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      Robot with humanoid hands cooks food better? : Effect of robotic chef anthropomorphism on food quality prediction

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      International Journal of Contemporary Hospitality Management
      Emerald

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          Abstract

          Purpose

          Robotic 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/approach

          An 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.

          Findings

          Robotic chef anthropomorphism affects food quality prediction through the sequential mediators of warmth and competence. Age is a significant control variable.

          Research limitations/implications

          Robotic 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 implications

          Restaurants which feature robotic chefs should use robotic chefs with anthropomorphic designs and promote the anthropomorphic elements of robotic chefs in advertisements.

          Social implications

          The anthropomorphic design of robot chefs will facilitate the development of artificial intelligence in restaurants in the future.

          Originality/value

          To 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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          Most cited references73

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          Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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            A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition.

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              Universal dimensions of social cognition: warmth and competence.

              Like all perception, social perception reflects evolutionary pressures. In encounters with conspecifics, social animals must determine, immediately, whether the "other" is friend or foe (i.e. intends good or ill) and, then, whether the "other" has the ability to enact those intentions. New data confirm these two universal dimensions of social cognition: warmth and competence. Promoting survival, these dimensions provide fundamental social structural answers about competition and status. People perceived as warm and competent elicit uniformly positive emotions and behavior, whereas those perceived as lacking warmth and competence elicit uniform negativity. People classified as high on one dimension and low on the other elicit predictable, ambivalent affective and behavioral reactions. These universal dimensions explain both interpersonal and intergroup social cognition.
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                Author and article information

                Journal
                International Journal of Contemporary Hospitality Management
                IJCHM
                Emerald
                0959-6119
                0959-6119
                April 13 2020
                April 13 2020
                : 32
                : 3
                : 1367-1383
                Article
                10.1108/IJCHM-10-2019-0904
                2415e57a-5eaa-4080-ad12-68d28e27aef0
                © 2020

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