Enhancing user experience in tourism services through digital nudging : an exploratory study of Gpt-based virtual agents

Abstract

After having thoroughly reviewed existent literature about nudging, digital nudging, chatbot technology, and the hospitality sector, and having identified the research gaps, this research will investigate whether implementing nudging techniques in virtual agents enhances user experience in tourism-related tasks, in particular in planning a trip to Baton Rouge, the capital of Louisiana. The objective is to assess whether implementing nudging techniques, such as default choices and framing to a virtual agent, improves user satisfaction, engagement, and perceived usefulness compared to standard GPT chatbots. Methodologically, an experimental exploratory approach was adopted, comparing a GPT-only chatbot with a GPT-nudging chatbot. Participants were randomly assigned to interact with one of the two virtual agents and subsequently completed a questionnaire based on an evaluative model that relies on the Technology Acceptance Model (TAM), Chatbot Usability Scale (CUS), and Client Satisfaction Questionnaire (CSQ-8). Results indicate that the GPT-nudging chatbot significantly improved user engagement, but not perceived usefulness, ease of use, and satisfaction, suggesting that while nudging techniques can increase interaction frequency, they do not necessarily enhance the overall user experience or the perceived value of the chatbot in tourism-related tasks. Conclusions highlight the potential of nudging-enhanced virtual agents to optimize user decision-making in tourism services, offering valuable insight for future research and implications for businesses aiming to leverage AI-driven customer interactions