Abstract
In this paper, we perform an analysis of reviews for a national quick serve (fast food) restaurant chain. Results show that the company-owned restaurants consistently perform better than franchised restaurants in numeric rating (1–5 stars) in states which contain both types of operations. Using sales data, correlations are used to evaluate the relationship between the number of guests or sales of a restaurant and the rating of the restaurant. We found positive correlations were present between the number of customers at a location and the numeric rating. No correlation was found between the average ticket size and numeric rating. The study also found that 5-star rated restaurants have frequent comments related to the cleanliness and friendliness of the staff whereas 1-star rated restaurants have comments more closely related to speed of service and temperature of food. Overall, the study found that in contrast to previous research, rating sites like Yelp are relevant in the quick serve restaurant sector and reviews can be used to inform operational decisions, leading to improved performance. Detailed explanations related to the process of extracting this data and relevant code are provided for future researchers interested in analyzing Yelp reviews.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dwyer, E. A. (2015). Price, Perceived Value and Customer Satisfaction: A Text-Based Econometric Analysis of Yelp! Reviews. Scripps Senior Theses. Paper 715. http://scholarship.claremont.edu/scripps_theses/715. Accessed 2 September 2016.
Garcia-Castro (2016). R. Example of creating n-gram clouds. https://rstudio-pubs-static.s3.amazonaws.com/118348_a00ba585d2314b3c937d6acd4f4698b0.html. Accessed 20 January 2016.
Gartner Group (2016). Dark Data. http://www.gartner.com/it-glossary/dark-data/. Accessed 3 September 2016.
Gregory, A., Parsa, H. G., & Terry, M. (2011). Why Do Restaurants Fail? Part III: An Analysis of Macro and Micro Factors. University of Central Florida, The Dick Pope Sr. Institute for Tourism Studies UCF Rosen College of Hospitality Management.
Halevy, A., Norvig, P., & Pereira, F. (2009). The Unreasonable Effectiveness of Data. IEEE Intelligent Systems, 24(2), 8–12.
Hlee, S., Lee, J., Yang, S., & Koo, C. (2016). An empirical examination of online restaurant reviews (Yelp.com): Moderating roles of restaurant type and self-image disclosure. Information and Communication Technologies in Tourism, 2016, 339–353.
King, B. (2016). Caught in the middle: franchise businesses and the social media wave. Journal of Business Strategy, 37(2), 20–26.
Lawrence, B., & Perrigot, R. (2015). Influence of organizational form and customer type on online customer satisfaction ratings. Journal of Small Business Management, 53, 58–74.
Lim, Y., & Van Der Heide, B. (2015). Evaluating the wisdom of strangers: The perceived credibility of online consumer reviews on Yelp. Journal of Computer Mediated Communication, 20, 67–82.
Luca, M. (2011). Reviews, Reputation, and Revenue: The Case of Yelp.com. Harvard Business School Working Paper, No. 12–016, September 2011. (Revised March 2016. Revise and resubmit at the American Economic Journal-Applied Economics.).
Luca, M., & Zervas, G. (2015). Fake it till you make it: reputation, competition, and yelp review fraud. http://people.hbs.edu/mluca/fakeittillyoumakeit.pdf. Accessed 2 September 2016.
Malhotra, A., & Malhotra, C. (2015). How CEOs Can Leverage Twitter. http://sloanreview.mit.edu/article/how-ceos-can-leverage-twitter/. Accessed 3 September 2016.
McNeill, M. (2015). Text Mining in R: How to Find Term Frequency. https://deltadna.com/blog/text-mining-in-r-for-term-frequency/. Accessed 3 October 2015.
National Restaurant Association (2014). Restaurant Industry Forecast. https://www.restaurant.org/Downloads/PDFs/News-research/research/RestaurantIndustry Forecast2014.pdf. Accessed 3 September 2016.
Open Table (2016). Our Story. https://www.opentable.com/about/. Accessed 3 September 2016.
Parsa, H.G., van der Rest, J.P., Smith, S., Parsa, R., & Buisic, M. (2014). Why Restaurants Fail? Part IV The Relationship between Restaurant Failures and Demographic Factors. Cornell Hospitality Quarterly October 2014.
Remmers, M. (2014). 5 Ways to Get More Diners with Yelp: Leveraging the Online Review Site Can Maximize Your Restaurant’s Exposure. https://www.qsrmagazine.com/outside-insights/5-5ways-get-more-diners-yelp/. Accessed 3 September 2016.
Sena, M. (2016). Fast Food Industry Analysis 2016—Cost & Trends. https://www.franchisehefranchisehelp.com/industry-reports/fast-food-industry-report. Accessed 3 September 2016.
Taylor, D., & Aday, J. (2016). Consumer generated restaurant ratings: A preliminary look at OpenTable.com. Journal of New Business Ideas & Trends, 14(1), 14–22.
Vasa, N., Vaidya, A., Kamani, S., Upadhyay, M., & Thomas, M. (2016). Yelp: Predicting Restaurant Success. http://www-scf.usc.edu/~adityaav/Yelp-Final.pdf. Accessed 3 September 2016.
Wang, Q., Wu, X., Xu, Y. (2016). Sentiment Analysis of Yelp’s Ratings Based on Text Reviews. http://cs229.stanford.edu/proj2014/Yun Xu, Xinhui Wu, Qinxia Wang, Sentiment Analysis of Yelp’s Ratings Based on Text Reviews.pdf. Accessed 20 October 2016.
Yelp Developers Search API. (2015). https://www.yelp.com/developers/documentation/v2/search_api. Accessed 1 August 2015.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Gadidov, B., Priestley, J.L. (2018). Does Yelp Matter? Analyzing (And Guide to Using) Ratings for a Quick Serve Restaurant Chain. In: Srinivasan, S. (eds) Guide to Big Data Applications. Studies in Big Data, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-53817-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-53817-4_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-53816-7
Online ISBN: 978-3-319-53817-4
eBook Packages: EngineeringEngineering (R0)