Advantages of Payoff Matrix for Decision Making

DECISION SUPPORT
TOOL
STUDENT ID:
[Pick the date]

Question 1
(a) The use of payoff matrix for making decision offers the following advantages (Flick,
2015).
 It highlights the associated payoff under different choices related to the various future
states which is quite helpful in decision making.
 Further, it offers the flexibility to the decision maker to make decision as per the
underlying decision rule such as optimist, pessimist. This allows customisation of
decision as per the decision maker while maintaining objectivity.
In order to form the payoff matrix, the first step is to outline the underlying choices available
with the decision maker along with the possible future states. Additionally, the probability of
the states also needs to be captured. Further, the payoff under different choice and state
combination needs to be represented in the matrix form (Medhi, 2016).
(b) Decision trees tend to have an edge over payoff matrix in certain scenarios. This is
especially the case when the decision maker needs to indulge in sequential decision
making. In such situations, the utility of payoff matrix tends to be limited. Decision tree
evaluation is based on node based approach where decision at every node can be analysed
to determine the likely tree and introduce changes based on intermediate changes (Hillier,
2015).
(c) (1) Payoff matrix
(2) Optimist technique
Maximax has observed for optionROB1 and hence, George being optimist will adopt ROB1.
(3) Pessimist technique
2

Maximin has observed for None and hence, George being pessimist will not buy robots.
(4) Lapalce criterion technique
Highest average has observed for robot 1 as well as for robot 2 and hence, George can buy
either of the given two robots.
(5) Regret criterion technique
Lowest value has observed for robot 2 and hence, George can buy robot 2 under this
technique.
(6) Expected monetary value technique
Highest value has observed for robot 1 and hence, George can buy robot 1 under this
technique.
(7) EVPI
Question 2
3

(a) Various notation has been used to find the revised prior probabilities
(b) Favourable market and positive scenario, then the posterior probabilities
P(S1 │Y1)=(0.6*0.9)/((0.6*0.9)+(0.4*0.8))=0.63
(c) EVSI& ENGSI
(d) EVPI
Question 3
(1) MONTE CARLO SIMULATION
For per day profit and average profit of flight
4