Graduation Year


Document Type




Degree Name

Master of Science (M.S.)

Degree Granting Department


Major Professor

Cihan Cobanoglu, CHTP

Committee Member

Ekaterina Berezina, CHTP, CRME

Committee Member

Faizan Ali, Ph.D.


restaurant attributes, online reviews, restaurant rating, choice-based conjoint


Since social media has been growing rapidly, the restaurant industry has been exploring this area extensively. Given that social media provides restaurant consumers with an opportunity to share their dining experiences, several studies have examined the impact of social media on consumer restaurant selection (Tran, 2015). As a part of the social media umbrella, online reviews are significant factors that influence consumer restaurant selection (Park & Nicolau, 2015; Yang, Hlee, Lee, Koo, 2017). However, there is a lack of understanding with regard to which attributes of restaurant online reviews are the most influential when it comes to customer decision making. Therefore, this study aims to investigate the relative importance of online review attributes in consumer restaurant selection. Particularly, this study focuses on the number of online reviews, the overall restaurant rating, and the following restaurant attributes: food quality, service quality, atmosphere, and price, to address the purpose of the research.

Based on the recommendation of Orme, (2010), 353 respondents are recruited via Amazon’s Mechanical Turk, and a choice-based-conjoint (CBC) analysis is performed. The CBC analysis reveals the relative importance of each attribute for customer decision making. Based on the CBC analysis, the results confirms that food quality is the most important attribute in consumer restaurant selection. This factor is followed by overall restaurant rating, price, service quality, the number of online reviews, and atmosphere. Additionally, the overall restaurant rating is determined to be a substantially important factor that influences consumer restaurant selection, while the rest of the attributes vary in their rank. The market simulation calculated the preference estimates for the products for each respondent. This approach predicts the impact of each attribute on the market share. Food quality and overall restaurant rating are used for the market simulations. Therefore, it is also found that in relation to the market simulation, the decrease of food quality influenced the market share by about 58.88%. The findings of this study contribute greatly to the knowledge of the importance of food quality, and as a result, an overall restaurant rating. Therefore, restaurant managers should prioritize these key attributes to manage strategies for the restaurant