MODULE A
DISCUSSION QUESTIONS
4.
EMV
is defined as the
expected monetary value
. The
EMV
is the expected or average return that
we would realize if we were to repeat the decision an infinite number of times.
“Expected value under certainty” is the expected or average return that we would realize if
we were to repeat the decision an infinite number of times, each time having “perfect” or
complete information and making the “best” possible decision based on that information.
EVPI
is
defined as the
expected value of
perfect information
.
EVPI
is equal to the difference between
EMV
(the expected or average return given that we were to make the decision based on current
or available information) and “expected value under certainty” and is the
maximum
amount we
would be willing to pay for additional (perhaps, perfect) information.
Determination of
EVPI
is useful any time the manager has the option of expending additional
resources to acquire additional information and making the decision using currently available
information.
9.
Maximax
is the optimistic criterion. It maximizes the maximum outcome.
10.
Maximin
is the pessimistic criterion. It maximizes the minimum outcome.
END-OF-MODULE PROBLEMS
A.1
States of Nature
Alternatives
Very
Favorable
Market
Average
Market
Unfavorable
Market
Row
Minimum
Row
Maximum
Row
Average
Large plant
$275,000
$100,000
–$150,000
–150,000
275,000
75,000
Small plant
$200,000
$60,000
–$10,000
–10,000
200,000
83,333
Overtime
$100,000
$40,000
–$1,000
–1,000
100,000
46,333
Do nothing
$0
$0
$0
0
0
0
maximin
maximax
equally likely
(a)
Large plant
(b)
Do nothing
(c)
Small plant
A.2
(a)
Market
Size
of First
Station
Good
Market
Fair
Market
Poor
Market
Row
Minimum
Row
Maximum
Row
Average
Small
50,000
20,000
–10,000
–10,000
50,000
20,000
Medium
80,000
30,000
–20,000
–20,000
80,000
30,000
Large
100,000
30,000
–40,000
–40,000
100,000
30,000
Very large
300,000
25,000
–160,000
–160,000
300,000
55,000
maximin
maximax
equally
likely
(b)
Maximax decision: very large station
(c)
Maximin decision: small station
Quantitative Module A: Decision-Making Tools
1