Potential User Segmentation Based on Expectations of Social Robots Using Q-Methodology

This study explores users' expectations of social robots by employing Q-methodology, a technique that identifies patterns of subjective opinions. By reviewing research papers and conducting interviews, we created 37 statements about social robot issues and users ranked these statements based on perceived importance. This made an individual's subjectivity be measured and analyzed to distinguish between features deemed important by most users and those with high degrees of disagreement. Participants showed low interest in gaming, talking, and bonding with robots. Opinions on additional service charges were neutral while personalization was favored. We identified four types of consumers: those perceiving robots as a burdensome machine, a trusted friend, an emotionally intelligent device, and an energizing gadget. This research suggests a new academic framework to evaluate social robots consists of five dimensions: physical anthropomorphism, psychological anthropomorphism, cognitive intelligence, and user's willingness to comply with robot's suggestions and sacrifice. Our findings offer broad applications for companies developing social robots, providing a methodology that can serve as a basis for market surveys prior to product development and help tailor designs to meet the expectations of specific consumer niches.