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

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.

Name thesis:degree_name

M.S., Applied Economics and Management

Level thesis:degree_level

Master of Science

Discipline thesis:degree_discipline

Applied Economics and Management

Grantor

Cornell University

Year dc:date.issued

2020

Author dc:creator

• Yalcinkaya, Beril

Committee members dc:contributor.committeemember

• Hoddinott, John
• Liaukonyte, Jurate

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

Statement dc:rights

• Attribution 4.0 International

Licence dc:rights.uri

• https://creativecommons.org/licenses/by/4.0/

Language dc:language.iso

en

DOI

https://doi.org/10.7298/rgjj-v171

Dc Identifier Other

ProQuest Submission ID: 10825
ProQuest Publication ID: 27837600

OAI identifier oai:identifier

oai:ecommons.cornell.edu:1813/70255