Patricia is researching venues for a restaurant business. She is evaluating three major attributes that she considers important in her choice: taste, location, and price. The value she places on each attribute, however, differs according to what type of restaurant she is going to start. If she opens a restaurant in a suburban area of Los Angeles, then taste is the most important attribute, three times as important as location, and two times as important as price. If she opens a restaurant in the Los Angeles metropolitan area, then location becomes three times as important as taste and two times as important as price. She is considering two venues, respectively, a steak restaurant and a pizza restaurant, both of which are priced the same. She has rated each attribute on a scale of 1 to 100 for each of the two different types of restaurants.
Attribute Steak Restaurant Pizza Restaurant
Taste 80 70
Location 55 80
Price 65 50
Show all of your calculations and processes. Describe your answer for each question in complete sentences.
Which of the two options should Patricia pursue if she wants to open a restaurant in a suburban area of Los Angeles? Calculate the total expected utility from each restaurant option and compare. Graph is not required. Describe your answer, and show your calculations.
Which of the two options should she pick if she plans to open a restaurant in the Los Angeles metropolitan area? Describe your answer, and show your calculations.
Which option should she pursue if the probability of finding a restaurant venue in a suburban area can be reliably estimated as 0.7 and in a metropolitan area as 0.3? Describe your reasoning and show your calculations.
Provide a description of a scenario in which this kind of decision between two choices, based on weighing their underlying attributes, applies in the âreal-worldâ business setting. Furthermore, what are the benefits and drawbacks, if any, to this method of decision making?
Patricia is researching venues for a restaurant business. She is evaluating three major attributes that she considers important in her choice: taste, location, and price. The value she places on each attribute, however, differs according to what type of restaurant she is going to start. If she opens a restaurant in a suburban area of Los Angeles, then taste is the most important attribute, three times as important as location, and two times as important as price. If she opens a restaurant in the Los Angeles metropolitan area, then location becomes three times as important as taste and two times as important as price. She is considering two venues, respectively, a steak restaurant and a pizza restaurant, both of which are priced the same. She has rated each attribute on a scale of 1 to 100 for each of the two different types of restaurants.
Attribute Steak Restaurant Pizza Restaurant
Taste 80 70
Location 55 80
Price 65 50
Show all of your calculations and processes. Describe your answer for each question in complete sentences.
Which of the two options should Patricia pursue if she wants to open a restaurant in a suburban area of Los Angeles? Calculate the total expected utility from each restaurant option and compare. Graph is not required. Describe your answer, and show your calculations.
Which of the two options should she pick if she plans to open a restaurant in the Los Angeles metropolitan area? Describe your answer, and show your calculations.
Which option should she pursue if the probability of finding a restaurant venue in a suburban area can be reliably estimated as 0.7 and in a metropolitan area as 0.3? Describe your reasoning and show your calculations.
Provide a description of a scenario in which this kind of decision between two choices, based on weighing their underlying attributes, applies in the âreal-worldâ business setting. Furthermore, what are the benefits and drawbacks, if any, to this method of decision making?
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Using the data below, I need answers to the following questions:
a) Using the data in Table 1, specify a linear functional form for the demand for Combination 1 meals, and run a regression to estimate the demand for Combo 1meals.
b) Using statistical software (Excel), estimate the parameters of the empirical demand function specifiedin part a.Write your estimated industry demand equation.
c) Evaluate your regression results by examining signs of parameters, p-values, and the R2.
d) Discuss how the estimation of demand might beimproved.
e) If the owner plans to charge a price of 4.15 for a Combination 1 meal and spend $18,000 per week on advertising, how many Combination 1 meals do you predict will be sold each week?
f) If the owner spends $18,000 per week on advertising, write the equation for the inverse demand function. Then, calculate the demand price for 50,000 Combination meals.
Estimation and Analysis of Demand for Fast Food Meals
You work for PriceWatermanCoopers as a market analyst. PWC has been hired by the owner of two Burger King restaurants located in a suburban Atlanta market area to study the demand for its basic hamburger meal packageâreferred to as âCombination 1" on its menus. The two restaurants face competition in the Atlanta suburb from five other hamburger restaurants (three MacDonaldâs and two Wendyâs restaurants) and three other restaurants serving âdrive-throughâ fast food (a Taco Bell, a Kentucky Fried Chicken, and a small family-owned Chinese restaurant).
The owner of the two Burger King restaurants provides PWC with the data shown in Table 1. Q is the total number of Combination 1 meals sold at both locations during each week in 1998. P is the average price charged for a Combination 1 meal at the two locations. [Prices are identical at the two Burger King locations.] Every week the Burger King owner advertises special price offers at its two restaurants exclusively in daily newspaper advertisements. A is the dollar amount spent on newspaper ads for each week in 1998. The owner could not provide PWC with data on prices charged by other competing restaurants during 1998. For the one-year time period of the study, household income and population in the suburb did not change enough to warrant inclusion in the demand analysis.
TABLE 1: Weekly Sales Data for Combination 1 Meals (1998)
week Q P A week Q P A
1 | 51,345 | 2.78 | 4,280 | 27 | 78,953 | 2.27 | 21,225 |
2 | 50,337 | 2.35 | 3,875 | 28 | 52,875 | 3.78 | 7,580 |
3 | 86,732 | 3.22 | 12,360 | 29 | 81,263 | 3.95 | 4,175 |
4 | 118,117 | 1.85 | 19,250 | 30 | 67,260 | 3.52 | 4,365 |
5 | 48,024 | 2.65 | 6,450 | 31 | 83,323 | 3.45 | 12,250 |
6 | 97,375 | 2.95 | 8,750 | 32 | 68,322 | 3.92 | 11,850 |
7 | 75,751 | 2.86 | 9,600 | 33 | 71,925 | 4.05 | 14,360 |
8 | 78,797 | 3.35 | 9,600 | 34 | 29,372 | 4.01 | 9,540 |
9 | 59,856 | 3.45 | 9,600 | 35 | 21,710 | 3.68 | 7,250 |
10 | 23,696 | 3.25 | 6,250 | 36 | 37,833 | 3.62 | 4,280 |
11 | 61,385 | 3.21 | 4,780 | 37 | 41,154 | 3.57 | 13,800 |
12 | 63,750 | 3.02 | 6,770 | 38 | 50,925 | 3.65 | 15,300 |
13 | 60,996 | 3.16 | 6,325 | 39 | 57,657 | 3.89 | 5,250 |
14 | 84,276 | 2.95 | 9,655 | 40 | 52,036 | 3.86 | 7,650 |
15 | 54,222 | 2.65 | 10,450 | 41 | 58,677 | 3.95 | 6,650 |
16 | 58,131 | 3.24 | 9,750 | 42 | 73,902 | 3.91 | 9,850 |
17 | 55,398 | 3.55 | 11,500 | 43 | 55,327 | 3.88 | 8,350 |
18 | 69,943 | 3.75 | 8,975 | 44 | 16,262 | 4.12 | 10,250 |
19 | 79,785 | 3.85 | 8,975 | 45 | 38,348 | 3.94 | 16,450 |
20 | 38,892 | 3.76 | 6,755 | 46 | 29,810 | 4.15 | 13,200 |
21 | 43,240 | 3.65 | 5,500 | 47 | 69,613 | 4.12 | 14,600 |
22 | 52,078 | 3.58 | 4,365 | 48 | 45,822 | 4.16 | 13,250 |
23 | 11,321 | 3.78 | 9,525 | 49 | 43,207 | 4.00 | 18,450 |
24 | 73,113 | 3.75 | 18,600 | 50 | 81,998 | 3.93 | 16,500 |
25 | 79,988 | 3.22 | 14,450 | 51 | 46,756 | 3.89 | 6,500 |
26 | 98,311 | 3.42 | 15,500 | 52 | 34,592 | 3.83 | 5,650 |