Decision Support Tools

DECISION SUPPORT TOOLS
STUDENT ID:
[Pick the date]

Question 1
(a) A key advantage associated with the use of payoff matrix is that the decision maker can
fully understand how changing the decision or choice would impact the payoff which
would enable the decision maker make the best choice after comparing it with other
available choices. In order to form a payoff matrix, it is imperative that all the possible
choices must be listed down along with the underlying probability associated for the
occurrence of each. Finally, the payoff for the different states and choices are multiplied
by the respective probability of obtain the payoff matrix comprising of payoff under
differ scenarios (Fehr & Grossman,2016).
(b) A key difference between payoff matrix and decision tree is that the latter tends to show
the various intermediate decisions and the associated choices with these. The payoff
matrix tend to represent the final outcome associated with a given choice. Hence, in
scenarios where the intermediate decisions are vital or dynamic in nature, the decision
tree as a technique would be more useful than payoff matrix (Eriksson & Kovalainen,
2015).
(c) George has three options: One is to buy ROB1, second is to buy ROB 2, third is not to
buy any robots or say do nothing.
1) Payoff Matrix
2) George: Optimist
Maximum value of the maximum payoff is for Robot 1 and hence, he should buy ROB1.
3) George: Pessimist
2

Maximum value of the minimum value comes out for option third and hence, George should
do nothing.
4) George follows Laplace Criterion
The average comes out to be same for ROB1 and ROB2 and hence, George can buy either of
the robots.
5) George follows Criterion of regret
The optimum action is to buy Robot 2 because it has minimum value of the maximum
opportunity loss.
6) Optimum action and expected return for favourable market probability 0.6
3

The optimum action is to buy ROB 1 because it has maximum expected return.
Therefore,optimum action is to purchase Robot 1and expected return is $14,000.
7) Expected value of perfect information
Question 2
(a) Revised prior probabilities
Assumption:
S1 = favourable market, S2 = unfavourable market
Y1 =positive, Y2= negative
Hence, revised prior probabilities (Excel)
(b) Posterior probabilities P (S1 | Y1) = 0.6279 as evident from the computations carried out
above.
4