Christina Soyoung Song
Papers
12
Total Citations
522
H-Index
7
About
Christina Soyoung Song is a pioneering researcher at the intersection of human-robot interaction (HRI), consumer behavior, and retail technology. Her work focuses primarily on how humanoid service robots are perceived, accepted, and integrated into retail environments, with particular emphasis on fashion and apparel contexts. Song's most influential contribution, "The Role of Human-Robot Interaction in Consumers' Acceptance of Humanoid Retail Service Robots" (2022), has garnered over 312 citations, establishing her as a leading voice in AI-driven retail automation. Grounded in frameworks such as Computers-Are-Social-Actors theory, service-dominant logic, and information sharing theory, her research examines how factors like social capability, usefulness, trust, and appearance shape consumer willingness to engage with and adopt retail service robots. Her methodological versatility is equally noteworthy — employing psychological network analysis, crisp-set qualitative comparative analysis (csQCA), and decision tree modeling to uncover nuanced consumer dynamics. Early in her career, Song contributed to the technical foundations of humanoid robotics, including biped walking control and gravity compensation systems, demonstrating a rare depth spanning both engineering and consumer science. Collectively, her body of work offers invaluable insights for retailers, technologists, and policymakers navigating the rapidly evolving landscape of AI-powered service automation.
Research Focus
Key Achievements
Top Papers
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- 5MODELING THE CONSUMER ACCEPTANCE OF RETAIL SERVICE ROBOTS13 citations · 2017
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- 7Applying Human-Robot Interaction Technology in Retail Industries9 citations · 2019
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- 10Self learning of gravity compensation by LOCH humanoid robot4 citations · 2008