Ching-Chih Tsao, Cheng-Yi Tang, Yu-Wen Chang, Y. Sung, S. Chien, Szu-Yin Lin
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The Influence of a Robot Recommender System on Impulse Buying Tendency
The present study examines the influences of a robot recommender system on human impulse buying tendency in online e-commerce contexts. An empirical user study was conducted, where different marketing strategies (limited quantity vs. discount rate) were applied to the products and intimate designs were utilized for the robotic agent. An electroencephalogram (EEG) headset was used to capture users' brain activities, which allowed us to investigate participants' real-time cognitive perceptions toward different experimental conditions (i.e., marketing plans and robotic agents). Our preliminary results reveal that marketing strategies and robot recommender applications can trigger impulsive buying behavior and contribute to different cognitive activities.
期刊介绍:
ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain.
THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.