Human Is Gold: Why Premium Customers Hate Chatbots and What to Do About It

Individuals are often biased in their judgments about AI, especially when it comes to customer-support-oriented service interactions. With three preregistered experiments (and three supplementary studies), the current research examines how marketplace status creates systematic differences in customer biases against chatbot-delivered services, and what firms can do to mitigate the impact of those biases on their evaluations. In Study 1 (N = 1,019), the authors show that high-tier (vs. basic) customers react more negatively to chatbot-delivered services, even when the objective service delivered is the same. They also demonstrate that greater perceptions of uniqueness neglect and entitlement among high-tier (vs. basic-tier) customers are possible explanations for this tier-based bias against chatbots. Study 2 (N = 1,196) demonstrates the effectiveness of three “framing interventions” that significantly reduced high-tier customers’ bias against chatbots. Finally, Study 3 (N = 899) examines different ways of acquiring a high marketplace status—earned versus unearned—as a boundary condition for the main effect, while experimentally demonstrating the mediational role of entitlement in addition to uniqueness neglect. Together, this research advances the understanding of human–robot interactions from a marketplace status lens and provides concrete managerial strategies for communicating about automated customer support services.

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Publication Details

Journal
Journal of Interactive Marketing
Published
2025-02-12
DOI
https://doi.org/10.1177/10949968251322513
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
0.00
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article

Human Is Gold: Why Premium Customers Hate Chatbots and What to Do About It

Jareef Martuza, Helge Thorbjørnsen, Aruna Divya Tatavarthy
Journal of Interactive Marketing
Sharing Economy and Platforms
article

Human Is Gold: Why Premium Customers Hate Chatbots and What to Do About It

Jareef Martuza, Helge Thorbjørnsen, Aruna Divya Tatavarthy
article en

Abstract

Individuals are often biased in their judgments about AI, especially when it comes to customer-support-oriented service interactions. With three preregistered experiments (and three supplementary studies), the current research examines how marketplace status creates systematic differences in customer biases against chatbot-delivered services, and what firms can do to mitigate the impact of those biases on their evaluations. In Study 1 (N = 1,019), the authors show that high-tier (vs. basic) customers react more negatively to chatbot-delivered services, even when the objective service delivered is the same. They also demonstrate that greater perceptions of uniqueness neglect and entitlement among high-tier (vs. basic-tier) customers are possible explanations for this tier-based bias against chatbots. Study 2 (N = 1,196) demonstrates the effectiveness of three “framing interventions” that significantly reduced high-tier customers’ bias against chatbots. Finally, Study 3 (N = 899) examines different ways of acquiring a high marketplace status—earned versus unearned—as a boundary condition for the main effect, while experimentally demonstrating the mediational role of entitlement in addition to uniqueness neglect. Together, this research advances the understanding of human–robot interactions from a marketplace status lens and provides concrete managerial strategies for communicating about automated customer support services.

Journal of Interactive MarketingVol. 61(1)
Norwegian School of Economics (NO)
Openalex Percentile: Top 97%
Sharing Economy and Platforms
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