The Factor Affecting Intention to Use Artificial Intelligence (AI) Chatbot in The Context E-Commerce

Leong, Chee Weng (2024) The Factor Affecting Intention to Use Artificial Intelligence (AI) Chatbot in The Context E-Commerce. Masters thesis, Tunku Abdul Rahman University of Management and Technology.

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Abstract

The rapid growth of e-commerce and advancements in artificial intelligence have led to the widespread adoption of AI chatbots in the online retail sector. While chatbots offer round-the-clock customer support, personalised recommendations, and cost-efficiency, there are challenges related to user acceptance. Some users embrace chatbots for their convenience, while others remain sceptical, preferring human interactions due to privacy concerns and the perceived impersonal nature of chatbot interactions. This variance in user acceptance limits the full potential of chatbots and can result in suboptimal customer experiences. To address this, it is essential to understand the factors influencing user willingness to adopt chatbots in e-commerce. Businesses can then customize chatbot strategies, enhance user experiences, and allocate resources efficiently. This research aims to shed light on these factors and contribute to the seamless integration of chatbots in e-commerce, ultimately improving customer satisfaction and competitive advantage. By reviewing the current body of research on the intention to use AI chatbots, it becomes evident that there are notable gaps in empirical studies in several key areas. These gaps encompass the examination of AI-specific characteristics, the exploration of how users navigate the trade-off between personalisation and privacy concerns, the significance of anthropomorphism, the mediating function of trust, and the influence of AI system transparency. Therefore, this research aims to consummate the understanding of intention to use AI Chatbot by examining the influence AI-specific characteristics such as personalisation and anthropomorphism on the intention to use AI chatbot in the context of e-commerce. For the conceptual framework development, Personalisation-Privacy Paradox and Privacy Calculus Theory are employed as theoretical support of the framework development. This research investigates the direct and indirect relationship between AI system transparency, anthropomorphism, personalisation, privacy concern, trust, and intention to use AI chatbot. Moreover, this research also establishes the moderator role of ability belief towards the relationship between AI system transparency and trust. To implement the research objectives, a total of 301 samples were collected through online self-administered questionnaire survey and the data is analysed by using Statistical Package for Social Sciences (SPSS) and Partial Least Square – Structural Equation Modelling (PLS-SEM). Based on the statistical findings generated, all the direct relationships between AI system transparency, anthropomorphism, personalisation, privacy concern, trust, and intention to use AI chatbot are significantly supported. For indirect relationships, all the mediation relationships are significantly supported. Besides, the result also proved that the direct relationship between AI system transparency and trust would be stronger when an online shopper has a high level of belief in the ability of the AI chatbot. The outcomes of this research hold significant theoretical and managerial implications. They substantiate the impact of variables, including AI-specific characteristics, AI system transparency, and trust, on users' intention to use AI chatbots. These variables wield considerable influence over users' trust and intention to utilize AI chatbots. As the research concludes, it highlights some limitations and offers recommendations for future studies aimed at further enhancing our understanding of users' intention to use AI chatbots in the e-commerce context.