How customers respond to chatbot anthropomorphism: the mediating roles of perceived humanness and perceived persuasiveness

Purpose This study aims to investigate how chatbots’ warmth and competence affect customer behavioural expectation (i.e. purchase, recommendation) through perceived humanness and perceived persuasiveness. Moreover, prior knowledge of chatbot is considered the boundary condition of the effects of chatbots’ warmth and competence. Design/methodology/approach A lab-in-field experiment with 213 participants and a scenario-based experiment of 186 participants were used to test the model using partial least squares structural equation modelling via SmartPLS 4. Findings Chatbot warmth positively affects customer behavioural expectation through perceived humanness while chatbot competence positively affects customer behavioural expectation through perceived persuasiveness. Prior knowledge of chatbot positively moderates the effect of chatbot warmth on perceived humanness. Research limitations/implications This study provides nuanced insights into the effects of chatbots’ warmth and competence on customer behavioural expectation. Future studies could extend the model by exploring additional boundary conditions of the effects of chatbots’ warmth and competence in different generations. Practical implications This study offers insightful suggestions for marketing managers on how to impress and convert online customers through designing verbal scripts in customer−chatbot conversations that encourage the customers to anthropomorphise the chatbots. Originality/value This study probes into the effects of chatbots’ warmth and competence on customer behavioural expectation by proposing and examining a novel research model that incorporates perceived humanness and perceived persuasiveness as the explanatory mechanisms and prior knowledge of chatbot as the boundary condition.

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Publication Details

Journal
European Journal of Marketing
Published
2024-11-21
DOI
https://doi.org/10.1108/ejm-11-2022-0827
Citations
15
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
5.21
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article

How customers respond to chatbot anthropomorphism: the mediating roles of perceived humanness and perceived persuasiveness

Ruolan Hou, Ran Tan, Yang Li
15 citations
European Journal of Marketing
AI in Service Interactions
5.21
article

How customers respond to chatbot anthropomorphism: the mediating roles of perceived humanness and perceived persuasiveness

Ruolan Hou, Ran Tan, Yang Li
article en
15 citations

Abstract

Purpose This study aims to investigate how chatbots’ warmth and competence affect customer behavioural expectation (i.e. purchase, recommendation) through perceived humanness and perceived persuasiveness. Moreover, prior knowledge of chatbot is considered the boundary condition of the effects of chatbots’ warmth and competence. Design/methodology/approach A lab-in-field experiment with 213 participants and a scenario-based experiment of 186 participants were used to test the model using partial least squares structural equation modelling via SmartPLS 4. Findings Chatbot warmth positively affects customer behavioural expectation through perceived humanness while chatbot competence positively affects customer behavioural expectation through perceived persuasiveness. Prior knowledge of chatbot positively moderates the effect of chatbot warmth on perceived humanness. Research limitations/implications This study provides nuanced insights into the effects of chatbots’ warmth and competence on customer behavioural expectation. Future studies could extend the model by exploring additional boundary conditions of the effects of chatbots’ warmth and competence in different generations. Practical implications This study offers insightful suggestions for marketing managers on how to impress and convert online customers through designing verbal scripts in customer−chatbot conversations that encourage the customers to anthropomorphise the chatbots. Originality/value This study probes into the effects of chatbots’ warmth and competence on customer behavioural expectation by proposing and examining a novel research model that incorporates perceived humanness and perceived persuasiveness as the explanatory mechanisms and prior knowledge of chatbot as the boundary condition.

European Journal of MarketingVol. 58(12)
University of Science and Technology of China (CN), Hefei University of Technology (CN)
Openalex Percentile: Top 4%
AI in Service Interactions
5.21
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