through experiments on a model of the system without any interference on the real
system. Thus, simulation bypasses complex mathematical analysis.
13.3.11 Decision Theory
Many managers have to take complex decisions, while still uncertain about several
factors. For instance, managers sanction capital investments with incomplete or
uncertain information about the product potential demand. Important decisions at
national level are often made, again with imprecise knowledge available about the
future, even when such choices could affect the public for several years or decades.
Decision theory plays a significant role in helping managers take better decisions
when future conditions are uncertain.
As an example, consider a concrete block manufacturing company that has to
select the best among several alternative methods of expanding its production to
meet the increased market demand. There could be the following three viable
alternatives:
(1) Expand the existing plant.
(2) Build a new plant.
(3) Subcontract extra production to other block manufacturing companies.
Having identified the feasible alternatives, the next step is to list the future events
(called states of nature) that may occur. In this problem, the greatest uncertainty is
about the future demand of concrete blocks. The various future events related to
demand can be
(a) high demand,
(b) moderate demand,
(c) low demand,
(d) no demand.
The expected return or payoff in rupees associated with each state of nature is
then determined and the decision resulting in the highest payoff is taken.
Decision theory deals with three classes of decision-making:
1. Under conditions of certainty: With complete certainty about the future, there is
only one state of nature. However, very few business situations will ever fall into
this category.
2. Under conditions of risk: Here, there are several states of nature, but sufficient
information is available to assign probability to each of the possible states.
3. Under conditions of uncertainty: Here again, there are several states of nature,
but there is little or no information about the various states, not even sufficient
knowledge to assign probabilities to them.
This topic is dealt in more detail in Chap. 16.
13.3 Types of Mathematical Models
365
system. Thus, simulation bypasses complex mathematical analysis.
13.3.11 Decision Theory
Many managers have to take complex decisions, while still uncertain about several
factors. For instance, managers sanction capital investments with incomplete or
uncertain information about the product potential demand. Important decisions at
national level are often made, again with imprecise knowledge available about the
future, even when such choices could affect the public for several years or decades.
Decision theory plays a significant role in helping managers take better decisions
when future conditions are uncertain.
As an example, consider a concrete block manufacturing company that has to
select the best among several alternative methods of expanding its production to
meet the increased market demand. There could be the following three viable
alternatives:
(1) Expand the existing plant.
(2) Build a new plant.
(3) Subcontract extra production to other block manufacturing companies.
Having identified the feasible alternatives, the next step is to list the future events
(called states of nature) that may occur. In this problem, the greatest uncertainty is
about the future demand of concrete blocks. The various future events related to
demand can be
(a) high demand,
(b) moderate demand,
(c) low demand,
(d) no demand.
The expected return or payoff in rupees associated with each state of nature is
then determined and the decision resulting in the highest payoff is taken.
Decision theory deals with three classes of decision-making:
1. Under conditions of certainty: With complete certainty about the future, there is
only one state of nature. However, very few business situations will ever fall into
this category.
2. Under conditions of risk: Here, there are several states of nature, but sufficient
information is available to assign probability to each of the possible states.
3. Under conditions of uncertainty: Here again, there are several states of nature,
but there is little or no information about the various states, not even sufficient
knowledge to assign probabilities to them.
This topic is dealt in more detail in Chap. 16.
13.3 Types of Mathematical Models
365