An exploratory analysis of quick service restaurants using tidyverse tools in R
-
DOIhttp://dx.doi.org/10.21511/im.13(2).2017.03
-
Article InfoVolume 13 2017, Issue #2, pp. 23-40
- 976 Views
-
363 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This study presents an exploratory analysis of Quick Service Restaurants (QSR) industry in the US during 2015 by using publicly available data and open-source R software. The data analysis framework and tools utilized here were developed primarily by Hadley Wickham and are included in his tidyverse package in R. This data analysis framework consists of data import, data wrangeling, data exploration (tranformation, visualization, and modeling), and communication of results (Wickham & Grolemund, 2016). These steps are illustrated by exploring the relationship between sales, customer satisfaction, and other characteristics of 65 QSR restaurants in the US. In order to facilitate reproduction and replication of this study, the dataset as well as the R code are included in this study.
- Keywords
-
JEL Classification (Paper profile tab)M31
-
References17
-
Tables17
-
Figures8
-
- Fig. 1. The tidyverse packages
- Fig. 2. QSR characteristics by segment
- Fig. 3. QSR boxplots and violin plots by segment
- Fig. 4. QSR sales by ACSI and unit average sales by ACSI
- Fig. 5. QSR best-in-segment sales and by segment relationships
- Fig. 6. QSR best-in-segment unit average sales and by segment relationships
- Fig. 7. Scatterplots, histograms, and correlations
- Fig. 8. Diagnostic plots (log-log OLS model)
-
- Table 1. Quick service restaurants (USA, 2015)
- Table 2. Quick service restaurants sales by segment
- Table 3. Quick service restaurants average unit sales by segment
- Table 4. Quick service restaurants ACSI index by segment
- Table 5. Descriptive Statistics
- Table 6. QSR Mean Values by Segment: Sales ($ millions), Average Sales per Unit (thousands), and ACSI (0 – 100)
- Table 7. QSR (Sales > 1500): Sales (millions), Average Sales per Unit (thousands), and ACSI (0 – 100)
- Table 8. OLS and log-log OLS models: 2015 dataset
- Table 9. Global test of log-log OLS regression model’s assumptions
- Table 10. Quick service restaurants (segment = sandwich)
- Table 11. Quick service restaurants (segment = chicken)
- Table 12. Quick service restaurants (segment = burger)
- Table 13. Quick service restaurants (segment = seafood)
- Table 14. Quick service restaurants (segment = ethnic)
- Table 15. Quick service restaurants (segment = pizza)
- Table 16. Quality measures of regression models
- Table 17. Coefficients of regression models
-
- ACSI LLC (2017). American Customer Satisfaction Index Benchmarks By Industry: Limited-Service Restaurants.
- Chang, Winston. (n.d.). Multiple graphs on one page (ggplot2). In Cookbook for R.
- Held, Fabian P. (2017). Introduction to the Tidyverse.
- Levy, Michael. (2016). Tidyverse Tutorial.
- QSR, Inc. (2016). The QSR 50: An inside look at the top 50 brands in quick service and fast casual.
- R & Data Science.
- R Views (2017). What is the tidyverse?
- The R Foundation (n.d.). The R Project for Statistical Computing.
- The tidyverse: dplyr, ggplot2, and friends. (n.d).
- Tibble Data Format in R: Best and Modern Way to Work with Your Data.
- Tidyverse (n.d.)
- Tidyverse packages (n.d.).
- Wickham, Hadley, & Grolemund, Garrett. (2017). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly.
- Wickham, Hadley. (2016). Tidyverse 1.0.0.
- Wickham, Hadley. (2017). The Tidy Tools Manifesto.
- Wickhham, Hadley. (2016). Ggplot2. Second edition. Springer.
- Wilke, C. O. (2016). Introduction to cowplot.