Dissertations, Theses, and Capstone Projects

Date of Degree

6-2024

Document Type

Dissertation

Degree Name

Ph.D.

Program

Business

Advisor

Lauren G. Block

Advisor

Mahima Hada

Committee Members

Ana Valenzuela

Ujwal Kayande

Subject Categories

Business | Cognition and Perception | Computational Linguistics | Experimental Analysis of Behavior | Linguistics

Keywords

Linguistic Mimicry, Word-of-Mouth, Breadth, Depth, Information Search, Information Processing

Abstract

Word-of-mouth (WOM) in marketing occurs when consumers discuss a company's product or service or any consumption experience with their friends, family, and others with whom they have any relationship. With the advent of social media, this phenomenon has expanded rapidly into virtual environments where consumer conversation is enabled through chats, forums, social media posts, and online reviews. In response to this rapid growth of online WOM, academics and practitioners have focused their interest on this phenomenon and its implications on consumers, firms, and society. So far, the evidence of the critical role that online WOM plays in helping consumers make their purchase decisions is compelling. However, extant research has documented systematic biases in the online WOM generation, both about the probability of consumers leaving reviews as the content they contributed. The present work investigates linguistic mimicry as a bias in the online WOM generation by demonstrating that consumers mimic two important determinants of review diagnosticity – information breadth (the diversity of topics in a review) and information depth (the amount of information on a particular topic). We show that online reviewers write reviews with a greater breadth of topics the greater the breadth of topics in the proximate reviews, and they write reviews with a greater depth of information the greater the depth in the proximate reviews. We replicate this in different consumption settings (e.g., hotels, work experience, restaurants) using a multi-method approach that includes a field study using data from Tripadvisor, controlled lab studies, and automated text analysis using Machine Learning (ML) methods and standard dictionary-based approaches. Our findings also illuminate the significant impact of this mimicry on consumer decision-making processes. These effects manifest in various aspects, such as review helpfulness, product evaluations, and purchase intentions. Notably, our research identifies enhanced perceptions of product consistency as a mediating factor driving those effects.

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