Embracing Digitalisation with Chatbots: A Qualitative Study of Danish Companies Adoption of Chatbot Technology

Abstract

This thesis set out to investigate what impacts the decision to adopt a chatbot. A chatbot is a computer program developed to converse with humans using natural language as in- and output. This technology is part of a broader discussion regarding automation of processes. Automation is widely believed to create an impact on the business industries and our daily life as we know it. Companies are eager to make things smarter, reduce cost and build the best service for their customers. Danish companies have not been late to understand this big potential in digital technologies and have invested heavily into the area in recent time. However, the functionality of the chatbot is currently very limited, and most of them still function as “hard coded decision trees”. We were thus driven by the contradiction between companies wanting to adopt the chatbot and that the technology is still very immature. Our research question thus became: Why do Danish companies decide to adopt the chatbot technology despite its immature state and how can this be explained by using the theory of IT innovation adoption? ● What are the barriers and drivers to the adoption of the chatbot technology? ● How does a company’s market strategy influence the adoption rate of the chatbot technology? To answer our research question, we created a conceptual framework based on IT innovation adoption theory. We then conducted a multiple-case study where we collected data from two different sources: semi-structured interviews and documentations. We found that companies saw far more drivers than barriers, which also supports the enthusiasm about the chatbot technology. We stressed, however, that every case organisation still had a unique combination of both drivers and barriers. We investigated these unique combinations by looking at the case organisation’s market strategy. We found that depending on how the organisation creates value and interacts with the environment, it can influence how an organisation approaches an innovation. It can influence it to approach an innovation faster, or to refrain from approaching it altogether. Lastly, we found that companies changed their perception of some adoption factors through the adoption process. This indicated that a factor, that initially was a driver, later turned into a barrier for the adoption. We argue that these insights explain that the companies that perceive the adoption as complex have not adopted a chatbot, meanwhile, those companies that do not perceive it as complex have already implemented the technology. Our answers imply that a positive attitude towards an innovation influences how organisations perceive the technology. They therefore approach the innovation quickly, leading some to not be prepared for the implementation. We confirm the IT adoption theory, that when many drivers are present, the organisation will likely adopt the technology. We imply that by using a qualitative approach, we are able to highlight gaps, where we could not explain the empirical data and thus recommend to expand the theoretical foundation. We did not claim that our findings could be applied outside of our domain without any reservation. We did however, argue that our findings could be generalised to similar settings as long as they share similar approaches to customer engagement and the chatbot stays a homogeneous technology.