Decision modeling and analysis | BUS 461 | Ashford University

 

Read Case 6.3: Electronic Timing System for Olympics on pages 275-276 of the textbook.  For this assignment, you will  assess and use the correct support tool to develop a decision tree as described in Part “a” of Case 6.3. Analyze and apply the best decision making process to provide answers and brief explanations for parts “a”, “b”, “c”, and “d”. The answers and explanations can be placed in the same Excel document as the decision tree.

  1. Develop a decision tree that can be used to solve Chang’s problem. You can assume in this part of the problem that she is using EMV (of her net profit) as a decision criterion. Build the tree so that she can enter any values for p1, p2, and p3 (in input cells) and automatically see her optimal EMV and optimal strategy from the tree.
  2. If p2 = 0.8 and p3 = 0.1, what value of p1 makes Chang indifferent between abandoning the project and going ahead with it?
  3. How much would Chang benefit if she knew for certain that the Olympic organization would guarantee her the contract? (This guarantee would be in force only if she were successful in developing the product.) Assume p1 = 0.4, p2 = 0.8, and p3 = 0.1
  4. Suppose now that this is a relatively big project for Chang. Therefore, she decides to use expected utility as her criterion, with an exponential utility function. Using some trial and error, see which risk tolerance changes her initial decision from “go ahead” to “abandon” when p1 = 0.4, p2 = 0.8, and p3 = 0.1.

In your Excel document,

  1. Develop a decision tree using the most appropriate support tool as described in Part a.
  2. Calculate the value of p1 as described in Part b. Show calculations.
  3. Calculate the possible profit using the most appropriate support tool as described in Part c. Show calculations.
  4. Calculate risk tolerance as described in Part d. Show calculations.

CASE 6.3

 Sarah Chang is the owner of a small electronics company. In six months, a proposal is due for an electronic timing system for the next Olympic Games. For several years, Chang’s company has been developing a new microprocessor, a critical component in a timing system that would be superior to any product currently on the market. However, progress in research and development has been slow, and Chang is unsure whether her staff can produce the microprocessor in time. If they succeed in developing the microprocessor (probability p1), there is an excellent chance (probability p2) that Chang’s company will win the $1 million Olympic contract. If they do not, there is a small chance (probability p3) that she will still be able to win the same contract with an alternative but inferior timing system that has already been developed. 

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