Exploring the Impact of Conversational Style in Enhancing Recruitment Chatbot Interactions

This research examines the influence of conversational style formalities in recruitment chatbots on job seekers’ willingness to disclose sensitive or confidential information and the quality of their responses. This research was carried out through two studies on the Prolific platform, evaluating the effects of formal and casual conversational styles used by RecoBot, an advanced recruitment chatbot designed to simulate the real-world recruitment process for job seekers. Study 1 evaluated the likelihood of information disclosure based on the sensitivity of the information requested, finding that a formal style enhanced perceptions of usefulness and efficiency, especially with sensitive career-related data. Study 2 explored the quality of user responses in discussing career development, revealing that formal interactions prompted more detailed and thoughtful exchanges. The findings highlight the importance of aligning chatbot conversational styles with professional standards to foster effective user interactions and improve the quality of data exchange in recruitment processes. The research underscores the potential for chatbots to dynamically adapt conversational styles to fit the context of the interaction, suggesting pathways for future technological and methodological enhancements in the design of conversational agents within professional settings.