Exploring Lexical Alignment in a Price Bargain Chatbot

This study investigates the integration of lexical alignment into text-based negotiation chatbots, including its impact on user satisfaction, perceived trustworthiness, and potential influences on negotiation results. Lexical alignment is the phenomenon where participants in a conversation adopt similar words. This study introduces a chatbot architecture for price negotiation, consisting of components such as intent and price/product extractors, dialogue management, and response generation using OpenAI’s API, with a lexical alignment feature. To evaluate the effects of lexical alignment on negotiation outcomes and the user’s perception of the chatbot, a between-subject user experiment was conducted online. A total of 52 individuals participated. While the results do not show statistical significance, they suggest that lexical alignment might positively influence user satisfaction. This finding indicates a potential direction for enhancing user interaction with chatbots in the future.