Abstract
E-commerce websites have created a great opportunity not only for businesses but also for consumers to perform their transactions directly. These transactions can be classified into different types such as consumer-oriented factors, behavioral factors, and Human Computer Interaction (HCI)-based factors. This study uses a twofold approach. In the first phase, prominent HCI factors are identified through existing literature namely; accessibility, simplicity, and usefulness which enhances the interaction of people with E-commerce websites. In the second phase of the study, we conducted a detailed experiment by varying the identified HCI factors towards consumer interaction using text-mining approach. Various approaches have been utilized to identify the relationship between factors affecting the consumers’ online purchasing behavior. Most of the cases, those studies focused on one website to identify the HCI factors pertaining to it. To overcome the research gap in current literature, the authors have built a novel and a unique approach to assess the factors related to HCI in enhancing online purchasing experience of diverse customer settings.
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Malkanthi, N., Rupasinghe, T.D. (2019). Text Mining-Based Human Computer Interaction Approach for On-line Purchasing. In: Hemanth, J., Silva, T., Karunananda, A. (eds) Artificial Intelligence. SLAAI-ICAI 2018. Communications in Computer and Information Science, vol 890. Springer, Singapore. https://doi.org/10.1007/978-981-13-9129-3_15
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