Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/27828
Title: Usability and Responsiveness of Chatbots on User Satisfaction and Continuance Intention of Generation Z in Sri Lanka
Authors: Nirasha, L. K
Malkanthi, S.S.
Keywords: AI chatbots, Continuance Intention, User Satisfaction
Issue Date: 2023
Publisher: Faculty of Commerce and Management Studies, University of Kelaniya Sri Lanka
Citation: Nirasha, L. K; Malkanthi, S.S. (2023), Usability and Responsiveness of Chatbots on User Satisfaction and Continuance Intention of Generation Z in Sri Lanka, 14th International Conference on Business and Information, Faculty of Commerce and Management Studies, University of Kelaniya Sri Lanka
Abstract: Artificial intelligence (AI) chatbots have gained a lot of attention over the past years. The purpose of this study was to examine the effect of chatbot adoption, user experience, and user satisfaction on the use of chatbots. Based on a comprehensive review of literature, a conceptual model was developed to answer the research questions of the study and it was tested using 125 responses collected from an online questionnaire. The quantitative approach was used in this study. Data were analysed using PLS-SEM with SmartPLS 4. Findings revealed a significant positive effect of user satisfaction on continuance intention. Further, it revealed that perceived intrinsic values have a significant positive impact on user satisfaction compared to perceived extrinsic values. Usability had a more significant impact on perceived intrinsic values than responsiveness. But when it comes to perceived extrinsic values, responsiveness had a significant impact. The findings of this study provided important implications for business managers in planning appropriate strategies to get the maximum out of chatbots. Finally, the findings of this study highlighted the directions for future research. Future research could utilize the model developed in this study to deepen the knowledge in this context.
URI: http://repository.kln.ac.lk/handle/123456789/27828
Appears in Collections:ICBI 2023 (Full Papers)



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