| dc.contributor.author | Kristkroshan, J. | |
| dc.date.accessioned | 2025-12-08T11:23:49Z | |
| dc.date.available | 2025-12-08T11:23:49Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://drr.vau.ac.lk/handle/123456789/1589 | |
| dc.description.abstract | This research investigates how AI-powered chatbots influence customer engagement in the e-commerce industry of Jaffna city, Sri Lanka. While such technologies are widely implemented to enhance digital customer service, there is a lack of insight into their impact in culturally unique and technologically developing areas like Jaffna. The study aims to fill this gap by examining the effect of key chatbot features such as speed of response and personalization on customer satisfaction, trust, and loyalty. Using a quantitative approach, data were gathered from 49 respondents through an online questionnaire. Descriptive statistics and correlation tests were applied to analyze the link between chatbot features and user interaction. Results showed that young adults aged 18–25 are the primary users of chatbots in this region. However, neither responsiveness nor personalization had a strong influence on how frequently users engaged with chatbots. Slight gender differences were observed, with male participants showing higher satisfaction. Overall, users viewed chatbots as practical tools rather than emotionally engaging agents. The study recommends improvements in local language support, better natural language processing, and integration of human agents for complex queries. These insights are valuable for developing region-specific strategies that can enhance chatbot effectiveness and digital customer experience in Sri Lanka’s evolving e-commerce sector. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Marketing Management, Faculty of Business Studies, University of Vavuniya | en_US |
| dc.title | Impact of AI-Powered Chatbots on Customer Engagement in the Sri Lankan E-Commerce Sector in the Urban Areas of Jaffna District | en_US |
| dc.type | Conference abstract | en_US |
| dc.identifier.proceedings | 1st Undergraduate Research Symposium on Marketing (URSM) - 2025 | en_US |