GE CEE Presentation Edited (2)

8/3/2019 GE CEE Presentation Edited (2)

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Decision theory

MBA (PRIST) 2nd SEM 2010-2012 BATCH (MSRMI)

Infrastructure Finance Media

Presented by:Devendra singh

John maryMazharNeerajmujbir


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IntroductionBasic managerial functions i.e. planning, organizing,monitoring, and controlling require to take a number ofdecisions in day today business scenario

Decisions are based on the objective of maximization of

profit and minimization of loss in any of the decision makingprocess

Rational decision making process involves impact ofexternal factors like Government policies, monitory framework, attitude & interest of stock holders, employees tobring out the best of decision maker and effective decisionmaking


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Definitiondecision theory

A process which results in the selection from a setof alternative courses, that course of action whichis considered to meet the objectives of the decisionproblem more satisfactorily then others as judged

by the decision makers.

Or

The process of logical and quantitative analysis of

all factors that influences the decision problem,assists the decision maker in analyzing theseproblems with several courses of action andconsequences.


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Essential characteristics

Decision alternatives:-it is defined as the course ofaction on the basis of decision alternatives andstrategies given by the decision maker

State of nature:-these are the possible future

conditions(consequences, events or scenario) onthe basis of decision alternatives,and are not incontrol of the decision maker

Pay off:-a numerical value (outcome)resulting fromeach possible alternative and state of nature iscalled pay off


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Decision processThe decision making process involves following steps:-

1:- Problem identification and definition

2:- List of all possible future events, called state of nature,which can occur in the context of decision problem

3:-Identification of all the courses of action (alternativesdecision choices) that are available to the decisionmaker

4:- Expressing the payoffs resulting from each pair of

course of action from and state of nature5:- Application of an appropriate mathematical decision

theory model to select the best of course of action onthe basis of effectiveness to get the optimal payoff


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Decision making environments

1. Decision-making under conditions of

certainty.

2. Decision-making under conditions ofuncertainty.

3. Decision-making under condition ofrisk.

4. Decision-making under conditions ofconflict.


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Decision making under certainty Certainty implies the complete knowledge of

(perfect information) of consequence of everydecision choice (course of action alternative).

Therefore the decision maker will select analternative that yields the largest return (payoff) for

the known future (state of nature)Alternatives States of nature(product demand)

High Moderate Low Nil

Expand Rs 50,000 Rs 25,000 -Rs25,000 -Rs45,000

Construct Rs 70,000 Rs 30,000 -Rs40,000 -Rs80,000

Subcontract Rs 30,000 Rs 15,000 -Rs 1,000 -Rs10,000


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Decision making under uncertainty uncertainty implies, the decision-maker has a

knowledge about the state(future) that happens butlacks the knowledge about the probabilities of theiroccurrence.

criterias are available which can help the decision-

maker in uncertainty:-1.Maximax Criterion or Criterion of Optimism.

2.Maximin Criterion or Criterion of Pessimism.

3.Minimax Regret Criterion(Savage Criterion) .

4.Hurwicz Criterion(Criterion of Realism).

5.Laplace Criterion or Criterion of Rationality

(Bayes Criterion).


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Maximax criterion or criteria of optimism

This criterion provides the decision-maker with

optimistic criterion. He finds the maximum possiblepayoff for each possible alternative and thenchooses the alternative with maximum payoff withinthe group.

Alternatives States of nature(product demand)

HighRs

ModerateRs

LowRs

NilRs

Maximumof row

Rs

Expand 50,000 25,000 -25,000 -45,000 50,000Construct 70,000 30,000 -40,000 -80,000

Subcontract 30,000 15,000 -1,000 -10,000 30,000

Maximum payoff= Rs 70,000


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This criterion provides the decision-maker with pessimisticcriterion.

The decision-maker maximizes his minimum possiblepayoffs.

He finds first the minimum possible payoff for eachalternative and then chooses the alternative with maximumpayoff within the group.

Maximin Criterion or Criterion ofPessimism(Wald Criterion).

Alternatives States of nature(product demand)

HighRs

ModerateRs

LowRs

NilRs

Minimumof rowRs

Expand 50,000 25,000 -25,000 -45,000 -45,000

Construct 70,000 30,000 -40,000 -80,000 -80,000

Subcontract 30,000 15,000 -1000 -10,000 -10,000

R C i i


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Minimax Regret Criterion(Savage Criterion) .

L.J.Savage developed the decision criterion.

He pointed out that the decision-maker might experience regretafter the decision has been made and the states of nature i.e.events have occurred.

Thus attempt to minimize regret before actually selecting aparticular alternative(strategy) should be done by decision-maker.

The basic steps involved in this criterion are:

Determine the amount of regret corresponding to each eventfor every alternative. The regret for jth event corresponding to ith

alternative is given by: ith regret=(maximum payoff - ith payoff)for jth event.

Determine the maximum regret amount for each alternative.

Choose the alternative which corresponds to the minimum ofthe maximum regrets.


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This table shows that the company will minimizeits regret to Rs 35,000 by selecting alternativeExpand

Alternative States of nature(product demand)

High(Rs) ModerateRs

Low(Rs) Nil(Rs) Maximumof rowRs

Expand 20,000 5,000 24,000 35,000 35,000

Construct 0 0 39,000 70,000 70,000

Subcontract 40,000 15,000 0 0 40,000

Minimax=35,000


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Hurwicz Criterion(Criterion of Realism)/WeightedAverage Criterion.

It is a compromise between the maximax and maximin

decision criteria. It is based on Hurwiczs concept of coefficient of optimism(or

pessimistic)

It allows the decision-maker to take into account both the

maximum and minimum for each alternative and assign themweights according to its degree of optimism(or pessimism).Thealternative which maximizes the sum of weighted payoffs isthen selected.

The criterion of realism consists of the following steps:

Choose an appropriate degree of optimism ,so that(1-)represents the degree of pessimism. is called coefficient orindex of optimism.

Determine the maximum as well as minimum of eachalternative and obtain.

P=.maximum +(1-).minimum


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Choose the alternative that yields the maximumvalue of P.

Assume =0.8Alternativ

e

States of nature(product demand)

HighRs

ModerateRs

LowRs

NilRs

Maximumof rowRs

Minimumof rowRs

P=.max+(1-).min

Expand 50,000 25,000 -25,000 -45,000 50,000 -45,000 31,000

Construct 70,000 30,000 -40,000 -80,000 70,000 -80,000 40,000

Subcontract

30,000 15,000 -1000 -10,000 30,000 -10,000 22,000

When =0,the criterion is too pessimistic.When =1,it is too optimistic.A value of =1/2 seems to be a reasonable choice.


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Laplace Criterion or Criterion ofRationality(Bayes Criterion).

It is based upon what is known as the principle ofinsufficient reason.

Since the probabilities associated with the occurrence ofvarious events are unknown, there is not enoughinformation to conclude that these probabilities will be

different. This criterion assigns equal probabilities to all the events

of each alternative decisions and selects the alternativeassociated with the maximum expected payoff

n denotes the number of events.Ps denotes the payoffs.

Expected value is represented by:

1/n(P1+P2+.+Pn)


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Thus the alternative subcontract results inmaximum average payoff of Rs 8,500.

Alternatives States of nature(Product demand)

HighRs

ModerateRs

LowRs

NilRs

Expected payoffRs

Expand 50,000 25,000 -25,000 -45,000 1000/4[50+25-25-

45]= -1,200Construct 70,000 30,000 -40,000 -80,000 1000/4[70+30-40-

80]= -5,000

Subcontract 30,000 15,000 -1000 -10,000 1000/4[30+15-1-10]= 8500


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Decision making under condition ofrisk

Most business decisions may have to be made underconditions of risk.

More than one states of nature exist and the decision-makerhas sufficient information to assign probabilities to each ofthese states.

These probabilities could be obtained from the past recordsor from simply the subjective judgment of the decision-maker.

Number of decision criteria are available, some are:

Expected Value Criterion. Expected Opportunity Loss Criterion.

Expected Value of Perfect Information.


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Expected value criterion:

This criterion requires the calculation of theexpected value of each decision alternative which is

the sum of the weighted payoffs for that alternative,where the weights are the probabilities assigned tothe states of the nature that can happen. Alsocalled as expected monetary value(EMV)criterion.

Expected opportunity loss(EOL) criterion: It is an alternative approach is to minimize expected

opportunity loss.EOL represents the amount bywhich maximum possible profit will be reduced

under various possible stock action. The course ofaction that minimizes this losses or reductions isthe optimal decision alternatives.

A li ti


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ApplicationDecision making

Select the best from among several job offers.

Select the most profitable investment portfolio.

Select the best way to build a modern electroniccomponent.

Determine the number of personal computers(PCs) to orderfor an office supply store.

Determine whether or not to expand a medical ormanufacturing facility.

Determine if a large plant, small plant, or no plant should bebuilt.

Decide if it is worthwhile to hire a marketing research teamto gather additional data.


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application contd.

Decide whether to lease, sub-contract or manufacture orselect a quality control plan.

Decide whether to invest in a new plant, equipment, etc.

Decide about the area of design and development of newand improved product and equipment.


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Decision tree A decision tree analysis involves the construction

of a diagram that shows, at a glance, whendecisions are expected to be made in sequence,their possible consequences, and what are theresultant payoffs. The results of the computationscan be shown directly on the trees.

A decision tree consists of nodes, branches,probability estimates, and payoffs.

There are two types of nodes:

1. Decision nodes (also called act nodes)

2. Chance nodes (also called event nodes)


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A decision nodes is usually represented by a squareand indicates places where a decision-maker mustselect one alternative course of action among the

available actions. The chance node is represented by a circle and

indicates a point at which the decision-maker willdiscover the response to his decision.

Branches emanate from and connect various nodesand either decisions or states of nature.

There are two types of branches:

1. Decision branches2. Chance branches


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Each branch leading away from a decision noderepresents a course of action or strategy that canbe chosen at a decision point, whereas a branch

leading away from a chance node represents thestate of nature of a set of chance events.

Any branch that makes the end of the decisiontree, i.e., it is not followed by either a decision orchance, is called a terminal branch.

The payoffscan be positive (i.e. revenue sales) ornegative (i.e. expenditure or cost) and they can be

associated either with decision or chancebranches.


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Steps in decision tree analysis:-

Identify the decision points and the alternative course ofaction at each decision point systematically.

At each decision point, determine the probability and payoffassociated with each course of action.

Commencing from the extreme right end, compute the

expected payoffs(EMV)for each course of action. Choose the course of action that yields the best payoff for

each of the decisions.

Proceed backwards to the next stage of decision points.

Repeat above steps till the first decisions is reached. Finally, identify the courses of action to be adopted from the

beginning to the end under different possible outcomes forthe situation as a whole.

Advantages of decision tree


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Advantages of decision treeapproach

It structures the decision process and helps decision-making in an orderly, systematic and sequential manner.

It requires the decision-maker to examine all possibleoutcomes, whether desirable or undesirable.

It communicates the decision-making process to others in

an easy and clear manner, illustrating each assumptionabout the future.

It displays the logical relationship between the parts of acomplex decision and identifies the time sequence in whichthe various actions and subsequent events would occur.

It is especially useful in situations wherein the initial decisionand its outcome affects the subsequent decisions.

It can be applied in various fields such as introduction ofnew product, marketing, make or buy decisions, investment

decision etc.


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Disadvantages of decision treeapproach

Decision tree diagrams more complicated as the number ofthe decisions alternatives increases and more variables areintroduced.

It becomes highly complicated when interdependentalternatives and dependent variables are present in the

problem.

It assumes the utility of money is linear with money.

It analyses the problem in terms of expected values andthus yield an average valued solution.

There is often inconsistency in assigning probabilities fordifferent events.


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