A Multicriteria Decision Support Methodological
Framework for the Evaluation of Transport Policy
Instruments
D. A. Tsamboulas a,1, A. G. Kopsacheili b
a
Assoc. Professor at the Department of Transportation Planning and Engineering, Faculty of
Civil Engineering, National Technical University of Athens, Athens, Greece.
b
Transport Economist at the Department of Transportation Planning and Engineering,
Faculty of Civil Engineering, National Technical University of Athens, Athens, Greece.
Abstract
Coherent decision-making requires a structured and systematic appraisal of advantages and
disadvantages of different choice possibilities, including non-economic effects (such as externalities).
In the past decades various decision support and evaluation methods have been developed in which the
economic evaluation played the dominant role. The inherent limitations of these approaches were also
progressively more recognized. Gradually, a variety of adjusted multicriteria methods has been
developed over the past years to complement conventional cost benefit analysis (CBA) but on a project
level basis. These methods investigate and evaluate all relevant impacts of an alternative (e.g., project,
plans, usually taking as fixed the policy options) by introducing some key policy criteria. Such methods
have particular relevance in case of non-priced or qualitative effects such as environmental impacts,
equity issues etc., resulting from the implementation of transport plans and/or policies. Hence, there is
a clear need for a systematic multicriteria approach for transport policies. The paper presents an
evaluation framework based on three widely used multicriteria methods. It provides a cohesive
framework, which can contribute to the development of good practice in the evaluation of spatialeconomic and environmental-economic transport policy instruments. This framework is applied for a
specific case with urban transport related policies to test its robustness and assist in the formulation of
policy actions.
1
Corresponding author. Tel.: +30-10-7721367; fax: +30-10-7722404
E-mail address: dtsamb@central.ntua.gr
2
multicriteria methods. Such methods can
1. Introduction
be used for various purposes. Because they
Transport policies, such as planning,
are applicable to every situation, they can
design, construction and management of
be used in transport research in many
transport infrastructure, have considerable
different ways. MCA serves to “suggest –
economic,
or prescribe – how a decision maker
social
and
environmental
consequences. These consequences are
should
spatially distributed across areas, which
identifying and structuring objectives,
are affected, by different benefits and
about making vexing trade-offs, and about
costs. The choice of the most appropriate
balancing risks” (Keeney and Raiffa,
policy involves balancing engineering,
1976). Hence, multicriteria methods can
economic
environmental
imply a significant improvement of urban
considerations, as well as their spatial
transport planning, design, construction
distribution. It also involves balancing the
and management.
and
think
systematically
about
and
Despite this common definition of the
organizations that have a stake in the
problem treated by multicriteria evaluation
decision.
methods, a distinction can be made in
demands
of
The
many
standard
evaluating
individuals
framework
for
terms of the objectives, which will be
policies
and
pursued in an application. At least four
transport
infrastructure
investments
from
an
different
functions
of
multicriteria
economic perspective is CBA (Vreeker,
evaluation methods can be distinguished
R., Nijkamp, P., Ter Weller, C., 2002). In
(Voogd, 1983, pg. 35):
the
case
of
transport
policies
the
i.
The use of multicriteria evaluation
complexities, such as transport-land use
methods for an
and transport-environment interactions,
analysis of the spatial system.
prompt
the
need
for
sophisticated
ii.
(descriptive)
The use of multicriteria evaluation
assessment methods and comprehensible
methods to select options (e.g.
decision-making processes in order to
policies/strategies) from a pre-
assess all advantages and disadvantages of
defined set of alternative options
choice possibilities.
in order to limit a decision area.
In modern evaluation theory it can be
iii.
The use of multicriteria evaluation
observed an increasing emphasis on
methods to account for a proposed
analytical decision support methods. After
line of action or policy line.
the popularity of CBA and other financial-
iv.
The use of multicriteria evaluation
economic evaluation methods we have
methods
seen
appropriateness
an
increasing
popularity
in
policy.
to
test
of
the
likely
a
certain
3
The focus of this paper concerns the
foundation of analytical decision methods
and it aims to highlight their usefulness for
strategic transport decision-making from
an operational point of view. From a large
set of existing multicriteria evaluation
methods three have been selected for a
more comprehensive treatment. Each of
these has a great potential for policy
analysis and evaluation in the transport
sector. The presentation of these methods
follows a structured approach set out by a
consistent
evaluation
methodological
framework. In terms of the objectives of
this framework, the use of these methods
is for selecting policy options from a predefined set of alternative options.
Section 2 of the paper introduces the
literature on transport policy objectives,
and transport policy instruments. Section 3
presents a short discussion of the different
possible evaluation methodologies –in
categories -, concluding to the three
methods included in the framework.
Section 4 of the paper offers a description
of the methodological framework for the
evaluation of urban transport policy
instruments. Section 5 is concerned with a
case study about transport policy options
before the Olympic Games; it tests
frameworks’ robustness and describes the
results of the application of the evaluation
methods employed. In Section 6 we draw
comments.
and
offer
some
2.1 Objectives
Good decisions need clear objectives.
These should be specific, measurable,
agreed, realistic and time-dependent.
“An objective is a statement of a
desired
end-state.
However,
such
statement can vary from the very general,
i.e. economic development, to the very
specific, i.e. avoid the increase of noise
levels
above
a
specified
threshold”
(KonSULT, 2002). It is sometimes useful
to classify objectives according to their
level.
Based on previous literature on this
subject, it seems particularly useful to
The paper is organized as follows.
conclusions
2. Transport Policies – Objectives
& Instruments
further
make a distinction between ultimate 0r
else higher-level objectives and immediate
ones.
Ultimate objectives are usually framed
in terms of strategic or higher-level
variables, such as the level of economic
growth, social cohesion or sustainable
development.
“Some of these "objectives" have
more to do with the strategy to be
implemented to meet other true objectives.
These
broad
objectives
indicate
the
directions in which strategies should be
developed. They are sufficient to indicate
that the appraisal procedures should
predict and assess the level of congestion,
noise, pollution, accidents and access.
They also provide a means of assessing the
relative performance of different strategies
4
in reducing pollution or accidents. They do
2.2
not, however, indicate whether a particular
(KonSULT, 2002)
Transport
Policy
Instruments
solution is adequate in its impact”
There is a wide range of policy
(KonSULT, 2002). To achieve the latter
instruments available to transport planners.
more specific, immediate objectives are
These instruments can be categorized in
needed.
several ways. The categorization that is
Immediate objectives are those, which
generally adopted has grouped them under
can be directly linked with the outputs of
the following six headings:
the
project.

Land use measures
Consideration of a proposed option needs

Behavioural measures
to concentrate on those criteria which

Infrastructure provision
contribute to the immediate, and hence to

Management of the infrastructure
the ultimate objectives.

Information provision

Pricing
policy,
programme,
Immediate
objectives
or
“provide
a
clearer basis for assessing performance of
the strategy, but they do require careful
A more detailed list of instruments-
definition if the specified thresholds are to
exactly
as
provided
be realistic. Once this is done, these
Knowledgebase-follows:
by
KonSULT
objectives provide a direct basis for
identifying problems, for current or future
conditions” (KonSULT, 2002).
Land use measures: This set of
measures focuses not on the transport
The issue of ‘whose objectives’ should
system, but on the land use patterns, which
be represented in multi-criteria evaluation
generate the demand for transport. The
is still a subject of much discussion.
overall emphasis is to identify ways in
A possible set of objectives can be
which the demand for travel can be
(KonSULT, 2002):
reduced, or modified to lessen its impact.

Sustainability
The key measures identified are:

Economic efficiency


Livable streets
increase in density of development

Environmental protection
throughout an area to reduce the need

Equity,
social
accessibility
inclusion
and
Development densities, involving an
to travel;

Development
pattern,
including

Safety
transport corridor-based developments

Economic growth
designed to encourage provision and

Finance
use of public transport;

Practicability

Development mix in which homes,
jobs and shops are placed close
5
together, thus reducing the need to
travel;

Protection
of
certain
sites
from
Parking
standards
for
new
additions or enhancements to the existing
are:


New road construction; and
developers can provide less parking,

New off-street parking.
payments,

Developer
contributions
to
the

Value capture taxes, designed to
to
influence
public
Upgrades
to
existing
fixed
infrastructure;
reflect the windfall benefits to existing

Reopening closed rail lines;
developments

New rail stations;

New rail lines;

New rail services on existing lines;

Light rail systems;
from
improved
accessibility; and

Measures
transport use
financing of infrastructure;

Measures to influence car use:
whereby
Commuted
but pay for public space;

The
transport infrastructure. The main ones
development;

measures:
measures listed under this heading involve
development;

Infrastructure
Other
land-use
taxes,
including
property taxes.

Guided bus systems;
behavioural

Park and ride;
measures: These are measures, which aim

Terminals and interchanges; and

Enhancement of bus and rail
Attitudinal
and
to change users' understanding of transport
problems, or provide alternatives outside
the transport sector, and hence induce
changes in travel patterns. The principal
vehicles.

ones are:

Public awareness campaigns, designed
to
encourage
individuals
to
use
alternatives, which reduce overall
travel, and travel by car;

Flexible working hours;

Telecommunications as an alternative
to travel; and

Company travel plans, in which firms
set out ways in which they can reduce
their demands on the transport system.

Provision for pedestrians

Pedestrian routes; and

Pedestrian areas.
Provision for freight

Lorry parks; and

Transhipment facilities.
Management
measures:
The
measures listed under this heading involve
changing the way in which the existing
transport infrastructure is used. They
involve a wide range of approaches,
including increases and reductions in road
capacity, reallocations of that capacity,
6

and changes in the operation of public
transport. They include:

cameras
for
traffic
regulation enforcement.

Measures to influence car use
Provision for pedestrians

Road maintenance;

Pedestrian crossing facilities; and

Conventional traffic management;

Safe routes to school, including

Conventional speed controls and
innovations such as "walking bus
restrictions;
services" in which children walk

Urban traffic control systems;
together.

Intelligent
transport
systems,

Provision for freight
which use new technology to

Lorry routes and bans; and
improve the performance of the

Lorry
road network;
parking
and
loading
restrictions.

Accident remedial measures;

Traffic calming measures;

Physical restrictions;
measures listed under this heading involve

Regulatory restrictions;
improvements in the information available

Parking


On-bus
Information
provision:
The
including
to transport users and operators. Some are
controls on duration, entry times
traditional fixed information systems;
and designated users; and
others draw on real time applications of
Car sharing.
information technology. They include:
Measures
controls,
to
influence
public

Measures to influence car use
transport use

Conventional direction signing;

Maintenance of existing fixed

Variable message signs;
infrastructure;

Real-time
New bus services;

Bus priorities;

High occupancy vehicle lanes;

Changes

bus
and
rail

"clock-face"

Measures
to
influence
public
transport use
Timetabling strategies, such as
regular
Parking guidance and information
systems.
frequencies;

information
systems and route guidance; and

in
driver

Conventional timetable and other
service information;
departure
times and simple (eg 10 minute

Real time passenger information;
headways);

Trip
planning
systems
which
information
on
Bus service management measures
provide
designed to improve reliability;
alternatives before the start of the
and
journey; and
7

Operation
information
systems
such as bus fleet management.


the better-known multi-criteria evaluation
methods categories/groups explaining also
Provisions for pedestrians
our decision to pursue the three multi-

Static direction signs; and
criteria methods used next in the decision

Tactile footways.
support framework.
Direct analysis of the alternatives
Provision for freight

Static direction signs; and
performance:

Fleet management systems.
information
A
limited
about
amount
options’
of
relative
qualities can be obtained by direct
measures
inspection of the alternatives performance.
listed here involve changes in the cost of
Dominance occurs when one option
transport use for both private vehicles and
performs at least as well as another on all
public transport. They include:
criteria and strictly better than the other on

Measures to influence car use
at least one criterion. In principle, one

Parking charges;
option might dominate all others, but in

Charges for ownership of private
practice this is unlikely.
Pricing
measures:
The
Outranking methods: It depends
parking space;

Urban road charging, including
area licensing and road pricing;


Vehicle ownership taxes; and

Fuel taxes.
Measures
to
influence
public
transport use
upon the concept of outranking. The
methods
that
have
evolved
all
use
outranking to seek to eliminate alternatives
that are, in a particular sense, ‘dominated’.
However,
unlike
dominance
idea
the
straightforward
outlined
in
before,
dominance within the outranking frame of

Fare levels;

Fares structures, such as flat fares,
zone fares and monthly passes;

Integrated ticketing systems; and

Concessionary fares, which are
lower for identified groups of
users such as elderly people.
reference uses weights to give more
influence to some criteria than others. One
option is said to outrank another if it
outperforms the other on enough criteria of
sufficient importance (as reflected by the
sum of the criteria weights) and is not
outperformed by the other option in the
sense of recording a significantly inferior
3. Multi-criteria
Methods
Evaluation
performance on any one criterion. All
options are then assessed in terms of the
3.1 Discussion
The first part of this section briefly
summarises the main features of some of
extent to which they exhibit sufficient
outranking with respect to the full set of
8
options being considered as measured
against a pair of threshold parameters.
Multi-attribute utility theory: There
is no normative model of how individuals
Linear additive models: If it can
should make multi-criteria choices that is
either be proved, or reasonably assumed,
without critics. The one that comes closest
that
to universal acceptance is based on multi-
the
criteria
independent
of
are
if
attribute utility theory. While this work
uncertainty is not formally built into the
provided powerful theoretical insights, it
MCA model, then the simple linear
does not directly help decision makers in
additive evaluation model is applicable.
undertaking
The linear model shows how an option’s
decision tasks. The breakthrough in this
values on the many criteria can be
respect is the work of Keeney and Raiffa,
combined into one overall value. This is
published in 1976.They developed a set of
done by multiplying the value score on
procedures, consistent with the earlier
each criterion by the weight of that
normative foundations, which would allow
criterion, and then adding all those
decision makers to evaluate multi-criteria
weighted scores together. However, this
options in practice. There are three
simple arithmetic is only appropriate if the
building blocks for their procedures. First
criteria
preference
is a performance matrix and the second is
independent. Models of this type have a
procedures to determine whether criteria
well-established record of providing robust
are independent of each other or not. The
and effective support to decision-makers
third consists of ways of estimating the
working on a range of problems and in
parameters in a mathematical function
various circumstances.
which allow the estimation of a single
are
each
preferentially
other
mutually
and
complex
multi-criteria
The Analytical Hierarchy Process:
number index, U, to express the decision
The Analytical Hierarchy Process (AHP)
maker’s overall valuation of an option in
also develops a linear additive model, but,
terms of the value of its performance on
in its standard format, uses procedures for
each of the separate criteria.
deriving the weights and the scores
MCA methods based on fuzzy sets:
achieved by alternatives, which are based,
A different response to the imprecision
respectively, on pair wise comparisons
that surrounds much of the data on which
between criteria and between options.
public decision making is based has been
Thus, for example, in assessing weights,
to look to the newly developing field of
the decision maker is asked a series of
fuzzy sets to provide a basis for decision
questions, each of which asks how
making models. However, methods of this
important
type are not yet widely applied.
one
particular
criterion
is
relative to another for the decision being
addressed.
9
It seems from the description, that out
function can be linear (in a simple case) or
of all, Linear Additive Models, Analytical
crooked linear or exponential or parabola
Hierarchical Process and Multi-attribute
or an other type, relatively to the nature of
Utility Theory are well established and
each Criterion.
widely applied methods.
Step-3: Thus, for Criterion “Cj”, from the
The first supports decision-makers to
Physical Performances “Xi,j” we create the
easily work on a range of problems and in
Artificial ones “Pi,j” (Alternative project
various circumstances. It leaves “open” the
“Oi”
“weighting”
subject
and
corresponding to this Criterion appropriate
disadvantage
but
the
Hierarchical
Process
that
is
a
Analytical
contributes
to
overcome this disadvantage by deriving
weights. Finally Multi-attribute Utility
Theory integrates them so as to provide a
robust
and
effective
framework
of
-
These three categories of methods will
be used and next the specific methods are
presented in more detail, as they have been
classified by EUNET Project (EUNET
Project, Deliverable 2, 1997)
“Cj”),
by
the
Utility Function: “Uj”. So, Pi,j = Uj(Xi,j).
Step-4: The Total Performance of each
Alternative Project Oi is equal to Pi,j =
= (T.P.)i.
Step-5: All the Alternative Projects are
ordered,
evaluation.
Criterion
respectively
to
their
Total
Performances. So, the greatest Total
Performance is corresponding to the better
Project and consequently, all the other
Projects are ordered by the same way.
“Utility Functions” Method is an
Additive Method. It creates a “Total
Performance”, as a Mathematical Norm,
3.2 Overview of Methods Used
for each Alternative Project.
3.2.1
“Additive
Utility
Functions”
Method
“Additive Utility Functions” Method
is a Linear Additive Model Method of
The Method, by the “utility functions”,
has both of capabilities in rendering of
Physical Projects Performances:
The
capability
of
Quantitative
Multi-Criteria Analysis. Its application
rendering and the capability of the
steps are the followings:
Appropriate corresponding of Artificial
Performances to Physical ones, relatively
Step-1: We determine Alternative Projects
and Evaluation Criteria.
Step-2: For each Criterion, a “utility
to the nature of each Criterion.
The lack of Criteria Weighting can be
considered as a disadvantage.
function” is created. “Utility Function” is a
Also, the Method (like as many of
rendering from the Physical Scale to the
Additive ones) has not the capability of
Artificial one of each Criterion. This
“veto”. This capability is important in
10
several cases, whereas, some Projects
Performances
are
worse
than
3.2.3 MAUT
“MAUT” Method is a Multi-Criteria
the
corresponding determined thresholds.
Method. It is relative to Additive Utility
Functions method. The main difference
3.2.2 Analytical Hierarchical Process -
between the two above methods is that
AHP
“MAUT” uses Criteria Weights “j “ in its
A technique, which may be used for
qualitative
data
(i.e.
where
physical/statistical data is unavailable)
structuring. Thus, “Total Performance” of
each Project “Oi” in MAUT is not equal to
Pi,j, but (T.P.)i = jPi,j.
whereby pair wise comparisons are made.
The problem is organised into a hierarchy
according to the factors important in
reaching a decision - at the top of the
hierarchy is the goal in the decision
making process, and below this in the
MAUT is an Additive Multi-Criteria
Method. So, MAUT has the capability of a
Quantitative Relation between Weights of
Criteria and also, it uses utility functions
for a Rendering from the physical scales to
artificial ones, relatively to Criteria.
hierarchy lie a series of branches and
possibly sub-branches of criteria.
The
available options (choices) lie at the
bottom layer of the hierarchy. There are 3
We must notice the lack of a "veto"
capability, relatively to cases where very
low Performances in some Criteria there
are.
main stages to the AHP process: 1) to
identify the important factors to the DM,
2) to form comparative judgements and 3)
4. Evaluation
Framework
Methodological
to establish weights for the choices. Thus
at each level of the hierarchy, pair wise
comparisons are made of all elements, and
strength of preference assigned according
to a 9 - point scale. This could be done
verbally. A matrix of preference scores
for each ‘branch’ can be converted to
relative scores (weights). This could be by
aggregation, geometric mean or Eigen
vector method. The contribution of each
alternative to the overall goal can be
assessed by aggregating weights vertically.
Evaluation (ex-post or ex-ante) of
transportation plans and projects have
been carried out in the past, using a variety
of methodological frameworks. In terms of
content, the available methodologies can
be classified into Cost-Benefit Analysis
(CBA), Multi-Criteria Analysis (MCA),
Social-based Analysis, Decision-Analysis,
other type applications (land suitability
analysis, resource management approaches
etc.)
and
simulation/mathematical
modelling. In terms of typology, they all
use variations of checklists, matrices,
networks
and
overlay
methods
11
(Tsamboulas and Mikroudis, pg. 283).
impacts, as well as the assessment of
Clearly, there is no single evaluation
impacts are considered.
method that can satisfactorily evaluate all
An
essential
complex aspects of an alternative transport
multicriteria
evaluation
concerns
plan, project or policy.
criteria
which
evaluation
by
component
an
of
a
the
is
evaluation
performed. The notion ‘criterion’ was
methodological framework is a blend of
defined in a very flexible way by Voogd
three multicriteria evaluation methods,
(1983) as ‘a measurable aspect of
presented already before.
judgment by which a dimension of the
The
proposed
(i) “Additive
Utility Functions” Method extended with
various
(ii) the Analytical Hierarchical Process,
consideration can be characterized’. The
AHP, to finally be included both in (iii)
flexibility of multicriteria evaluation is to a
Multiple
large degree determined by the way the
Attributes
Utility
Function,
MAUT.
choice
possibilities
under
criteria are incorporated into the analysis.
The framework is elaborated to be
While the policy objectives indicate
easy, understandable, flexible and coherent
the directions in which a policy should
in terms of handling the complexity and
aim, they say nothing about the amount,
uncertainty
which it would be appropriate to achieve.
of
transportation
issues,
especially in an urban environment.
As a result, it may be difficult to judge
An overview of the framework can be
whether a proposed policy is successful, or
seen in Figure 1 and next the general
whether more could be achieved. More
stages/steps of it are presented:
quantified objectives can be specified in
terms of a series of impacts/criteria (or
Stage
1:
Specification
of
Policy
else indicators), which can be either
Objectives, Alternative Policy Instruments
general or specific, and which can be used
and Impacts.
also to identify problems.
The idea behind this framework is to
Criteria for use in planning must meet
provide the Decision-Maker with a tool for
a number of requirements. First, they must
selecting policies/strategies from a pre-
be comprehensive, and fully reflect the
defined set of alternatives in order to limit
objectives to which they relate. Second,
the decision area, following specific policy
they must avoid double counting. Third,
objectives and priorities set by the relevant
they should be sensitive to changes in the
authorities.
policy instruments implemented.
Therefore,
the
transport
policy
The result of this stage is the creation
objective/s as well as the alternative
of an extensive set of criteria, to be used
transport policy instruments are pre-
next in the methodological framework. An
defined. So in Stage 1, the selection of
indicative such set is presented next. It is
Inputs
Definition of
Criteria Set
Stage 2
Transport
Policy
Objectives
Stage 1
12
Stage 3
Stage 4
Alternative
Transport Policy
Instruments
Additive
Utility
Functions
Un-weighted
Scores First Ranking
Criteria Index
Function
Criteria Scores
Stage 5
Transport
Policy
Priorities
AHP
MAUT Method
Final Ranking
Criteria
Weights
Final Alternative
Transport Policy
Instruments
Scores
CHOICE
Figure 1
13
an integration of knowledge of EU
Transport
Policy
Framework,

Local
Accident-related
costs
(materials
damage, police and fire, insurance
Politicians and Public Opinions, Possible
administration, legal and court costs)
Specific Local Conditions and Experts

Accidents rate/frequency
Knowledge2.

Insecurity (subjective)
Accessibility:
Criteria Set:

Activities (by type) within a given
Economic efficiency:
time and money cost for a specified

Delays for vehicles (by type)
origin and mode

Delays for pedestrians

Time and money costs of journeys
cost to all activities of a given type
actually undertaken
from a specified origin by a specified
Variability in journey time (by type of
mode



Weighted average time and money
journey)
Sustainability:
Costs of operating different transport

services – Depreciation (wear and tear
Environmental,
safety
and
accessibility indicators as above
of vehicle), consumption of fuel and

CO2 emissions for the area as a whole
oil, wear and tear of tyre, repair and

Fuel consumption for the area as a
maintenance, overhead costs.
whole
Environmental protection:
Economic regeneration:

Noise levels

Employment

Vibration

Environmental

Levels of different local and regional
indicators as above, by area and
air pollutants
economic sector

Visual intrusion
Finance:

Townscape quality (subjective)


Severance (subjective)
Safety:

and
accessibility
Operating costs and revenues for
different modes

Casualty related costs (human cost,
Costs and revenues for parking and
other facilities
lost output, medical and support

Tax revenue from vehicle use
services)

System operating and maintenance
costs – signalling, enforcement
Equity:
2
Sources for the compilation of Criteria set
were, EU research projects such as EUNET
and DTSC : A methodology for policy analysis
and spatial conflicts in transport policies, the
KonSULT Knowledgebase as well as expertise
of transport planners.

Indicators
as
above,
considered
separately for different impact groups
14
Stage 2: Un-weighted Alternatives Score Estimation of Criterion Scores
In
a
multicriteria
Stage 3: Estimation of Criteria Weights
The relative importance of criteria and
evaluation the
criteria scores to one another is reflected
characteristics of the alternatives under
by priorities or weights. It appears that
consideration are represented by means of
such weights have a major effect on the
the criterion scores. These scores reflect to
final evaluation result. Already in many
which degree an alternative meets a
cases a slight variation of the priorities can
certain criterion. Criterion scores can be
yield another ranking of alternatives under
derived in many different ways and can be
consideration.
expressed in ‘qualitative’ or ‘quantitative
There are many different weighting
terms’. To make the various criterion
techniques and their choice depends on the
scores compatible it is necessary to
characteristics
transform
evaluation and on the data available.
them
into
one
common
of
the
project
under
measurement unit, for example by taking
In this stage the policy priorities are
care that for each criterion score will have
included. By using AHP, Criteria weights
a range from 0 to 1. (Voogd, 1983)
will be derived. Along with AHP a
In this stage, for each alternative
convenient standardization technique will
transport policy instrument, using the
be used in order to derive weights that
Additive Utility Functions method, a score
sum-up to 1.
will be derived and a first rank of the
the pragmatic reasons –identified before -
alternatives will be obtained.
Initially,
its
of choosing this weighting technique,
corresponding index function will be
there are theoretical considerations as
identified, therefore its score. Secondly the
well.
total
for
performance
each
It should be noted here that, apart from
of
criterion
the
alternative
The existence of Eigen vector method
transport policy will be derived by
in AHP is the basic one. The literature of
summing-up the scores of each criterion.
applied mathematics considers this method
Summing up the scores from each
as “fast” and “secure”. “Fast” due to short
criterion has been criticised in the past and
time necessary for its application and
it is the basic disadvantage of the method
“secure” in terms of the high probability in
as well. Though, there is a reason for this
producing “realistic” results.
“un-weighted” summation. The reason is
that the results from Stage 2 will serve as
Stage
feedback to policy priorities.
Alternatives Scores
In other words this stage enables the
4:
Estimation
Weighted
summation
of
Weighted
of
criterion
co-operation between transport planner
scores will take place in this stage,
and authorities-policy makers.
following
Multiple
Attributes
Utility
15
Function Method, MAUT. The final score
of
each
alternative
transport
5.1.1 Scenario 0: Current Situation
policy
This scenario serves as a reference
instrument will be calculated, using the
scenario. Current trends are used to make
results of Stages 2 and 3 in order to reflect
predictions about the future. The main
the policy priorities.
purpose of this scenario is to evaluate the
situation where there are no changes in
Stage 5: Hierarchy of Alternatives – Final
Choice
Based on the results of Stage 4 the
current trends and policies.
Three scenarios incorporating the
policy
instruments
"bundles"
are
final ranking and therefore selection of the
examined, as well as the current situation
appropriate alternative transport policy
scenario.
instrument will take place.
5.1.2 Scenario 1: Infrastructure, Land
5. Application
of
the
Methodological Framework and
Methods
Use and Attitudinal & Behavioural
The application of the evaluation
additions or enhancements to the existing
methodological framework developed is
transport infrastructure, on the generation
presented. This is done for a case study on
of transport demand as well as on inducing
differing plans for accommodating and
changes in travel patterns. The scenario
improving the movement of athletes and
can be summarized as follows:
visitors during the Olympic Games in
1. New roads construction
Athens with minimum disruption of the
2. New off-street parking
existing travel behaviour patterns.
3. Upgrades
measures
This choice option will concentrate on
to
existing
fixed
infrastructure for public transport
5.1 Case Study: a brief description
4. New rail stations
This case study is a first attempt to predict
5. New rail lines
the impacts of alternative transport policy
6. New rail services in existing lines
instruments “bundles” application, in the
7. Light rail system
city of Athens during the Olympic Games
8. Terminals and interchanges
of 2004. The data and predictions used for
9. Enhancement of bus and rail systems
this case study are from a study elaborated
10. Pedestrian routes and areas around
by Attiko Metro back in 1996 and from
Olympic Stadiums
extensive interviews of experts at the in
11. Lorry Parks
National Technical University of Athens.
12. Transhipment Facilities
13. Transport
developments
corridor-based
16
14. Protection
of
certain
sites
(archaeological sites)
23. Lorry routes and bans, restrictions on
parking and loading
15. Public awareness campaigns
16. Flexible working hours
5.1.4 Scenario 3:Infrastructure, Pricing
and Information Provision measures
5.1.3 Scenario 2: Infrastructure and
This choice option will concentrate on
Management measures
additions or enhancements to the existing
This choice option will concentrate on
transport infrastructure, on changes on the
additions or enhancements to the existing
cost of using infrastructure as well as on
transport infrastructure and on changing of
improving
the way the existing infrastructure is used.
transport users. The scenario can be
The scenario can be summarized as
summarized as follows:
follows:
1. New roads construction
1. New roads construction
2. New off-street parking
2. New off-street parking
3. Upgrades
3. Upgrades
to
existing
fixed
infrastructure for public transport
information
to
available
existing
to
fixed
infrastructure for public transport
4. New rail stations
4. New rail stations
5. New rail lines
5. New rail lines
6. New rail services in existing lines
6. New rail services in existing lines
7. Light rail system
7. Light rail system
8. Terminals and interchanges
8. Terminals and interchanges
9. Enhancement of bus and rail systems
9. Enhancement of bus and rail systems
10. Pedestrian routes and areas around
10. Pedestrian routes and areas around
Olympic Stadiums
Olympic Stadiums
11. Lorry Parks
11. Lorry Parks
12. Transhipment Facilities
12. Transhipment Facilities
13. Parking charges
13. Urban traffic control systems
14. Fare levels
14. Intelligent transport systems
15. Fares structures, flat fares, zone fares
15. Physical restrictions
and monthly passes
16. Regulatory restrictions
16. Integrated ticketing System
17. Parking controls
17. Concessionary
18. New bus services
fares
for
elderly
people, students etc.
19. Bus priorities
18. Variable messages signs for car users
20. High occupancy vehicles lanes
19. Static directions signs for pedestrians
21. Changes in bus and rail frequencies
22. Pedestrian crossing facilities
and freight vehicles
17
5.2 Definition of Criteria and Impacts
Table
the measures
QualitativeF
C5:
The choice process of a transport
Turnover – Food
policy instruments bundle against the
provision Freight
background of sustainability should be
transport
description of the
easement of
transhipments and
turnovers
based upon a broad set of criteria which
Qualitative
allow for the simultaneous consideration
description of the
of the impacts from different viewpoints,
C6:
notably economical, social, environmental.
Severance
measures effects on
community
For each of these classes –and based on
severance
the
Percentage
opinion
of
experts
and
people
responsible for the Olympic Games – the
following list of criteria –and their
deviation from the
C7:
CO2 concentrations
Air Pollution (CO2)
without the
physical measurement expression - was
measures
compiled.
Criterion
Qualitative
Measurement
Deviation from the
C1:
appropriate journey
Variability in
3
Journey Time for
the Athletes
C8:
description of the
Safety
measures effects on
safety of transferees
time for the athletes
as it is set by the
Table 1 Criteria and their measurement
Olympic Committee
F:
The qualitative/verbal description is as
C2:
Percentage
Variability in
deviation from the
follows:
Journey Time4 for
journey time
Strong negative impact
the Visitors – by car
without the
Large negative impact
& Public Transport
measures
Moderate negative impact
C3:
Percentage
Small negative impact
Variability in
deviation from the
Journey Time4 for
journey time
the Visitors -
without the
pedestrians
measures
C4:
Percentage
Number of people
deviation from the
transferred/hour –
number of people
Public Transport
transferred without
No impact
Small positive impact
Moderate positive impact
Large positive impact
Strong positive impact
According to the available data from
Attiko Metro study and a piecemeal
3
From the Olympic Village to the Central
Olympic Stadium
4
Mean Journey time from whatever area in
Athens to the Central Olympic Stadium
simulation based on extensive interviews
of
experts
in
National
Technical
18
University
of
Athens
and
in
the
by any vehicle in Athens area cannot be
Organization Athens 2004, the impacts
more
than
25%.
table was created, Table 2.
implementation
So
of
if
after
transport
the
policy
instruments the predicted journey time for
5.3 Additive Utility Functions Method;
visitors - transferred by cars or public
obtaining a first rank of alternative
transport - is decreased by 25% or more,
transport policy instruments
then the score in artificial scale is 1. If
For each criterion, a “utility function”
there is no change in journey time then the
is created, which is a rendering from the
score is 0. Also according to experts the
Physical scale (P, values) to the Artificial
maximum acceptable increase in journey
scale of each criterion. The Artificial scale
time cannot be more than 15%, due to the
(U, values) for all criteria is common and
specific traffic conditions in Athens. So if
it is:
after the implementation of transport
[-1 to 0 to +1],
policy instruments the predicted journey
where:
time for visitors - transferred by cars or
-1: Worse
public transport - is increased by 15% or
0: No change
more, then the score in artificial scale is
+1: Perfect
-1. We assume that the utility function is
linear
Utility Functions:
/crooked
linear
for
simplicity
reasons.
C1:
+PC2/25, if P >0
Since the journey time for athletes must
UC2={
not be more than 20 minutes, if after the
implementation
of
transport
policy
0,
if P=0
-PC2/15, if P< 0
C3:
instruments the predicted journey time for
According to the interviews conducted
athletes is less or equal to 20 minutes –
with experts on transport issues the top
with a minute or two minutes deviation -
decrease of travel/journey time pedestrians
then the score in artificial scale is 1. In any
in Athens area can be more than 20%. So
other case is –1. Therefore the 20 minutes
if after the implementation of transport
in this case serve as a strict threshold.
policy instruments the predicted journey
+1, if P= or <20 minutes
time for visitors - transferred by cars or
public transport - is decreased by 20% or
UC1={
-1, if P>20 minutes
more, then the score in artificial scale is 1.
C2:
If there is no change in journey time then
According to the interviews conducted
the score is 0. Also according to experts
with experts on transport issues the
the maximum acceptable increase in
maximum decrease of travel/journey time
journey time cannot be more than 30%,
19
Impacts
C1
Scenario 1
Scenario 2
Scenario 3
0-1 minute deviation from the 20 minute 0-1 minute deviation from the 20 minute 0-1 minute deviation from the 20 minute
Journey Time For Athletes as it is set by the Journey Time For Athletes as it is set by the
Journey Time For Athletes as it is set by the
O.C.
O.C.
O.C.
C2
Decrease of 12%
Decrease of 18%
Decrease of 16%
C3
Increase of 20%
Increase of 20%
Increase of 20%
C4
Increase of 11%
Increase of 23%
Increase of 18%
C5
Medium Positive Impact
Large Positive Impact
Medium Positive Impact
C6
Small Negative Impact
Small Negative Impact
Small Negative Impact
C7
Decrease of 5%
Decrease of 3%
Decrease of 4%
C8
Large Positive Impact
Strong Positive Impact
Large Positive Impact
Table 2 Scenarios impacts
20
due to the prevailing conditions. So if after
corresponds to the verbal description as
the implementation of transport policy
follows:
instruments the predicted journey time for
-1
Strong negative impact
visitors - transferred by cars or public
-0.75
Large negative impact
transport - is increased by 30% or more,
-0.5
Moderate negative impact
then the score in artificial scale is
-0.25
Small negative impact
assume that the utility function is linear
0
No impact
/crooked linear for simplicity reasons.
+0.25 Small positive impact
-1. We
+PC3/20, if P >0
UC3={
0,
+0.5
if P=0
Moderate positive impact
+0.75 Large positive impact
-PC3/30, if P< 0
+1
Strong positive impact
C4:
C6:
During the Olympic Games it is estimated
As C5
that the percentage of people that must be
C7:
carried more than usually by public
According
transport, is roughly 25%. Therefore if
percentage decrease of CO2 for Greece is
after the implementation of transport
8%. This number will serve as threshold.
policy instruments the predicted increase –
Therefore if after the implementation of
in percentage- of people carried is more or
transport policy instruments the predicted
equal to 25% then the score in artificial
decrease - in percentage - of CO2
scale is 1. If there is no change in the
emissions is equal to 8% then the score in
number of people carried the score is 0
artificial scale is 1. If there is no change
and in the case of less people carried-
then the score is 0. In the case of any
although this is rather impossible – the
increase the score is –1. We assume that
score is –1. We assume that the utility
the utility function is linear /crooked linear
function is
for simplicity reasons.
linear/crooked
linear
for
simplicity reasons.
Kyoto
summit
the
+PC7/8, if P >0
+PC4/25, if P >0
UC4={
to
0,
if P=0
-1,
if P< 0
UC7={
0,
if P=0
-1,
if P< 0
C8:
C5:
As C5, C6
For this criterion the P values –physical
performance – is expressed verbally.
Criteria Scores:
Therefore there is no utility function in
According to the criteria utility functions
terms of mathematic norm but just an
derived and the impacts table with
artificial
criteria’s
scale
of
scores,
which
physical
performances
the
21
criteria artificial performances/scores are
5.4 AHP; include policy objectives and
shown next for each scenario.
priorities
According to policy priorities set out
Scores
C1
+1
from the experts interviewed, pairwise
C2
+0.48
comparisons of all criteria were made, and
C3
-0.66
strength of preference assigned according
C4
+0.44
to Saaty’s 9 – point scale, where 1 implies
C5
+0.5
C6
-0.25
C7
+0.625
C8
+0.75
C1
+1
C2
+0.72
C3
-0.66
C4
+0.92
C5
+0.75
C6
the base factor is equally equivalent in
importance to the other factor, and 9
implies the base factor is overwhelmingly
more important than the other factor.
The matrix of preference scores for
C2
C3
C4
C5
C6
C7
C8
C1
1
1/5
1/3
1/2
1/3
3
3
7
-0.25
C2
5
1
7
7
5
3
7
9
C7
+0.375
C3
3
1/7
1
1
1/5
3
7
9
C8
+1
C4
2
1/7
1
1
1
3
7
9
C1
+1
C5
3
1/5
5
1
1
1
5
9
C2
+0.64
C6
1/3
1/3
1/3
1/3
1
1
5
9
C3
-0.66
C7
1/3
1/7
1/7
1/7
1/5
1/5
1
3
C4
+0.72
C8
1/7
1/9
1/9
1/9
1/9
1/9
1/3
1
C5
+0.5
C6
-0.25
2,3
14,9
11,1
8,8
14,3
35,3
C7
+0.5
C8
+0.75
Matrix 1 of Saaty application
Table 3 Criteria and scenarios scores
The relative score of importance can
A first ranking, to be used as feedback
be found by normalizing each columns
to the opinions expressed by experts
total by dividing each total by sum of all
interviewed, is:
totals.
Scenario 2>Scenario 3>Scenario 1
So the weights set is:
W1 = 0.09
W2 = 0.01
W3 = 0.09
W4 = 0.07
56,0
C1
14,8
each criterion is shown next.
Total
Scenario 3
Scenario 2
Scenario 1
Criteria
22
W5 = 0.06
mixed data on impacts/effects of the
W6 = 0.09
alternatives.
W7 = 0.22
multicriteria evaluation methods have
W8 = 0.36
been proposed.
Three
harmonizing
The application of the methodological
5.5 Multiple Attribute Utility Additive
framework has led to the identification of
Functions Method; obtaining final rank
the best possible ranking of the proposed
of
alternatives.
alternative
transport
policy
Since the methodological framework
instruments
The
Total
Performance
of
each
followed is a combination of existing
Scenario is the weighted sum of the
methods of estimation and evaluation, the
criteria scores for each scenario.
reliability
concerning
the
results
is
somehow increased.
8
T .P.Scenarioi  W j * U j ,i
Furthermore, the approach adopted is
j 1
The Final Scores for each Scenario are
that it is able to measure different impacts,
shown next:
expressed in different units, by introducing
T.P. Scenario 1 = 0.4812
a common unit scale. This facilitates the
T.P. Scenario 2 = 0.5672
comparison between levels of different
T.P. Scenario 3 = 0.4749
impacts and can be used in order to find
the overall level on an alternative.
The
Final
Ranking
among
the
Moreover, the simplistic form of the
framework adopted makes the procedure
alternative scenarios is:
easy to understand and apply. In addition
the easy structure supports a better co-
Scenario 2>Scenario 1>Scenario 3
operation between the relevant authoritiesWe observe the difference in ranking
before and after the introduction of
policy makers and transport planners.
Finally, regarding the results of the
case study: the opinions given from the
weights or else the policy priorities.
experts imply that out of all policy
priorities, sustainability of the area and the
6. Some comments
The aim of this paper is to offer
decision-makers
a
methodological
framework in order to analyse
the
adequacy and priority of pre-defined
alternative transport policy instruments in
the case of quantitative, qualitative or
minimum
disruption
of
the
existing
situation is of top priority. The latter might
change until 2004 depending on possible
changes in the predictions of impacts as
presented in this paper. This can affect the
criteria weights and consequently the final
ranking of the scenarios. Furthermore, the
23
data on which the case study was based
date back to 1996, so a better appraisal of
the scenarios could be done with more
recent data. Nonetheless the results of this
case study can serve as the basis for
further analysis.
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Cost-Benefit Analysis and Multicriteria
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and
Transport,
2002,
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www.transportconnect.net
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“EFECT - evaluation framework of
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