Regulatory fit and online review helpulness: a word-embedding analysis

Update Item Information
Title Regulatory fit and online review helpulness: a word-embedding analysis
Publication Type dissertation
School or College David Eccles School of Business
Department Business
Author Ramakrishnan
Date 2020
Description Online reviews play a significant role in individual shopping behavior. With more and more people choosing to shop online, the number of reviews posted for each product has also increased. In order to ensure that the customer gets the best information possible, online shopping portals are using different algorithms to rank reviews and showcase the most influential reviews to customers. One metric that is significant in this process is the number of helpfulness votes received by the review. The helpfulness ratings received by a review indicates its persuasiveness and affects its visibility and overall impact. In this research, we analyze the triangular relationship between the content posted by a company (product description), content posted by a customer (product review), and the influence of the same on a prospective customer (using helpfulness votes). Using past research on regulatory focus, which has suggested that regulatory fit results in a higher evaluation of products, we propose that if there is a regulatory fit between product description (provided by the firm) and product reviews (provided by consumers), it will result in higher helpfulness ratings. We use a novel text analysis method, word embeddings, that allows one to semantically compare text, to test our hypothesis. We tested our hypothesis across different types of products and thousands of reviews. We find that for reviews that have a negative valence, regulatory fit increases the number of helpfulness votes. However, for reviews with positive valence, regulatory fit does not significantly increase helpfulness votes. We also conducted lab studies that supported the effect. We discuss the implications for marketing theory and practice.
Type Text
Publisher University of Utah
Dissertation Name Doctor of Philosophy
Language eng
Rights Management (c) Ramakrishnan
Format application/pdf
Format Medium application/pdf
ARK ark:/87278/s62xjy9g
Setname ir_etd
ID 2311456
Reference URL https://collections.lib.utah.edu/ark:/87278/s62xjy9g
Back to Search Results