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Customer Preferences in Small Fast-Food Businesses: A Multilevel Approach to Google Reviews Data

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Abstract

Online reviews influence customers' decisions and present publicly available data to investigate their preferences on dining experience attributes. This study compares customer reviews of small fast-food businesses to national fast-food chains and builds executable recommendations to small businesses by analyzing 82,598 customer entries from Google Reviews. With text analysis tools and multilevel multinomial models, the study demonstrates that customer reviews for small businesses are less polarized and more positively skewed compared to chain restaurants. The findings also demonstrate the significance of four dining experience attributes: food, service, ambience, and price. The analysis suggests that among these, food and service are the most crucial qualities for fast-food restaurants. While food offerings are essential to get high ratings for small businesses, service is the primary factor in inducing customers to share their feelings. Due to positive skewness in customer ratings, small businesses need to have powerful testimonials to differentiate them from their competitors. Therefore, to build and increase customer base, small fast-food restaurants need to capture the attention of customers with food offerings and promote positive and insightful review contents with service quality.

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Description

110 pages

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Date Issued

2020-05

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Keywords

Customer Preferences; Customer Reviews; Multilevel Model; Restaurants; Small Business; Text Analysis

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Union Local

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Committee Chair

Just, David

Committee Co-Chair

Committee Member

Hoddinott, John
Liaukonyte, Jurate

Degree Discipline

Applied Economics and Management

Degree Name

M.S., Applied Economics and Management

Degree Level

Master of Science

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Government Document

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Attribution 4.0 International

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dissertation or thesis

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