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Chapter 14 Part 3

# Chapter 14 Part 3 - Chapter 14 Decision Analysis Part 3...

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Chapter 14 Decision Analysis – Part 3

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Restaurant Decision A company plans to open a restaurant/bar in Newark. It is considering 3 locations, A, B and C. Location A is furthest from campus, B is next closest and C is adjacent to the campus. The closer to campus, the greater the chance the restaurant will NOT get a liquor license– which will greatly impact revenues. The company plans to request a special vote to obtain a license. The vote could be favorable or unfavorable.
Restaurant Decision The following payoff table shows the potential revenue for each location given the vote outcome: Location Favorable Unfavorable A 60 50 B 80 30 C 100 0

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Restaurant Decision If the company has determined that the likelihood of a favorable vote is .55 and unfavorable is .45, then EMVs could be calculated as follows: EMV A = 60(.55) + 50(.45) = EMV B = 80(.55) + 30(.45) = EMV C = 100(.55) + 0(.45) =
Restaurant Decision - EVPI If the company has determined that the likelihood of a favorable vote is .55 and unfavorable is .45, then the EVPI could be calculated as follows: EVPI = EPPI – EMV EVPI = (100)(.55) + (50)(.45) – 57.5 = EVPI =

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Sensitivity Analysis In many cases, probabilities and payoffs are based on subjective assessments and can vary over time. Sensitivity analysis can be used to determine how changes to these inputs impact your decision If a small change in one of the inputs causes a change in the recommended decision alternative, extra effort and care should be taken in estimating the input value. The inverse is true as well!
Assume a reversal of the likelihoods from our restaurant example: Favorable = .45, Unfavorable = .55. Now EMVs could be calculated as follows:

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Chapter 14 Part 3 - Chapter 14 Decision Analysis Part 3...

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