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Chatbot Adoption Framework for Real-Time Customer Care Support
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| dc.contributor.author | Nyongesa, Geoffrey | |
| dc.contributor.author | Omieno, Kelvin | |
| dc.contributor.author | Otanga, Daniel | |
| dc.date.accessioned | 2025-07-07T08:17:49Z | |
| dc.date.available | 2025-07-07T08:17:49Z | |
| dc.date.issued | 2025 | |
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The chatbot enhancing customer service in Kenya. O Tech Trends Kenya. O Tech Trends Kenya Article. | en_US |
| dc.identifier.issn | 2810-0670 | |
| dc.identifier.uri | http://erepository.kafuco.ac.ke/123456789/273 | |
| dc.description.abstract | In our society today, most sectors are digitizing and automating their processes for efficiency. Human labour has become obsolete as a result of the disruption of labour markets brought about by the rising complexity and availability of software programs. When seen in this light, the adoption of artificial intelligence chatbots by businesses as a supplement to human customer service representatives serves as a crucial development. Computer programs or software that communicate with humans using natural language are referred to as chatbot applications. Through the use of speech, text, or both, the purpose of a chatbot is to simulate human interaction in response to input in natural language. For the purpose of providing customer care support services, there are no well formulated rules for the implementation of artificial intelligence chatbots in Kenyan telecom companies. An adoption framework for the deployment of artificially intelligent chatbots in the telecommunications sector was proposed as the objective of the research. This was accomplished by determining the current level of the installation of chatbot apps in Kenya and identifying the primary metrics that might be used as indications for the dissemination of chatbots. A study of the earlier frameworks and models on technology adoption was conducted in order to determine the relevant metrics. A combination of research approaches was used in this study, with questionnaires and interview schedules being used to obtain quantitative and qualitative data, respectively. In order to examine qualitative data, content analysis was what was used. Using tables and charts, descriptive analysis was performed on the quantitative data, and the findings were presented. AI specialists working for Safaricom PLC and the Communications Authority of Kenya were the ideal candidates for this position. From the two different telecommunications companies, a sample was selected for the research study utilizing the Delphi approach. A descriptive analysis as well as a major component analysis were used because they serve as a guide on aspects to consider before using AI chatbots for customer support services provision. The results of this research are particularly important to all companies that are involved in providing telecommunication services. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | International Journal of Informatics Information System and Computer Engineering | en_US |
| dc.subject | artificial intelligence, chatbot, customer support, machine learning, virtual assistant | en_US |
| dc.title | Chatbot Adoption Framework for Real-Time Customer Care Support | en_US |
| dc.type | Preprint | en_US |
