Factors Affecting the Revenue of the Pizza Industry

In this report, we built a competition model to analyze the market shares for the pizza shop industry in a Columbus neighborhood.  17 pizza shops are included in our model: Bono Pizza, Caffe Davinci, Carsoni’s Stromboli & Pizza, Cowtown Pizza, Dewey’s Pizza, Donatos Grandview, Donatos Upper Arlington, Grandad’s Pizza, Little Caesar’s Pizza, Mama Mimi’s Pizza, Panzera’s Pizza, Pizza Hut, rotolo’s Pizza, Spagio, Sparano’s Pizza, Tommy’s Pizza Inc. and Vino Vino.After locating each shop in the study area,  we analyzed the market share and net sales for each pizza shop in the area.

Some of these shops are chain restaurants, and some are individually owned.  The following map shows the location of all the 17 stores:

blog1

 

In order to increase the accuracy of the model, a grid is used to neutralize the shape effect of the irregular census blocks for our area. We then found the population for the area.  The population consists not only of people living in the area, but also of people going to school or working in the neighborhood.  All of these people are likely to be consumers at these pizza shops.  Shops located in the more dense areas of the map have an advantage over their competitors who are located on the fringe of the population centers.

blog2

 

For our study, the population of the study area was just one of the many variables taken into account.  We also used the size of the restaurant, the number of employees, and hours that the restaurant is open.  As each of these variables increases, revenue will increase as well. Price and number of toppings offered by each shop were also factors in our study.  Other factors include whether a store provides delivery service, serves alcohol, offers waiter service, has T.V.’s to watch sports, is part of a national chain, is discount vs. high end, and whether they serve quick lunch (pizza by the slice or buffet).

After setting values for each of these variables, the results of our model were obtained.  The following is a table of Market Share and Annual Net Sales for pizza shops in our confined study area.

blog3

 

The graph below is a comparison of revenue for each store.  Dewey’s, a high end restaurant, clearly obtains the highest revenue according to our model.  The chain restaurants, Pizza Hut and Donatos, are the next highest.

blog4

 

Based on this model, we conclude that chain restaurants such as Pizza Hut and Donatos usually have higher annual revenue.  The market share numbers show that smaller shops usually have less revenue in comparison to their large competitors which have multiple locations.  This being said, the small shops still earn a substantial amount of the market share and do fairly well in comparison to their competitors.  This is probably due to the quality of the pizza, as well as the fact that small shops usually offer delivery.

From this study, we can conclude that small store revenue could be increased if lunch were offered (pizza by the slice or buffet).  Although it does add to the cost of the business, the benefits more than cover the costs if a shop opens for the lunch hour.  By setting the parameter value and revenue prediction results on a single variable and leaving all others constant, we can see that the number of hours open has a large impact on market share.  The model also shows that pizza price is the variable that differentiates the market share most.

This model does not take into account the costs incurred by the pizza shops such as the fluctuating price of cheese, or the role that bad weather plays in the amount of revenue a shop will receive.  These factors will ultimately influence the capabilities of a shop.

To conclude, this model has a set of variables and maps that are used to predict revenue and market share.  We did not ask each store for their revenue numbers, rather we calculated the revenue of each store based on our parameters.  If actual revenue data were used, the model could be calibrated to show changes in economic conditions and predict future market share and revenue changes.  The model can be adjusted to add other pizza shops or take away shops that leave the area and to show how this could affect the other stores.