k.fedra ‘97 decision support systems multiple objectives, multiple criteria and valuation in...

K.Fedra ‘97

Decision Support SystemsDecision Support SystemsDecision Support SystemsDecision Support Systems

multiple objectives, multiple multiple objectives, multiple criteria and valuation in criteria and valuation in

environmental DSS environmental DSS

multiple objectives, multiple multiple objectives, multiple criteria and valuation in criteria and valuation in

environmental DSS environmental DSS

K.Fedra ‘97

DSS DefinitionDSS DefinitionDSS DefinitionDSS Definition

A DSS is a computer based A DSS is a computer based

problem solving system that problem solving system that

assists assists choicechoice between between

alternativesalternatives in complex and in complex and

controversialcontroversial domains. domains.

A DSS is a computer based A DSS is a computer based

problem solving system that problem solving system that

assists assists choicechoice between between

alternativesalternatives in complex and in complex and

controversialcontroversial domains. domains.

K.Fedra ‘97

Decision makingDecision makingDecision makingDecision making

AA choice choice between between alternativesalternativesrequires a requires a rankingranking of alternatives by of alternatives by

the decision makers preferences:the decision makers preferences:the preferred alternative mustthe preferred alternative must• satisfy the constraintssatisfy the constraints• maximise the decision makers utility maximise the decision makers utility

functionfunction

AA choice choice between between alternativesalternativesrequires a requires a rankingranking of alternatives by of alternatives by

the decision makers preferences:the decision makers preferences:the preferred alternative mustthe preferred alternative must• satisfy the constraintssatisfy the constraints• maximise the decision makers utility maximise the decision makers utility

functionfunction

K.Fedra ‘97


rankingranking of alternatives is trivial with of alternatives is trivial with

a single attribute (e.g., cost):a single attribute (e.g., cost):

select the alternative with the select the alternative with the minimum costminimum cost

provided the attribute can be measured provided the attribute can be measured

without errorwithout error..

rankingranking of alternatives is trivial with of alternatives is trivial with

a single attribute (e.g., cost):a single attribute (e.g., cost):

select the alternative with the select the alternative with the minimum costminimum cost

provided the attribute can be measured provided the attribute can be measured

without errorwithout error..

K.Fedra ‘97

Decision support paradigmsDecision support paradigmsDecision support paradigmsDecision support paradigms

Multiple attributesMultiple attributes

multiple objectivesmultiple objectives

multiple criteriamultiple criteria

trade-off, compromise, trade-off, compromise,

satisfaction, acceptancesatisfaction, acceptance

Multiple attributesMultiple attributes

multiple objectivesmultiple objectives

multiple criteriamultiple criteria

trade-off, compromise, trade-off, compromise,

satisfaction, acceptancesatisfaction, acceptance

K.Fedra ‘97

Multiple attributesMultiple attributesMultiple attributesMultiple attributes

Criteria:Criteria: problem dimensions problem dimensions relevant for the decisionrelevant for the decision

Objectives: Objectives: the goals to be furtheredthe goals to be furthered criteria to be maximized criteria to be maximized or minimized: or minimized: maxmax f(c) f(c)Constraints:Constraints: bounds for acceptablebounds for acceptable solutions, limit values on solutions, limit values on

criteria criteria

Criteria:Criteria: problem dimensions problem dimensions relevant for the decisionrelevant for the decision

Objectives: Objectives: the goals to be furtheredthe goals to be furthered criteria to be maximized criteria to be maximized or minimized: or minimized: maxmax f(c) f(c)Constraints:Constraints: bounds for acceptablebounds for acceptable solutions, limit values on solutions, limit values on

criteria criteria

K.Fedra ‘97

Multicriteria decision exampleMulticriteria decision exampleMulticriteria decision exampleMulticriteria decision example

set of criteria set of criteria individual criteria may be:individual criteria may be:• cardinal cardinal (numerical):(numerical): distance to employment: 1,2,3,4 ...kmdistance to employment: 1,2,3,4 ...km• ordinal ordinal (symbolic but ordered)(symbolic but ordered) neighborhood: peaceful, active, noisyneighborhood: peaceful, active, noisy• nominalnominal heating system: oil, gas, electricheating system: oil, gas, electric

set of criteria set of criteria individual criteria may be:individual criteria may be:• cardinal cardinal (numerical):(numerical): distance to employment: 1,2,3,4 ...kmdistance to employment: 1,2,3,4 ...km• ordinal ordinal (symbolic but ordered)(symbolic but ordered) neighborhood: peaceful, active, noisyneighborhood: peaceful, active, noisy• nominalnominal heating system: oil, gas, electricheating system: oil, gas, electric

K.Fedra ‘97


rankingranking of alternatives with multiple of alternatives with multiple attributes:attributes:

• collapse attributes into a single collapse attributes into a single attribute (e.g., monetization)attribute (e.g., monetization)

• OR solve the multi-dimensional OR solve the multi-dimensional problemproblem

rankingranking of alternatives with multiple of alternatives with multiple attributes:attributes:

• collapse attributes into a single collapse attributes into a single attribute (e.g., monetization)attribute (e.g., monetization)

• OR solve the multi-dimensional OR solve the multi-dimensional problemproblem

K.Fedra ‘97


the multi-dimensional problemthe multi-dimensional problem

Multi-objective optimisationMulti-objective optimisation

min f(min f(xx))where where XX=(x=(x11, x, x22, ….. ,x, ….. ,xnn))

is the vector of decision variables.is the vector of decision variables.

the multi-dimensional problemthe multi-dimensional problem

Multi-objective optimisationMulti-objective optimisation

min f(min f(xx))where where XX=(x=(x11, x, x22, ….. ,x, ….. ,xnn))

is the vector of decision variables.is the vector of decision variables.

K.Fedra ‘97

Multi-objective optimisationMulti-objective optimisationMulti-objective optimisationMulti-objective optimisation

The vectorThe vector

f(f(XX) = (f) = (f11(x), f(x), f22(x), ….., f(x), ….., f n n(x))(x))

represents the objective function.represents the objective function.

Decision Decision XX11 is considered preferable to is considered preferable to

XX2 2 if f(if f(XX11) .GE. f() .GE. f(XX22) )

andand ffii(x(x11) .GE. f) .GE. fii(x(x22) for all i) for all i

The vectorThe vector

f(f(XX) = (f) = (f11(x), f(x), f22(x), ….., f(x), ….., f n n(x))(x))

represents the objective function.represents the objective function.

Decision Decision XX11 is considered preferable to is considered preferable to

XX2 2 if f(if f(XX11) .GE. f() .GE. f(XX22) )

andand ffii(x(x11) .GE. f) .GE. fii(x(x22) for all i) for all i

K.Fedra ‘97


The The Pareto optimalPareto optimal solution f(x solution f(x**) to) to

min min f(x) f(x)

requires that there is no attainable f(x) requires that there is no attainable f(x) that scores better than f(xthat scores better than f(x**) in at least ) in at least one criterion one criterion i i (f(fii(x) .LT. f(x) .LT. fii(x(x**)) without )) without

worsening all other components of f(xworsening all other components of f(x**))

The The Pareto optimalPareto optimal solution f(x solution f(x**) to) to

min min f(x) f(x)

requires that there is no attainable f(x) requires that there is no attainable f(x) that scores better than f(xthat scores better than f(x**) in at least ) in at least one criterion one criterion i i (f(fii(x) .LT. f(x) .LT. fii(x(x**)) without )) without

worsening all other components of f(xworsening all other components of f(x**))

K.Fedra ‘97

Pareto optimalPareto optimalPareto optimalPareto optimal

an alternative is Pareto optimal or non-an alternative is Pareto optimal or non-dominated, if it is:dominated, if it is:

• best in at least one criterion (better best in at least one criterion (better than any other alternative); than any other alternative);

• or equal to the best in at least one or equal to the best in at least one criterion without being worse in all criterion without being worse in all other criteria.other criteria.

an alternative is Pareto optimal or non-an alternative is Pareto optimal or non-dominated, if it is:dominated, if it is:

• best in at least one criterion (better best in at least one criterion (better than any other alternative); than any other alternative);

• or equal to the best in at least one or equal to the best in at least one criterion without being worse in all criterion without being worse in all other criteria.other criteria.

K.Fedra ‘97


Pareto solutions are efficient (non Pareto solutions are efficient (non improvable), the implied ordering is improvable), the implied ordering is incomplete, i.e., a incomplete, i.e., a partial orderingpartial ordering..

This means that the problem has more This means that the problem has more than one solution which are not directly than one solution which are not directly comparable with each other. comparable with each other.

Pareto solutions are efficient (non Pareto solutions are efficient (non improvable), the implied ordering is improvable), the implied ordering is incomplete, i.e., a incomplete, i.e., a partial orderingpartial ordering..

This means that the problem has more This means that the problem has more than one solution which are not directly than one solution which are not directly comparable with each other. comparable with each other.

K.Fedra ‘97

Multicriteria decisionsMulticriteria decisionsMulticriteria decisionsMulticriteria decisions

A simple example:A simple example:• statement of the problem (objectives)statement of the problem (objectives)• set of alternativesset of alternatives• set of criteriaset of criteria• set of constraints (feasible sub-set)set of constraints (feasible sub-set)• evaluation of alternatives (trade-off)evaluation of alternatives (trade-off)• decision rules, selectiondecision rules, selection

A simple example:A simple example:• statement of the problem (objectives)statement of the problem (objectives)• set of alternativesset of alternatives• set of criteriaset of criteria• set of constraints (feasible sub-set)set of constraints (feasible sub-set)• evaluation of alternatives (trade-off)evaluation of alternatives (trade-off)• decision rules, selectiondecision rules, selection

K.Fedra ‘97


statement of the problem (objectives)statement of the problem (objectives)

• characterises the DM goals characterises the DM goals

• allows identification of alternativesallows identification of alternatives

Buy a new car that is cost efficientBuy a new car that is cost efficient

Alternatives: different modelsAlternatives: different models

statement of the problem (objectives)statement of the problem (objectives)

• characterises the DM goals characterises the DM goals

• allows identification of alternativesallows identification of alternatives

Buy a new car that is cost efficientBuy a new car that is cost efficient

Alternatives: different modelsAlternatives: different models

K.Fedra ‘97


set of alternativesset of alternatives

• Rolls RoyceRolls Royce• PorschePorsche• VolvoVolvo• VolkswagenVolkswagen• SeatSeat• LadaLada

set of alternativesset of alternatives

• Rolls RoyceRolls Royce• PorschePorsche• VolvoVolvo• VolkswagenVolkswagen• SeatSeat• LadaLada

K.Fedra ‘97


set of criteriaset of criteria• purchase pricepurchase price• operating costsoperating costs

– mileage– serviceservice, repairs– insurance, road tax

• safety• prestige value

set of criteriaset of criteria• purchase pricepurchase price• operating costsoperating costs

– mileage– serviceservice, repairs– insurance, road tax

• safety• prestige value

K.Fedra ‘97


set of criteriaset of criteria• is considered important with regard to is considered important with regard to

the objectives of the decision makersthe objectives of the decision makers• common for all feasible alternativescommon for all feasible alternatives• necessary to describe the alternatives necessary to describe the alternatives

(decision utility), should be maximised (decision utility), should be maximised or minimisedor minimised

• its elements are independent from its elements are independent from each othereach other

set of criteriaset of criteria• is considered important with regard to is considered important with regard to

the objectives of the decision makersthe objectives of the decision makers• common for all feasible alternativescommon for all feasible alternatives• necessary to describe the alternatives necessary to describe the alternatives

(decision utility), should be maximised (decision utility), should be maximised or minimisedor minimised

• its elements are independent from its elements are independent from each othereach other

K.Fedra ‘97


set of constraintsset of constraints

• maximum available budgetmaximum available budget (limit on one of the criteria)(limit on one of the criteria)

• repair shop within a 20 km radiusrepair shop within a 20 km radius (independent of criteria, implicit: distance to (independent of criteria, implicit: distance to

repair shop)repair shop)

• must fit into the garagemust fit into the garage (implicit: size, maneuverability)(implicit: size, maneuverability)

set of constraintsset of constraints

• maximum available budgetmaximum available budget (limit on one of the criteria)(limit on one of the criteria)

• repair shop within a 20 km radiusrepair shop within a 20 km radius (independent of criteria, implicit: distance to (independent of criteria, implicit: distance to

repair shop)repair shop)

• must fit into the garagemust fit into the garage (implicit: size, maneuverability)(implicit: size, maneuverability)

K.Fedra ‘97


objectives and constraintsobjectives and constraintscan be reformulated:can be reformulated:

constraint:constraint: maximum cost maximum costobjective:objective: minimise cost minimise cost

objectives and constraintsobjectives and constraintscan be reformulated:can be reformulated:

constraint:constraint: maximum cost maximum costobjective:objective: minimise cost minimise cost

K.Fedra ‘97


set of constraintsset of constraintsdefines the feasible subset:defines the feasible subset:

11 Roll Royce: exceeds budget limit Roll Royce: exceeds budget limit does not fit into garagedoes not fit into garage22 Porsche: no repair shop within Porsche: no repair shop within specified radiusspecified radius

set of constraintsset of constraintsdefines the feasible subset:defines the feasible subset:

11 Roll Royce: exceeds budget limit Roll Royce: exceeds budget limit does not fit into garagedoes not fit into garage22 Porsche: no repair shop within Porsche: no repair shop within specified radiusspecified radius

K.Fedra ‘97


evaluation of alternatives (trade-off)evaluation of alternatives (trade-off)

price OMR S Pprice OMR S P

11 Rolls Royce 10 10 8 10 Rolls Royce 10 10 8 10 22 Porsche 6 8 6 8 Porsche 6 8 6 8 33 Volvo 3 3 10 6 Volvo 3 3 10 6 44 Volkswagen 2 2 5 4 Volkswagen 2 2 5 4 55 Seat 1.5 2.1 3 2 Seat 1.5 2.1 3 2 66 Lada 1.0 3 1 1 Lada 1.0 3 1 1

evaluation of alternatives (trade-off)evaluation of alternatives (trade-off)

price OMR S Pprice OMR S P

11 Rolls Royce 10 10 8 10 Rolls Royce 10 10 8 10 22 Porsche 6 8 6 8 Porsche 6 8 6 8 33 Volvo 3 3 10 6 Volvo 3 3 10 6 44 Volkswagen 2 2 5 4 Volkswagen 2 2 5 4 55 Seat 1.5 2.1 3 2 Seat 1.5 2.1 3 2 66 Lada 1.0 3 1 1 Lada 1.0 3 1 1

K.Fedra ‘97


decision rules, selectiondecision rules, selection

price only: select 6price only: select 6 (Lada)(Lada)total cost (3y): select 5total cost (3y): select 5 (Seat)(Seat)total cost (5y): select 4total cost (5y): select 4 (VW)(VW)safety only: select 3 safety only: select 3 (Volvo)(Volvo)total cost + safety: ??total cost + safety: ??all criteria: ??all criteria: ??

decision rules, selectiondecision rules, selection

price only: select 6price only: select 6 (Lada)(Lada)total cost (3y): select 5total cost (3y): select 5 (Seat)(Seat)total cost (5y): select 4total cost (5y): select 4 (VW)(VW)safety only: select 3 safety only: select 3 (Volvo)(Volvo)total cost + safety: ??total cost + safety: ??all criteria: ??all criteria: ??

K.Fedra ‘97


cost plus safety:cost plus safety:cost plus safety:cost plus safety:

safety

cost

1

310

utopia

nadir

dominatedreferencepoint

efficientpoint

K.Fedra ‘97

Pareto efficiencyPareto efficiencyPareto efficiencyPareto efficiency

K.Fedra ‘97

Pareto efficiencyPareto efficiencyPareto efficiencyPareto efficiency

Pareto frontier or surface represents Pareto frontier or surface represents the set of all the set of all non-dominated non-dominated alternatives:alternatives:

an alternative is non-dominated, if it is an alternative is non-dominated, if it is better in at least one criterion than better in at least one criterion than any other alternative; or equal to the any other alternative; or equal to the best without being worse in all other best without being worse in all other criteria.criteria.

Pareto frontier or surface represents Pareto frontier or surface represents the set of all the set of all non-dominated non-dominated alternatives:alternatives:

an alternative is non-dominated, if it is an alternative is non-dominated, if it is better in at least one criterion than better in at least one criterion than any other alternative; or equal to the any other alternative; or equal to the best without being worse in all other best without being worse in all other criteria.criteria.

K.Fedra ‘97


cost plus safety:cost plus safety:cost plus safety:cost plus safety:

safety

cost

1

310

utopia

nadir


efficientpoint

K.Fedra ‘97


axes normalized as % of possible axes normalized as % of possible achievement (utopia - nadir):achievement (utopia - nadir):

axes normalized as % of possible axes normalized as % of possible achievement (utopia - nadir):achievement (utopia - nadir):

safety

cost

100%

0%100%

utopia

nadir


efficientpoint

K.Fedra ‘97


trade off:trade off:

• indifferenceindifference: a trade-off is the change : a trade-off is the change in criterion Cin criterion C11 that is necessary to that is necessary to

offset a given change in criterion Coffset a given change in criterion C22

so that the new alternative Aso that the new alternative A22 is is

indifferent to the original one (Aindifferent to the original one (A11).).


• indifferenceindifference: a trade-off is the change : a trade-off is the change in criterion Cin criterion C11 that is necessary to that is necessary to

offset a given change in criterion Coffset a given change in criterion C22

so that the new alternative Aso that the new alternative A22 is is

indifferent to the original one (Aindifferent to the original one (A11).).

K.Fedra ‘97



• preferred proportions: preferred proportions: a trade-off is a trade-off is the proportion of change in criteria Cthe proportion of change in criteria C1 1

and Cand C22 that the DM would prefer if he that the DM would prefer if he

could move away from the initial could move away from the initial alternative in some specific way.alternative in some specific way.

(implicit relative weights of attributes).(implicit relative weights of attributes).


• preferred proportions: preferred proportions: a trade-off is a trade-off is the proportion of change in criteria Cthe proportion of change in criteria C1 1

and Cand C22 that the DM would prefer if he that the DM would prefer if he

could move away from the initial could move away from the initial alternative in some specific way.alternative in some specific way.

(implicit relative weights of attributes).(implicit relative weights of attributes).

K.Fedra ‘97


weightsweights (relative importance) of criteria (relative importance) of criteria are not constant over the range of are not constant over the range of alternatives:alternatives:

trade-off between criteria and the trade-off between criteria and the relative weights of criteria are context relative weights of criteria are context dependent.dependent.

weightsweights (relative importance) of criteria (relative importance) of criteria are not constant over the range of are not constant over the range of alternatives:alternatives:

trade-off between criteria and the trade-off between criteria and the relative weights of criteria are context relative weights of criteria are context dependent.dependent.

K.Fedra ‘97


trade-off between price and location oftrade-off between price and location of

a housea house

(distance(distance

to work)to work)

trade-off between price and location oftrade-off between price and location of

a housea house

(distance(distance

to work)to work)

dominated

K.Fedra ‘97


indifference and preference curves forindifference and preference curves for

cost cost vsvs

distancedistance

indifference and preference curves forindifference and preference curves for

cost cost vsvs

distancedistance

K.Fedra ‘97


indifference:indifference:moving from the initial alternative moving from the initial alternative

AA00(18,50) to the closer alternative A(18,50) to the closer alternative A11

at (10,.) the DM is willing to pay 85.at (10,.) the DM is willing to pay 85.AA11(10,85) is considered(10,85) is consideredequivalent to Aequivalent to A00(18,50) ,(18,50) ,DM has no preference,DM has no preference,he is indifferent. he is indifferent.

indifference:indifference:moving from the initial alternative moving from the initial alternative

AA00(18,50) to the closer alternative A(18,50) to the closer alternative A11

at (10,.) the DM is willing to pay 85.at (10,.) the DM is willing to pay 85.AA11(10,85) is considered(10,85) is consideredequivalent to Aequivalent to A00(18,50) ,(18,50) ,DM has no preference,DM has no preference,he is indifferent. he is indifferent.

K.Fedra ‘97

Multicriteria decisionsMulticriteria decisionsMulticriteria decisionsMulticriteria decisions3 criteria (3D) extension of the 3 criteria (3D) extension of the

indifference curvesindifference curves3 criteria (3D) extension of the 3 criteria (3D) extension of the

indifference curvesindifference curves

K.Fedra ‘97


complicated by high dimensionality of complicated by high dimensionality of the problemthe problem

difficulty to elicit meaningful and difficulty to elicit meaningful and consistent preferences from DMconsistent preferences from DM– explicit weights

– elicitation (pairwise comparison, etc.)

– reference point

complicated by high dimensionality of complicated by high dimensionality of the problemthe problem

difficulty to elicit meaningful and difficulty to elicit meaningful and consistent preferences from DMconsistent preferences from DM– explicit weights

– elicitation (pairwise comparison, etc.)

– reference point

K.Fedra ‘97

Multicriteria decision makingMulticriteria decision makingMulticriteria decision makingMulticriteria decision making

Valuation:Valuation:expressing the value of ALL criteria in the expressing the value of ALL criteria in the

same (monetary) units, so that a simple same (monetary) units, so that a simple ordering is possible.ordering is possible.

How to value:How to value: safety cost of insurancesafety cost of insurance prestige value cost of an alternativeprestige value cost of an alternative way to achieve theway to achieve the same goalssame goals

Valuation:Valuation:expressing the value of ALL criteria in the expressing the value of ALL criteria in the

same (monetary) units, so that a simple same (monetary) units, so that a simple ordering is possible.ordering is possible.

How to value:How to value: safety cost of insurancesafety cost of insurance prestige value cost of an alternativeprestige value cost of an alternative way to achieve theway to achieve the same goalssame goals

K.Fedra ‘97

Multicriteria decision makingMulticriteria decision makingMulticriteria decision makingMulticriteria decision making

Valuation:Valuation:monetization (assigning monetary monetization (assigning monetary

values) depends on the existence of values) depends on the existence of some form of market.some form of market.

There is There is no marketno market for most for most environmental goods and services.environmental goods and services.

Valuation:Valuation:monetization (assigning monetary monetization (assigning monetary

values) depends on the existence of values) depends on the existence of some form of market.some form of market.

There is There is no marketno market for most for most environmental goods and services.environmental goods and services.

K.Fedra ‘97

ValuationValuationValuationValuation

of environmental goods and servicesof environmental goods and services• commercial use of a resourcecommercial use of a resource• functional value (service)functional value (service)• on-site recreational useon-site recreational use• option for maintaining the potential for option for maintaining the potential for

future use (visit)future use (visit)• existence value (knowing it is there)existence value (knowing it is there)• bequest value (for future generations)bequest value (for future generations)

of environmental goods and servicesof environmental goods and services• commercial use of a resourcecommercial use of a resource• functional value (service)functional value (service)• on-site recreational useon-site recreational use• option for maintaining the potential for option for maintaining the potential for

future use (visit)future use (visit)• existence value (knowing it is there)existence value (knowing it is there)• bequest value (for future generations)bequest value (for future generations)

K.Fedra ‘97


of environmental goods and servicesof environmental goods and servicescan be grouped in can be grouped in

useuse and and non-usenon-use values. values.

How to measure How to measure

non-use valuesnon-use values ? ?

of environmental goods and servicesof environmental goods and servicescan be grouped in can be grouped in

useuse and and non-usenon-use values. values.

How to measure How to measure

non-use valuesnon-use values ? ?

K.Fedra ‘97


How to measure How to measure non-use valuesnon-use values ? ?

willingness to paywillingness to pay (or compensation demanded)(or compensation demanded)

- - contingent valuationcontingent valuation - travel costtravel cost restoration costrestoration cost

(what is the restoration cost (what is the restoration cost for an extinct species ?)for an extinct species ?)

How to measure How to measure non-use valuesnon-use values ? ?

willingness to paywillingness to pay (or compensation demanded)(or compensation demanded)

- - contingent valuationcontingent valuation - travel costtravel cost restoration costrestoration cost

(what is the restoration cost (what is the restoration cost for an extinct species ?)for an extinct species ?)

K.Fedra ‘97


Willingness to payWillingness to paymeasures the value of goods or measures the value of goods or

services that do not have a market to services that do not have a market to establish prices.establish prices.

Basic methodsBasic methods:: contingent valuation contingent valuation (hypothetical)(hypothetical) observed behavior observed behavior (travel cost)(travel cost)

Willingness to payWillingness to paymeasures the value of goods or measures the value of goods or

services that do not have a market to services that do not have a market to establish prices.establish prices.

Basic methodsBasic methods:: contingent valuation contingent valuation (hypothetical)(hypothetical) observed behavior observed behavior (travel cost)(travel cost)

K.Fedra ‘97


Travel costTravel cost method: method:

uses the average expenditures (travel uses the average expenditures (travel

cost) and number of visitors to cost) and number of visitors to

determine the value of a recreational determine the value of a recreational

resource like a park, lake, etc.resource like a park, lake, etc.

Travel costTravel cost method: method:

uses the average expenditures (travel uses the average expenditures (travel

cost) and number of visitors to cost) and number of visitors to

determine the value of a recreational determine the value of a recreational

resource like a park, lake, etc.resource like a park, lake, etc.

K.Fedra ‘97


Contingent valuationContingent valuation::

uses survey data on hypothetical uses survey data on hypothetical transactions (transactions (willingness to pay, willingness to pay,

compensation demandedcompensation demanded) contingent upon ) contingent upon the creation of a market to establish the the creation of a market to establish the value of a non-market good.value of a non-market good.

Contingent valuationContingent valuation::

uses survey data on hypothetical uses survey data on hypothetical transactions (transactions (willingness to pay, willingness to pay,

compensation demandedcompensation demanded) contingent upon ) contingent upon the creation of a market to establish the the creation of a market to establish the value of a non-market good.value of a non-market good.

K.Fedra ‘97


Restoration costs or opportunity costs:Restoration costs or opportunity costs:

estimates the costs of restoring an estimates the costs of restoring an

environmental good or service, or environmental good or service, or

providing it in an alternative way:providing it in an alternative way: Estimate the value of an aquifer by the cost Estimate the value of an aquifer by the cost

of restoring it, or the cost of alternative of restoring it, or the cost of alternative water supply.water supply.


estimates the costs of restoring an estimates the costs of restoring an

environmental good or service, or environmental good or service, or

providing it in an alternative way:providing it in an alternative way: Estimate the value of an aquifer by the cost Estimate the value of an aquifer by the cost

of restoring it, or the cost of alternative of restoring it, or the cost of alternative water supply.water supply.

K.Fedra ‘97



fails for irreversible damage (extinction fails for irreversible damage (extinction

of a species) or the existence value of of a species) or the existence value of

an environmental good (irreplaceable an environmental good (irreplaceable

by definition).by definition).


fails for irreversible damage (extinction fails for irreversible damage (extinction

of a species) or the existence value of of a species) or the existence value of

an environmental good (irreplaceable an environmental good (irreplaceable

by definition).by definition).

K.Fedra ‘97


The basic problems:The basic problems:

• Intangibles: Intangibles: difficult to measure and express difficult to measure and express

in quantitative termsin quantitative terms

• Qualitative character of values:Qualitative character of values: including ethical, moral, religious ….. aspectsincluding ethical, moral, religious ….. aspects

• Time dependency: Time dependency: discounting versus discounting versus

sustainability, intergenerational equitysustainability, intergenerational equity

The basic problems:The basic problems:

• Intangibles: Intangibles: difficult to measure and express difficult to measure and express

in quantitative termsin quantitative terms

• Qualitative character of values:Qualitative character of values: including ethical, moral, religious ….. aspectsincluding ethical, moral, religious ….. aspects

• Time dependency: Time dependency: discounting versus discounting versus

sustainability, intergenerational equitysustainability, intergenerational equity

K.Fedra ‘97


Simple example:Simple example:

use scores, points, indices, or use scores, points, indices, or

similar subjective measurements similar subjective measurements

to make non-commensurate to make non-commensurate

attributes comparableattributes comparable

Simple example:Simple example:

use scores, points, indices, or use scores, points, indices, or

similar subjective measurements similar subjective measurements

to make non-commensurate to make non-commensurate

attributes comparableattributes comparable

K.Fedra ‘97


Hypothetical water project:Hypothetical water project: scorescore

Water supply 50 M mWater supply 50 M m33/day 40/day 40Flood control:Flood control: damage damage 200,000 $/year 20200,000 $/year 20Flood control: Flood control: lives lives 1/year 201/year 20Electricity supply: 3 MKWh 20Electricity supply: 3 MKWh 20Recreation: Recreation: reservoir reservoir 40,000 visitor days 340,000 visitor days 3Aquatic habitat: Aquatic habitat: increase increase 100,000 fish 1100,000 fish 1

TOTAL score for TOTAL score for benefits 104benefits 104




K.Fedra ‘97



Construction cost 10 M$ 120Construction cost 10 M$ 120Operating costs 100,000 $/year 10Operating costs 100,000 $/year 10Nutrient losses:Nutrient losses: farming farming 100 tons/year 5 100 tons/year 5Beach nourishment: 20 tons/year 5Beach nourishment: 20 tons/year 5Loss of Recreation: Loss of Recreation: 1,000 visitor days 51,000 visitor days 5Terrestrial habitat: Terrestrial habitat: losses losses 1 bear, 50 deer 101 bear, 50 deer 10

TOTAL score for TOTAL score for losses 155losses 155




K.Fedra ‘97


Hypothetical water project:Hypothetical water project: TOTAL score for benefits 104TOTAL score for benefits 104TOTAL score for TOTAL score for losses 155losses 155

Public welfare contribution Public welfare contribution -49 -49

Conclusion: Conclusion: don’t build !don’t build !


Public welfare contribution Public welfare contribution -49 -49

Conclusion: Conclusion: don’t build !don’t build !

K.Fedra ‘97








K.Fedra ‘97



Public welfare contributionPublic welfare contribution 25 25

Conclusion: Conclusion: build !build !


Public welfare contributionPublic welfare contribution 25 25

Conclusion: Conclusion: build !build !

K.Fedra ‘97


Hypothetical water project:Hypothetical water project:to improve the estimate for recreational to improve the estimate for recreational

benefits, use the travel cost method:benefits, use the travel cost method:since the reservoir (lake) does not yetsince the reservoir (lake) does not yetexist, use:exist, use:• a similar lake or reservoira similar lake or reservoir• hypothetical questionshypothetical questions

Hypothetical water project:Hypothetical water project:to improve the estimate for recreational to improve the estimate for recreational

benefits, use the travel cost method:benefits, use the travel cost method:since the reservoir (lake) does not yetsince the reservoir (lake) does not yetexist, use:exist, use:• a similar lake or reservoira similar lake or reservoir• hypothetical questionshypothetical questions

K.Fedra ‘97


Travel cost method:Travel cost method:• count visitorscount visitors• determine distance traveled (travel determine distance traveled (travel

cost based on mileage)cost based on mileage)• determine other expendituresdetermine other expenditures• estimate total expenditures from estimate total expenditures from

recreational users == value of the recreational users == value of the resourceresource

Travel cost method:Travel cost method:• count visitorscount visitors• determine distance traveled (travel determine distance traveled (travel

cost based on mileage)cost based on mileage)• determine other expendituresdetermine other expenditures• estimate total expenditures from estimate total expenditures from

recreational users == value of the recreational users == value of the resourceresource

k.fedra ‘97 decision support systems multiple objectives, multiple criteria and valuation in...

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