Assignment 1 Making Decisions Based on Demand and Forecasting Essay

Assignment 1: Making Decisions Based on Demand and Forecasting

1 - Assignment 1 Making Decisions Based on Demand and Forecasting Essay introduction. Report the demographic and independent variables that are relevant to complete a demand analysis providing a rationale for the selection of the variables.

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More Essay Examples on Domino's Pizza Rubric

According to bundle website (2012), business is defined as normally Domino’s has made gains in three key measures: 1)Penetration i.e. the percentage of all households in the US that has ordered at least once from Dominos in the last year (last year Dominos delivered to 14% of all homes!), 2)The frequency with which a customer re-orders (about once per month), 3)The average value on the receipt ticket from each order (typically around 23)The demographic of Domino’s Pizza in my community at the following; Demographics of dominos’ pizza customers in zip code 20814 where I live ; You are more likely to see these groups of people at Domino’s pizza than in other local restaurants.

Location: 30% of Domino’s Pizza customers reside in zip code 20814, 79% are from Montgomery County, 83% are from Maryland, and 17% are from out of state.

The majority of customers spend a total of $16-35 per transaction, and the typical (median) total cost is $23. Total cost includes taxes and
gratuities, and does not account for party size.

2. Using Excel or other calculation software, input the data you collected in criterion one to calculate an estimated regression. Then, from the calculation provided, interpret the coefficient of determination, indicating how it will influence your decision to open the pizza business. Explain any additional variables that may improve the coefficient of determination.

Table 1. Sample data: The demand of domino’s pizza
Zip Code
Y
X1
X2
20002
20
23
30
20003
17
22
85
20005
19
20
30
20007
57
22
125
20009
25
22
20
20011
21
21
30
20016
16
22
125
20019
23
28
30
20032
39
26
20
20740
43
16
125
20743
31
21
65
20747
25
19
65
20781
20
23
45
20783
31
20
30
20814
57
23
125
20816
78
24
125
20852
47
22
65
20901
25
21
65
20902
8
20
30
20906
18
19
30
20910
16
20
45
21207
20
18
30
21208
13
18
45
21222
30
22
30
21224
36
21
30
21227
16
18
45
21237
35
17
65
22204
18
20
65
22206
22
20
65
Y = The percentage of people in the zip code who buy domino’s pizza X1= Price of Pizza (Median cost)
X2= Income of customers who buy Domino’s pizza (in K)

To estimate the demand of a particular good or service, first determine all the factors that might influence this demand. I wanted to estimate the demand for Domino’s pizza by person who live in Bethesda, Maryland by conducting a survey of thirty randomly selected zip codes area where have a domino’s pizza shop in my community, Maryland during a particular month. Suppose I have gathered the following information for each zip code from this survey: 1) Domino’s customer who lives in by 30 zip codes area, (2) average of domino’s pizza per box, 3) the percentage of people making X2 income that buy dominos pizza, and 4) Income of customers who buy Domino’s pizza. The data obtained from my website survey are presented in Table 1.

The reasons for selecting these variables are based on economic theory of demand. However, it should be clear why the price of domino’s pizza, average income, and average customers buying pizza, were selected for this study. Among the software package used by economists to conduct a regression analysis of the demand for a good or service are SPSS, SAS, and Micro TSP. To estimate the demand for pizza, I employed the regression function contained in Excel. Although, it only contains the basic elements of regression function. I believe it is perfectly suitable for many analyses that would be conducted in business research. Using the regression function in excel, I obtained the following estimates for domino’s pizza-demand regression equation: SUMMARY OUTPUT

Regression Statistics
Multiple R
0.584245498
R Square
0.341342802
Adjusted R Square
0.316948091
Standard Error
12.88456041
Observations
29

ANOVA

df
SS
MS
F
Significance F
Regression
1
2322.920159
2322.920159
13.9924921
0.000875305
Residual
27
4482.32122
166.0118971

Total
28
6805.241379

Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
13.49703762
4.666261932
2.89247321
0.00746584
3.9226591
23.0714161
3.922659101
23.07141614
0.257914486
0.068949036
3.74065397
0.00087531
0.11644275
0.39938622
0.116442751
0.399386221

In the regression results, I observe that the coefficient a show positive relationship between demand and income. In principle, the demand showed also depends in the price. As the price of pizza (X1) changes, the quantity demanded for pizza will change in the opposite direction. If the price of pizza goes up so the demand of pizza will decrease. However, in my sample there was not much variation in the price across zip codes the average price was about $20. So I was not able to find a relationship between demand and price from my sample. The price of domino’s pizza is 20 that not enough variation to elasticity.

3. Test the statistical significance of the variables and the regression equation, indicating how it will impact your decision to open the pizza business.

Coefficients
Standard Error
t Stat
13.49703762
4.666261932
2.89247321
0.257914486
0.068949036
3.74065397

Test the statistical significance of the variables and the regression equation results are truly reflective of the domino’s pizza customers demand. For this statistical analysis, the Coefficients are 13.49 and 0.25
, Standard Error are 4.66 and 0.06 and t Stat 2.89 and 3.74 those are the good power of the regression equation. In my opinion, Domino’s pizza is the best franchise to do business with because I consider from demographic, regression equation, forecasting demand, and the test statistical significance, etc. So if I purchase this franchise I believe that I will get more profits every year.

4. Forecast the demand for pizza in your community for the next four months using the regression equation, including the assumptions that were used to create the demand. Justify the assumptions made related to the forecast.

The forecast demand for pizza in my community that I got from regression equation; Demand = 13.5 + .26 * Income (income in zip code20814)
= 13.5 + .26* 125
= 55
As a result, I predict that a customer will purchase domino’s pizza in zip code 20814 because people have strong demand to buy it and residents also have a high income. However, if the price goes up so the demand will decrease. It is true that if prices go up too much demand will decrease. But, if price stays in the range of $17-$24, as it was the case in my sample, my results suggest that demand will not be affected too much Normally, Pizza is enjoyed by people from all walks of life and eating out at restaurants is an essential part of the American lifestyle. According to the National Restaurant Association, 45% of adults say that restaurants are still a major part of their lifestyle and that they will continue to frequent their favorite restaurants.

In The future, it will depend greatly on the ability of Domino’s marketing team to remain proactive, centered, and focused on the customers’ needs. Here are some typical examples of assumptions: (1) the most relevant assumptions for Domino’s Pizza Inc. with regards to operating income come from our revenue decomposition. (2) Domino’s has placed emphasis on expanding its domestic franchising business and its international revenue, and (3) Their costs of sales are broken down into categories that correspond to the revenue decomposition (e.g. supply chain revenue and supply chain cost of sales). 5. Based on the forecasting demand, determine whether Dominos should establish a restaurant in your community. Provide a rationale and support for the decision.

Based on the forecasting demand that people live in zip code 20814 to strong demand to buy domino’s pizza. My community has high income and they prefer specialty pizza such as Domino’s pizza which is expensive, good taste and good quality of product because they don’t care about the price. In my opinion, Domino’s Pizza should establish a restaurant in my community because they have the good strategies and their unique which are different than other pizza. So, Domino’s success, however, is due to the fact that they have been able to differentiate themselves on a very crowded playing field.

According to franchise direct website (2010), Domino’s Pizza, with over 9000 units around the world, is one of the leading pizza delivery companies in the US and operates in 50 other countries. Domino’s Pizza brand is one of the most widely-recognized consumer brands in the world. Strong brand image results in a loyal customer base and also helps the company leverage its brand strength to introduce new products. The new pizza, which has a new sauce and cheese combination and herb- and garlic-flavored crust, has proved to be a success as Domino’s more than doubled their fourth quarter profit last year. For the first quarter of 2010 sales surged 18.4% to $381.1 million in the US.

References
Bundle unbiased, data-driven rating (2011). Domino’s pizza company. Retrieved on October 24, 2012 from http://www.bundle.com/merchant/detail/dominos-pizza-bethesda-md-3811080/#customers Dean. G. (2010), Domino pizza beyond the dough. Retrieved on October 26, 2012 from http://marketography.com/2010/03/09/dominos-pizza-beyond-the-dough/ Franchisedirect.com(2010), Pizza franchise Industry report. Retrieved on oct,26 2012 from http://c1176552.r52.cf0.rackcdn.com/pizza-franchise-industry-report.pdf McGuigan, J. R., Moyer, R. C.,& Harris, F. H. D. (2008). Managerial economics: Applications, strategy, and tactics (12th ed.). Mason, OH: South-Western Cengage Learning

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