This paper explores the intersection of neuromarketing, e-commerce, and human-robot interaction by investigating the impact of personality traits on user satisfaction, purchase intention, and brainwave patterns across different chatbot models (rule-Based vs generative AI) and platforms (virtual chatbots vs humanoid robots). The study introduces Generative AI chatbots to e-commerce websites, comparing their effectiveness with rule-based chatbots. Additionally, physical robots are included as a reference group to assess the effects of virtual and physical robots in shopping assistance. The manipulation of three personality traits (introvert, ambivert, and extrovert) in both online and offline settings enriches the understanding of user behavior in diverse scenarios. Data collection involves EEG measurements, system logs, and surveys to capture subjective perceptions, unconscious reactions, and decision-making processes. Ultimately, the research seeks to provide valuable insights for the development of human-computer interaction design, contributing to the formulation of design guidelines adapted specifically for the e-commerce landscape.
CITATION STYLE
Chang, Y. W., Chien, S. Y., Chan, Y. C., & Tsao, C. C. (2024). Human-Robot Interaction in E-Commerce: The Role of Personality Traits and Chatbot Mechanisms - A Neuromarketing Research. In ACM/IEEE International Conference on Human-Robot Interaction (pp. 312–316). IEEE Computer Society. https://doi.org/10.1145/3610978.3640742
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