey brand attributes and influence consumer perceptions without relying on emotional engagement. Practical implications suggest that Sri Lankan e-commerce businesses should invest in technically robust and user-friendly AI chatbots to enhance consumer engagement and brand perception. Additionally, policymakers and digital marketplace stakeholders should consider these findings when promoting responsible and effective AI integration in the e-commerce sector. Despite its contributions, the study has certain limitations. The cross-sectional design restricts the ability to assess long-term behavioral changes among consumers. Moreover, reliance on self-reported data introduces the potential for response bias. The study also does not account for individual chatbot features or advanced emotion measurement technologies, which may play a role in shaping consumer interactions. Future research could explore these aspects further, incorporating longitudinal approaches and experimental designs to deepen the understanding of AI chatbot effectiveness in digital consumer engagement.
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.