Date of Award

2015

Document Type

Thesis

Degree Name

Master of Arts (MA)

Specialization

Communication and Leadership

School or Department

School of Leadership Studies

First Advisor

Dr. Carolyn Cunningham

Second Advisor

Dr. David Givens

Abstract

As shopping online continues to grow in popularity and convenience, so does the way consumers communicate information about products they have purchased. Most online retailers utilize some form of product review system (PRS) and customers are often encouraged to leave feedback about the product and their online shopping experience. Often a product can have radically polarizing reviews making it confusing for consumers. Using Berger’s and Calabrese’s Uncertainty Reduction Theory (URT) as well as Chaiken’s Heuristic-Systematic Model of Information Processing (HSM), this study looks to deduce what heuristic methods are the best for consumers who are looking to make informed decisions when navigating online customer reviews. Utilizing an online survey and a small focus group, participants analyzed examples of online customer reviews (OCR) for the purpose of deducing the heuristics that were favored in reducing uncertainty. The findings suggest that OCR that is objective, containing both pros and cons seem to reduce the most uncertainty, while purely negative/positive reviews actually increase it.

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