Abstract
PurposeRobotic chefs are starting to replace human chefs in restaurant industry. Whether customers have a good food quality prediction may have an important effect on their patronage decision. Based on the stereotype content model, the purpose of this paper is to investigate the impact of robotic chef anthropomorphism on food quality prediction through warmth and competence.Design/methodology/approachAn empirical analysis was done to test the theoretical model by using the SmartPLS software. A nonhuman-like robotic chef and a robotic chef with humanoid hands were used as background materials in the questionnaire. The effective sample was 221.FindingsRobotic chef anthropomorphism affects food quality prediction through the sequential mediators of warmth and competence. Age is a significant control variable.Research limitations/implicationsRobotic chef anthropomorphism positively affects food quality prediction. The halo effect of warmth perception on competence perception should be considered in the context of robot anthropomorphism.Practical implicationsRestaurants which feature robotic chefs should use robotic chefs with anthropomorphic designs and promote the anthropomorphic elements of robotic chefs in advertisements.Social implicationsThe anthropomorphic design of robot chefs will facilitate the development of artificial intelligence in restaurants in the future.Originality/valueTo the best of the authors’ knowledge, this paper is one of the first to focus on how robotic chef anthropomorphism affects food quality prediction and reveals the roles of warmth and competence in the influence of robotic chef anthropomorphism on food quality prediction.
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