Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Business Administration
First Advisor's Name
Alexandra Aguirre-Rodriguez
First Advisor's Committee Title
Committee chair
Second Advisor's Name
David Luna
Second Advisor's Committee Title
committee member
Third Advisor's Name
Ha Ta
Third Advisor's Committee Title
committee member
Fourth Advisor's Name
Ronald Mesia
Fourth Advisor's Committee Title
committee member
Fifth Advisor's Name
Bennett L. Schwartz
Fifth Advisor's Committee Title
committee member
Keywords
ARTIFICIAL INTELLIGENCE, SOUND SYMBOLISM, Name of AI Agent
Date of Defense
6-29-2023
Abstract
Although the widespread use and rapid advancement of Artificial intelligence (AI) technology are revolutionizing marketing and consumer behaviors in the marketplace, many consumers resist AI-assisted customer service agents across a variety of contexts. Yet, little is known regarding how to increase consumers’ AI acceptance. To fill this knowledge gap, the current study seeks to identify mechanisms that can potentially enhance consumers’ receptivity to AI. Drawing on sound symbolism theory, I propose that marketers can increase the accessibility of warmth and competence concepts in consumers’ minds by choosing congruent-sounding names for AI agents given their task type. Consequently, this matching effect of names and roles, which should operate implicitly, will facilitate consumer-AI interaction. Across several studies, I show the association of warmth (vs. competence) and front (vs. back) vowel sounds and the matching effect of the name sound with the AI agent role of coach (vs. expert) on consumers’ AI agent attitude, AI agent perceived trustworthiness, and the likelihood to follow the AI agent’s recommendation.
Identifier
FIDC011223
Recommended Citation
Tavallaei Nosratabadi, Malihe, "Sounds Like a Friend or an Expert: How Sound Symbolism Mitigates Resistance to Artificial Intelligence" (2023). FIU Electronic Theses and Dissertations. 5342.
https://digitalcommons.fiu.edu/etd/5342
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