Business Analytics

A corporation plans on building a maximum of 11 new stores in a large city. They will build these stores in one of three sizes for each location – a convenience store (open 24 hours), standard store, and an expanded services store. The convenience store requires $4.125 million to build and 30 employees to operate. The standard store requires $8.25 million to build and 15 employees to operate. The expanded-services store requires $12.375 million to build and 45 employees to operate. The corporation can dedicate $82.5 million in construction capital, and 300 employees to staff the stores. On the average, the convenience store nets $1.2 million annually, the standard store nets $2 million annually, and the expanded services store nets $2.6 million annually.

  1. How many of each should they build to maximize income?
  2. What is the maximum income they will earn based on your answer in A?
  3. Which kind of store – convenience, standard, expanded services – will contribute the most to corporate income?
  4. Which kind of store – convenience, standard, expanded services – will contribute the least to corporate income?
  5. Identify any constraints which are not fully utilized – which are they?

You are devising a regression to value farms 100 acres or more. Data is in course files and is titled Test II bsad 2304 data spring 2021.xlsx. Your dependent variable – price per acre – will be explained by

  • Dummy variables(1=Yes) describing the property that include
    • is there a creek?
    • Is the land cultivated for farming (instead of suitable for hunting)
    • Does it have access to water lines
    • Is it heavily treed
    • Is it bordered by an asphalt road
  • Along with a continuous variables: the number of wells
  • And market characteristics for the county where the land was sold including:
    • average rainfall
    • average high temp
    • average low temp
    • % college grads
    • Unemployment rate
    • county population
    • county population/sq mi
    • average income

Run a regression that explains price per acre using all your independent terms. Use your regression results to answer the following questions:

  1. Of water lines, the number of wells, and the presence of creeks, which statistically affect the price per acre at the 90% level or greater? If your goal is to make the most money, would you rather have more wells, access to a creek, or access to water lines? Rank your answer by calculating the dollar difference per acre between your choices.
  2. What’s better: land that is heavily treed or land that is cultivated?  Calculate the dollar difference per acre.  What do you think drives this difference?
  3. What is your most significant variable when explaining land value. Explain why you think this drives value.  What is another variable that might contribute to price/acre for the same reason as your most significant variable?
  4. Comment on the accuracy of this statement: The further north you go, the more valuable the land.
  5. Parcel A gets 60 inches of rain per year. Parcel B gets only 50 inches of rain per year.  Which parcel is worth more? What is the price difference per acre?
  6. Kent County has 726 people or .9 people per mile. Taylor County has 137,640 or 143.64 people per square mile? Does this wide difference in population matter when pricing land? Explain.