Project Title: EXPLORING THE COMPLEXITY OF … · of Volvo Research and Education Foundations ......

Project Title: EXPLORING THE COMPLEXITY OF POLICY DESIGN

Review on policy-making and process

PART I: Public policy literature review

(WP1)

Due date of deliverable: July 2012

Actual Submission date: 21st

July 2012

Leading Institution for this project: Instituto Superior Técnico

ABOUT THE DOCUMENT

The production of this document has been made possible through the financial contribution

of Volvo Research and Education Foundations (VREF) via the Across Latitudes and Cultures

- Bus Rapid Transit Center of Excellence in Chile (ALC-BRT CoE).

The material presented in this document is part of the on-going doctoral of the PhD student

Maria Spandou, under the supervision of Prof. Rosário Macário at Instituto Superior Técnico

(IST). All rights reserved.

ABOUT ALC-BRT CoE

Across Latitudes and Cultures - Bus Rapid Transit (ALC-BRT) is a Centre of Excellence for

Bus Rapid Transit development implemented in Santiago, Chile, and financed by the Volvo

Research and Educational Foundations (VREF).

This CoE was established in May of 2010 and is working as a consortium of five institutions

that include Pontificia Universidad Católica de Chile (PUC), Massachusetts Institute of

Technology (MIT), Technical University of Lisbon, The University of Sydney and EMBARQ -

The WRI Center for Sustainable Transport, including its network of centers of sustainable

transport.

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LS2 - EXPOD - EXPLORING THE COMPLEXITY OF POLICY DESIGN

WP 1 - Literature review on policy-making and process

Table of Contents

1. Introduction .................................................................................................................. 4

2. Public goods vs Private Goods ....................................................................................... 4

3. Decision-making ........................................................................................................... 7

3.1. Decision Typologies ............................................................................................... 7

3.2. Overview of Relevant Theories............................................................................... 7

3.2.1. Decision-making theories ............................................................................... 7

3.2.1.1. Pure and Bounded Rationality ........................................................................ 7

3.2.1.2. Incrementalism or Muddling through model .................................................. 8

3.2.1.3. Adaptive (or Mixed scanning or humble) decision making ............................. 9

3.2.1.4. Decision Making Determinants .................................................................... 10

3.2.1.4.1. Conflicts ...................................................................................................... 11

3.2.2. Causal theories............................................................................................. 12

4. Strategy ....................................................................................................................... 16

5. What is public policy? ................................................................................................. 18

6. Public policy types ...................................................................................................... 18

7. Why is there a need for public policy and government intervention?............................ 20

8. Actors in public policy................................................................................................. 21

9. Conflicts in policy making ........................................................................................... 27

10. Public Policy Analysis Models ................................................................................. 29

10.1. Stages or Policy Cycle model ................................................................................ 29

10.2. Garbage can model of organizational choice ......................................................... 32

10.3. Multiple streams model ....................................................................................... 34

10.4. Advocacy Coalition Framework ........................................................................... 36

10.5. Punctuated Equilibrium Framework.................................................................... 39

10.6. Institutional Rational Choice ............................................................................... 40

10.7. Policy Process Networks (PPN) framework ......................................................... 40

11. Policy implementation ................................................................................................. 41

12. Information and evidence as determinants of Public policy ...................................... 47

13. Institutions and public policy .................................................................................. 49

13.1. Some definitions .................................................................................................. 49

13.2. Institutional analysis frameworks ........................................................................ 53

13.2.1. Institutional Analysis and Development (IAD) framework ........................... 54

13.2.2. Institutional decomposition and analysis (IDA) framework ......................... 57

13.2.3. Procedure for Institutional Compatibility Assessment (PICA) ..................... 60

13.2.4. Social Fabric Matrix Approach..................................................................... 63

13.2.5. Institutional and organizational development process (IO/DP) .................... 70

14. Discussion and conclusions ..................................................................................... 71

15. References ............................................................................................................... 75

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1. Introduction

As stated by Parsons (1995), policy-making takes place in conditions of uncertainty, flux,

unpredictability and variation, that is the analysis of policy design and implementation

requires the understanding of a multi-agent complex system often with multi-levels of

government. The policy-making approach and the underlying policy process are instrumental

for the success of any efficient policy packaging. Besides, policy packaging often means

“cherry picking” components governed by different public sector areas, calling for negotiation

and concertation whenever hierarchies are absent. So, decision-making plays also a role in

this problematic that cannot be ignored.

Since its very beginning political science has been concerned with the relation between

knowledge – policy making – power. Many authors have dedicated their research efforts to

this triad and to have a deeper understanding on policy development we must undertake a

complete review of literature that will enable us to better perceive the relation between

policies and the instruments and institutions for its materialization.

Despite the amount of knowledge in this domain, there is also strong evidence that, as

Parsons (2002) observed policy-making in most parts has been more about “muddling

through” rather than a process in which social or policy sciences have had an influential part

to play. The aim of developing more effective and efficient policy packages has the implicit

consequence of trying to enhance the techniques of developing, managing and controlling the

policy-making process.

The following paragraphs present an overview of the theories, frameworks and models that

underlie the issues mentioned earlier concerting knowledge from various scientific fields and

disciplines, so as to delineate the public policy-making and implementation topic in its

entirety.

2. Public goods vs Private Goods

In economics and policy analysis, the fundamental classification of goods lies between public

and private goods, based primarily on their attributes of rivalry (or rival consumption) and

excludability (or excludable ownership/use). In rough terms, private goods are rivalrous and

excludable, while pure public goods are nonrivalrous and nonexcludable. This classification

depicts the two extreme positions of the spectrum, but as can be seen in Figue 1 there are

other intermediate classes of goods. Except for these two parameters, Weimer and Vining

(2011) introduced also the parameter of congestion, which differentiates internally each class.

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A more parametric description is provided by Samuelson (1954) according to whom:

• ordinary private consumption goods (X1, …, Xn) can be parcelled out among different

individuals (1, 2, …, i , … ,s) according to the relations X� � ∑X��

• public (collective) consumption goods (Xn+1, …, Xn+m) which all enjoy in common in

the sense that each individual's consumption of such a good leads to no subtraction

from any other individual's consumption of that good, so that X�� X��

simultaneously for each and every i-th individual and each collective consumptive

good.

Another similar classification is introduced by Hayman (2008) on the basis of pure private or

public goods, nonrivalry goods and congestible goods and is depicted diagrammatically in

Figure 2.

Figure 1: A Classification of Goods: Private and Public1,2 (adapted from Weimer and Vining (2011))

1 Notations NW, NE, SW, SE refer to the localization of the quarters in the classification framework of Weimer and Vining (2011) and numbers 1 and 2 denote the different sub-regions that each quarter is divided into based on the existence of congestion or not, e.g. NW2 is the second sub-region of the quarter located in the northwest part of the classification square.

RIVALROUS NONRIVALROUS

NO

NE

XC

LUD

AB

LE

EX

CLU

DA

BLE

Uncongested: Private Good

Efficient market supply

Congested:

Private Good with

Consumption Externality

Overconsumption because

consumers respond to price

rather than marginal social cost.

NW1

NW2Uncongested: Toll Good

No private supply at

efficient price of zero;

underconsumption

at any positive

price.

Congested:

Toll Good with

Crowding

Private supply can be

efficient if price at marginal

social cost; peak-load pricing

required if congestion variable.

NE1

NE2

Uncongested: “Free Good”

Supply exceeds demand

at zero price; no

inefficiency until

demand grows to

exceed supply

at zero price.

Congested:

Private Good with

Consumption Externality


consumers respond to price

rather than marginal social cost.

SW1

SW2Uncongested: Pure Public Good

private supply unlikely

because exclusion not

possible; some

private supply in

privileged and

intermediate

groups.

Congested:

Ambient Public Good

with Consumption

Externality


consumers ignore external cost.

SE1

SE2

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Figure 2: Classification of Goods according to the degree of rivalry and excludability of benefits from

their use (adapted from Hayman (2008))

Similarly, Ostrom and Ostrom (1977) presented a typology, based on the level of excludability

of potential beneficiaries and subtractability of use (Table 1), identifying the following

categories:

• toll or club goods,

• private goods,

• public goods, and

• common-pool resources

Table 1: Ostrom and Ostrom´s (1977) four basic types of goods (adapted from Ostrom, 2005).

There are many instances, when the economic nature of the good is not clear cut, leading to

different approaches towards the policy issues that characterize the social consumption and

production of this good (or service). Furthermore, except for the economic nature of the

2 “An externality is any valued impact (positive or negative) resulting from any action (whether related to production or consumption) that affects someone who did not fully consent to it through participation in voluntary exchange. (…) Production externalities affect either firms (producer-to-producer externalities) or consumers (producer-to-consumer externalities); consumption externalities may also affect the activities of firms (consumer-to-producer externalities) or those of other consumers (consumer-to-consumer externalities).” (Weimer and Vining, 2011)

Exc

lud

ab

ilit

y

Rivalry0

1

B

C

H

A

1

A: Pure private good

B: Pure public good

C: Nonrivalgood (e.g. TV transmission)

H: Congestible pubic good (e.g. limited access highway)

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good, another dimension that influences the role of public policy is the right-based aspects of

the good (Simon, 2007).

3. Decision-making

Since public policy making is primarily based on decisions taken by responsible parties, a

very brief overview of the decision-related concepts and theories is presented in the following

paragraphs, so as to complement conceptually the part of the literature review related to

public policy making and implementation.

3.1. Decision Typologies

Griffin and Moorhead (2010) distinguish between programmed and non-programmed

decisions. More precisely, they define as programmed a decision that recurs often enough for a

decision rule to be developed, where a decision rule is defined as a statement that tells a

decision maker which alternative to choose based on the characteristics of the decision

situation. On the other side, they define as nonprogrammed a decision that recurs infrequently

and for which there is no previously established decision rule; the form of decision making in

this situation is a problem solving approach, in which the issue is unique and alternatives must

be developed and evaluated without the aid of a programmed decision rule. In the same

spirit, Mintzberg et al. (1976) characterize unstructured the decision processes that have not

been encountered in quite the same form and for which no predetermined and explicit set of

ordered responses exists in the organization.

In the outset we have to distinguish two theoretical perspectives of decision making: the

micro-perspective, i.e. the decisions of one individual and the macro-perspective, i.e. the decisions

made in an organizational context, involving more than one individual. Of course, there is a

two-way interaction between these approaches in the sense that an organizational (macro)

decision, as e.g. investment in certain infrastructure, is heavily dependent on the individual

(micro) decisions of each decision maker involved in the process, based on their cognitive,

psychological, preferential and cultural characteristics.

3.2. Overview of Relevant Theories

3.2.1. Decision-making theories

3.2.1.1. Pure and Bounded Rationality

Rationality is one of the most influential concepts in decision making theories, with

literature contributions from many disciplines such as social sciences, economics, psychology

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etc. Developing a theory that represents human behavior in the most realistic way has been a

challenge for scholars for many years. Thus, departing from pure rationality, through

bounded rationality and nowadays to behavioral economics, decision making theories are

evolving so as to incorporate more sophisticated and complex aspects of individual and

collective behavior.

Bounded rationality has two main research streams, namely Simon and Lindblom’s

perspectives, which focus on how adaptive we can be despite our cognitive constraints and

Kahneman and Tversky’s approach, which emphasizes how easily we can err even when

confronted by simple problem.

The term of bounded rationality is coined by Herbert Alexander Simon, who postulates that

“with the discovery of voluminous discordant empirical evidence3, maximizing expected

utility is rapidly disappearing as the core of the theory of human rationality, and a theory of

bounded rationality, embracing both the processes and products of choice, is replacing it”. A

central element in Simon’s theory is the concept of satisficing, which assumes that a decision

maker has an internal standard, an aspiration level, which partitions all current payoffs into

satisfactory and unsatisfactory (Bendor, 2010).

According to Simon (1997), theories of bounded rationality can be derived from Subjective

Expected Utility (SEU) theories by relaxing one or more of the (SEU) assumptions of fixed

set of alternatives to choose from, known probability distributions of outcomes or

maximization of a utility function and assume instead a process for generating alternatives,

introduce estimating procedures or look for strategies for dealing with uncertainty that do

not assume knowledge of probabilities and postulate a satisficing strategy, respectively

(Simon, 1997).

In other words, to satisfice is to pursue not the best option, but a good enough option, thus a

satisficer often moves in the direction of maximization without ever having it as a deliberate

goal (Schwartz et al, 2002).

3.2.1.2. Incrementalism or Muddling through model

Incrementalism is a formal title for what is otherwise known as the science of muddling

through, which advocates moving not so much toward a goal as away from trouble, trying

this or that small maneuver without any grand plan or sense of ultimate purpose (Etzioni,

2001). The term muddling through was coined by Lindblom (1959).Another issue

highlighted by Lindblom (1982) is that the concept of incrementalism is widely used in policy

3 For summaries of some empirical research on rationality and bounded rationality the reader is prompted to see Eisenhardt and Zbarack (1992).

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analysis but when taken into closer consideration, he identified three meanings; simple

incremental analysis, disjoint incrementalism and strategic analysis (see Table 2 for

definitions).

Table 2: Three meanings of incrementalism as policy analysis (based on Lindblom, 1982; tabulated by

the author)

Incrementalism as… Meaning

simple incremental

analysis

Analysis limited to consideration of alternative policies all of which are

only incrementally different from the status quo

disjoint

incrementalism

Analysis marked by a mutually supporting set of simplifying and focusing

stratagems of which simple incremental analysis is only one, the others

being the following:

• Limitation of analysis to a few somewhat familiar policy alternatives,

• An intertwining analysis of policy goals and other values with the

empirical aspects of the problem,

• A greater analytical preoccupation with ills to be remedied than

positive goals to be sought,

• A sequence of trials and errors and revised trials,

• Analysis that explores only some, not all, of the important possible

consequences of a considerate alternative

• Fragmentation of analytical work to many (partisan) participants in

policy making

strategic analysis Analysis limited to any calculated or thoughtfully chosen set of strategems

to simplify complex policy problems.

Extended from the decision-making realm to the public policy realm, incrementalism means

that policy choice at a particular time is a marginal adjustment from a previous policy choice

(Jones and Baumgartner, 2005).

3.2.1.3. Adaptive (or Mixed scanning or humble) decision making

According to Etzioni (2001) this model of decision making involves two sets of judgments:

firstly, broad, fundamental choices about the organization’s basic policy and direction and

secondly incremental decisions that prepare the way for new, basic judgments and that

implement and particularize them once they have been made. Thus, mixed scanning is much

less detailed and demanding than rationalistic decision making, but still broader and more

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comprehensive than incrementalism (Etzioni, 2001). He also identifies some adaptive

procedures in face of partial knowledge:

• Focused trial and error (knowing where to start the search for an effective

intervention, and checking outcomes at intervals to adjust and modify the

intervention).

• Tentativeness (a commitment to revise one’s course as necessary).

• Procrastination (delay permits the collection of fresh evidence, the processing of

additional data, the presentation of new options) through decision staggering or

fractionalizing.

• Hedging bets or maintaining strategic reserves.

3.2.1.4. Decision Making Determinants

Risk and uncertainty are the most important parameters in decision making and they are

highly related to the concepts of luck or asymmetry of information, the decision-makers

rationality, as well as his/her preferences and expectations.

Hammond et al (2001) argue that making wise trade-offs is one of the most important and

difficult challenges in decision making, since the more alternatives you’re considering and the

more objectives you’re pursuing, the more trade-offs you’ll need to make. Furthermore, they

also claim that the consequences of the objectives should be identified and mapped in a

consequence matrix.

Decision-making is very heavily influenced by the psychology of the decision maker as well as

a number of external factors. Payne et al (1988) examine the influence of effort and accuracy

in the adaptive use of decision processes. They concluded that highly adaptive in responding

to changes in the structure of the available alternatives and to the presence of time pressure.

Furthermore, they postulate that the major classes of factors that influence the choice of

strategy when it comes to a particular decision problem are the characteristics of the decision

problem, of the person and of the social context (Figure 3). (Payne et al, 1993). Thus, the

importance of the adaptability attribute is highly recognized not only in adaptable decision

making, but also in adaptable public policy making, as well as adaptable governance.

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Figure 3: Contingent strategy selection (adapted from Payne et al., 1993)

Gigerenzer and Gaissmaier (2011) investigated the heuristics of decision-making and they

concluded that individuals and organizations often rely on simple heuristics in an adaptive

way, and that ignoring part of the information can lead to more accurate judgments than

weighting and adding all information. These interesting results point out the importance of

information and the de facto use of heuristic decision making models. They also argue that

by identifying common building blocks, from which the various heuristics are constructed,

theory is developed on the basis of an organizing principle (Gigerenzer and Gaissmaier, 2011).

In this context, they cite the three building blocks proposed by Gigerenzer et al (1999):

1. Search rules specify in what direction the search extends in the search space.

2. Stopping rules specify when the search is stopped.

3. Decision rules specify how the final decision is reached.

Anderson et al (2003) identified four adaptive decision- and problem-solving processes, the

characteristics of which are presented in Table 4:

4. Static decision making

5. Passive adaptive management

6. Active (or experimental) adaptive management

7. “Evolutionary” problem solving

3.2.1.4.1. Conflicts

Conflicts are also an important aspect of decision making, both in an individual and an

organization level. Janis and Mann (1977) developed the “Conflict model of decision making”

which identified common patterns of decision making behavior that include defensive

avoidance (delaying decisions unduly), overreaction (making decisions impulsively in order

to escape the anxious state), and hypervigilance (obsessively collecting more and more

information instead of making a decision) (as cited by Etzioni, 2001). Their model is

structured on information available and a sequence of logical questions regarding the

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existence of serious risks in the case of no change, in the case of change, the existence of a

realistic better solution and the existence of sufficient time. Furthermore, Galtung (1967)

identified two fundamental types of conflict, namely structure and actor conflicts, which are

based on vertical and horizontal interactions respectively.

According to Giddens (1984) there is a difference between conflict and contradiction.

According to his view, (structural) contradiction is defined as “disjunction of structural

principles of system organization”, while conflict is the “struggle between actors or

collectivities expressed as definite social practices”.

Finally, there are many moments that conflicts can arise, mainly because of differences in

preferences and interests, such as for example when one industry is preferred over another,

leading to conflict over policy, or conflicts over property rights, or conflicts among

consumers with different interests and ability as well as between consumers and producers

(Schmidt, 2004). In an intra-organizational context, Rainey (2009) mentions that conflicts

exist within a person, between people, and within and between groups and organizational

departments or divisions, both in horizontal and vertical direction.

3.2.2. Causal theories

Stone (2002) distinguishes two models of political society, namely the market model and the

polis model. In rough terms, the former is based on the individual, its self-interest

maximization and competition, while the latter is based on the community, the public

interest, loyalty and completion along with cooperation among groups and organizations.

She also argues that policy is the rational attempt to attain objectives, the primary of which

are equity, efficiency, security, liberty and community, while there are tradeoffs involved

among these goals. Problem identification can be approached either through symbols4 /

words or numbers, while there are two primary frameworks for interpreting the world,

namely, the natural and the social. She also argues that the distinctions between action and

consequences and between purpose and lack of purpose can form the base of a framework for

describing the types of causal theories into mechanical, accidental, intentional and

inadvertent causes (Table 3). Many policy problems, though, require a more complex model

of cause, such as for instance complex systems models, institutional models or historical

models.

4 Four aspects of symbolic representation are especially important in the definition of policy problems, namely, narrative stories, synecdoches (figures of speech in which part is used to represent the whole, metaphors and ambiguity (Stone, 2002)

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Table 3: Types of causal theories with examples (Stone, 2002)

Consequences

Intended Unintended

Unguided

MECHANICAL CAUSE

intervening agent(s)

brainwashed people

machines that perform as

designed, but cause harm

ACCIDENTAL CAUSE

nature

weather

earthquakes

machines that run amok

Purposeful

INTENTIONAL CAUSE

oppression

conspiracies that work

programs that work as

intended but cause harm

INADVERTENT CAUSE

intervening conditions

unforeseen side effects

avoidable ignorance

carelessness

omission

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Table 4: Characteristics of four adaptive decision- and problem-solving processes (adapted from Anderson et al, 2003)

Static decision making Passive adaptive

management Active (experimental) adaptive management Evolutionary problem solving

Characteristics related to the nature of the ecological problem

Units under

consideration One project One or more projects

One experiment (usually involving several projects as

replicates) Many small, independent prototypes

Ongoing

monitoring Not required Essential Essential Essential; coordinated among projects

Decision points

Single—assumptions about all

future conditions and actions

are made at the time of analysis.

Multiple Multiple Multiple

Choice at decision

points

Best apparent management

option is chosen at start of

Best apparent management

option is chosen at each

A range of management options is explored in early

decision points. Inferences are made and best apparent

management option chosen and applied at later

decision point.

Managers copy and adapt features of

the most successful prototypes as

they share experiences. Particularly

promising cases are singled out for

intensive study.

Characteristics related to the internal social context

Analytic

requirements

High, if all decision analysis

steps are completed.

Moderate to high; reliability of

learning depends on quality of

monitoring and time-series

analysis.

High, including experimental design and statistical

analysis at end of experiment when inferences are

made

Low to moderate; progress in

improving practice depends largely

upon design of communication

processes

Social organization

required of the

decision makers

Decision process is not

dependent on social factors, but

stakeholders should help

develop the decision tree.

Continuity of oversight; time-

frame may exceed manager’s

professional “lifespan.”

Managers must become scientists, so social

organization must nurture curiosity, credit, and checking.

Timeframe may exceed manager’s professional

“lifespan”.

Social organization must facilitate

innovation, diffusion, and adaptation.

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Characteristics related to the external social context

Goals and

objectives

Goals must be clearly defined at

the outset, with quantifi able

objectives. Outcomes are

evaluated with a single metric.

Goals and objectives should be

clearly defined.

Goals will include a balance between management

goals and learning. Hypotheses to be tested must relate

to those goals.

Multiple, incommensurable goals are

the norm.

Uncertainty and

learning

Uncertainty is explicitly

included in initial choice, but

will not be resolved.

Learning is a goal, but

information at later decision

points may be unreliable, owing

to possible confounding factors.

Learning is a goal, and a good experimental design

should produce reliable new information for later

decision points.

The chief benefit is improved practice

over time, but learning about

causation will usually occur as well.

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4. Strategy

In general policy formulation and implementation finally relate to the decisions that are

taken and the choices that are made for the strategies that fit best the policy objectives

defined beforehand. What is strategy and how it is developed has been extensively covered in

the literature, with Mintzberg´s work dominating (deliberate and emerging strategy (Figure

4). A summary of the strategy typologies is presented in Table 5, so as to assist the public

policy overview of this paper.

Figure 4: Types of strategies (adapted from Mintzberg and Waters (1985))

Table 5: Summary description of types of strategies (Columns 1&2 adapted from Mintzberg and

Waters (1985), Column 3 added by the author, based on Mintzberg and Waters (1985))

Strategy Major features Graphical representation

Planned Strategies originate in formal plans:

precise intentions exist, formulated and

articulated by central leadership, backed

up by formal controls to ensure surprise-

free implementation in benign,

controllable or predictable environment;

strategies most deliberate

Entrepreneurial Strategies originate in central vision:

intentions exist as personal,

unarticulated vision of single leader, and

so adaptable to new opportunities;

organization under personal control of

leader and located in protected niche in

environment; strategies relatively

deliberate but can emerge.

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Ideological Strategies originate in shared beliefs:

intentions exist as collective vision of all

actors, in inspirational form and

relatively immutable, controlled

normatively through indoctrination

and/or socialization; organization often

proactive vis-à-vis environment;

strategies rather deliberate

Umbrella Strategies originate in constraints:

leadership, in partial control of

organizational actions, defines strategic

boundaries of targets within which

other actors respond to own forces or to

complex, perhaps also unpredictable

environment; strategies partly

deliberate, partly emergent and

deliberately emergent

Process Strategies originate in process:

leadership controls process aspects of

strategy (hiring, structure, etc.), leaving

content aspects to other actors;

strategies partly deliberate, partly

emergent (and, again, deliberately

emergent)

Unconnected Strategies originate in enclaves: actor(s)

loosely coupled to rest of organization

produce(s) patterns in own actions in

absence of, or in direct contradiction to,

central or common intentions; strategies

organizationally emergent whether or

not deliberate for actor(s)

Consensus Strategies originate in consensus:

through mutual adjustment, actors

converge on patterns that become

pervasive in absence of central or

common intentions; strategies rather

emergent

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Imposed Strategies originate in environment:

environment dictates patterns in actions

either through direct imposition or

through implicitly pre-empting or

bounding organizational choice;

strategies most emergent, although may

be internalized by organization and

made deliberate

??????

Legend: V=vision, I=ideology

5. What is public policy?

Public policy in general terms is related to the public or government intervention in various

aspects involving private, public, toll, common etc goods. Definitions in the literature span

from general approaches, as for example Anderson’s (2006) (cited in Kraft and Furlong,

2007) definition of public policy as a “policy adopted by a public institution, typically to

address a problem faced by society or by particular groups in society” to a more specific one

such as Birkland’s (2005) perception of public policy as a “statement of government of what

it intends to do or not to do, such as laws, regulation, ruling, decision or order or a

combination of these”. He also argues that “the lack of such statements may also be an

implicit statement of policy” (Birkland, 2005).

Similarly, Stone (1997) defines policy as the rational attempt to attain objectives and public

policy is about communities trying to achieve something as communities. The primary

objectives, according to her view, are equity, efficiency, security, liberty and community,

while there are tradeoffs involved among these goals.

6. Public policy types

There is a great number of public policy typologies in the literature. The most simple

classification, is according to the policy area or topic (e.g. transportation policy, land use

policy, health policy etc), but as Birkland (2005) puts it, “it did not help us draw general

conclusions about the politics that underlie these polices”. This gap was filled in by Lowi´s

seminal work (1964), who categorized public policies, as (Parsons, 1995):

• Distributive (of new resources)

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• Redistributive (of existing resources)

• Regulatory (regulation and control of activities)

• Constituent (setting-up or reorganization of institutions)

Figure 5: Lowi´s Policy Typologies (adapted from Simon, 2007)

Lowi´s typology has been criticized on its simplicity and the difficulty to clearly separate the

types, but proponents of the typology argue that the perception of the types as a continuum

constitutes an arguments to the critics (Stewart et al, 2008).

This typology was further enhanced by Ripley and Franklin (1982) (cited by Hill and Hupe,

2002) who further disaggregated the regulatory policy type into:

• Protective regulatory,

• Competitive regulatory

Anderson (2005) proposed an addition to Lowi´s typology, that of suasion policies, which

can be manipulative, persuasive or somewhere between, and contrasts to the coercive power

of the previously mentioned typologies. He analyzed US Public health policy through the

lenses of the suasion approach.

Another relevant classification of politics in policymaking is provided by Wilson (1973, 1989)

(cited by Mintrom, 2000), who categorized politics in terms of the perceived benefits and

costs, namely the level of their concentration or dispersion (Table 6).

Table 6: Wilson´s Classification of the Politics of Policy Issues (adapted from Mintrom, 2000)

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Perceived costs

Perceived Benefits Distributed Concentrated

Distributed Case 1

Majoritarian politics

Case 2

Entrepreneurial politics

Concentrated Case 3

Client politics

Case 4

Interest group politics

7. Why is there a need for public policy and government

intervention?

After defining public, private goods and public policy, the question that emerges is relevant

to the existence of a relationship among these concepts. In other words, what are the

conditions and necessities that justify government intervention when it comes to the

production or supply of goods? It has to be noted that private goods can be provided /

consumed by both private and public actors, and correspondingly public goods can me

provided / consumed by both private and public actors as well. Thus, the implications of this

statement are that the state, while conceiving, formulating and implementing public policy,

needs to take into account various actors, representing various interests and having different

objectives.

According to Weimer and Vining (2011), the presence of nonrivalry, nonexcludability or

congestion arising from changes in levels of demand can lead to failure of markets to achieve

Pareto efficiency, while the presence of either nonrivalry or nonexcludability is a necessary

condition for the existence of public good market failure. Thus, market failure (1-4) and other

competitive limitations (5-10) are substantial reasons for public policymaking (Weimer and

Vining, 2011):

1. Public Goods

2. Externalities

3. Natural monopolies

4. Information asymmetries

5. Thin markets (cartelization)

6. Preference problems

7. Uncertainty problems

8. Intertemporal problems

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9. Adjustment costs

10. Macroeconomic Dynamics

8. Actors in public policy

The actors (official or unofficial) that are involved in the public policy process are many and

their roles and behaviors influence the quality, success or even existence of a certain policy.

Actors, whether stakeholders or not, may give rise to conflicts or promote cooperation and

convergence throughout the process, influencing this way the outcomes or the performance.

A very illustrative representation of the above is provided by Considine (2005), though three

public policy scenarios that investigate the role of various actors and their engagement in the

public policy process, through stances of conflict and convergence. Of course, the categories

of the actors involved depend on the specific socio-economic context and the political

structure, but there are certain actor categories that are traditionally involved in all public

policy processes. For the context of South Africa, Hendrickse (2006) identified the following

actors in the public policy process:

• Legislators at national, provincial and local government level (by producing laws,

ordinances, and by-laws respectively)

• (elected) Political office bearers,

• Public office bearers,

• The public (individual citizens - through voting or petition drafting – or

interest/pressure groups/associations – though public participation)

• The media,

• Opposition Political parties,

• International institutions,

• Other states and international influences

Hanekom (1987) (cited by Hendrickse, 2006) stresses out that public office bearers have

various roles, such as:

• Policy innovators,

• Policy advisers,

• Policy formulators,

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• Policy implementers

• Policy monitors

• Policy analysts

• Policy evaluators

Similarly Cahn (2013), distinguishes institutional (Congress, The President and the

Executive Bureaucracy, The Courts) and non-institutional actors (public, media, Parties,

Interest Groups, Political Consultants), the role of which, as well as the relationship between

them, ultimately determine policy outcomes.

Finally, Howlett (2011) considers four distinct “communities” of upper level policy advisors,

based on whether they belong to the government or not and whether they are close to the

decision –makers or not, namely core actors, public and private sector insiders and outsiders

(Table 7). Furthermore, in his own words, “different sets of actors, with different sets of ideas

are active at different levels of policy formulation and policy design”, as depicted in Table 8.

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Table 7: Howlett´s four communities of policy advisors (adapted from Howlett, 2011)

Proximate actors Peripheral actors

Public/governmental sector Core actors: Public sector insiders:

Executive staff

Central agencies and task

forces

Professional governmental

policy analysts

Commission, committees

Research councils/scientists

International organizations

Non-governmental sector Private sector insiders:

Consultants

Political party staff

Pollsters

Donors

Outsiders:

Public interest groups

Business associations

Trade unions

Academics

Think tanks

Media

International non-

governmental organizations

Table 8: Howlett´s general model on ideas, actors and instruments (adapted from Howlett, 2011)

Governance mode Policy regime Programme level

Policy level High-level

abstraction

Programme-level

operationalization

Specific on-the-

ground measures

Policy goals General abstract

policy aims

Operationalizable

policy objectives

Specific policy

targets

Policy ideas World views and

ideologies

Policy paradigms Causal stories

Policy actors Public, outsiders

and insiders

Public and private

sector

Core actors

Policy means General policy

implementation

preferences

Operationalizable

policy tools

Specific policy tool

calibrations

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The “Iron Triangle” or subgovernment model is one attempt to establish interrelationships,

and it is defined as a triangle of mutually reinforcing relationships between three types of

players: the representatives of the regulated or benefit interests, the legislators (the

congressional committee or subcommittee in the US context) and the agency that is charged

with the regulating responsibility (Birkland, 2005) (or alternatively administration or

bureaucracy) (Figure 6).

Figure 6: The Iron Triangle (adapted from Schwartz, 2011)

The term of policy community was introduced to express a new approach to public policy

making. Indeed, policy community is defined as “[t]he group of actors - such as interest

groups, government agencies, the media and the elected officials – who are actively involved

in policy making in a particular domain” (Birkland, 2005). In general terms, the issues that

should be taken into account when analyzing a policy network are the following:

• Structure

• Purpose or function

• Leadership

Coleman and Skogstad (1990), identified five types of policy networks, namely pressure

pluralist, clientele pluralist, corporatist, unisonal and state directed networks (Table 9),

while Agranoff (2003; 2007) identified four types of networks, based on their purpose:

• informational networks,

• developmental networks,

• outreach networks, and

• action networks

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Furthermore, Rhodes (1997) provides a similar classification of policy networks (Table 10),

while according to Marsh and Rhodes (1992), public communities and issue networks

express the two extremes of the spectrum of policy networks, the differences of which are

presented in the comparative Table 11.

Leadership in networks is another issue of importance. Silvia and McGuire (2010) compared

three types of leadership behavior (organization-, people-, and task-oriented) between

network and hierarchical/single-agency structures. They concluded that “while the frequency

of organization-oriented behaviors vary widely between the agency and network contexts,

leaders in their networks focus more on people-oriented behaviors and less on task-oriented

behaviors when compared to leading their agency”.

Table 9: Policy networks typology and characteristics (Coleman and Skogstad, 1990; adapted from

Ranaei et al, 2010)

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Table 10: Rhodes policy networks typology (Rhodes, 1997; adapted from Löffler, 2009)

Type of network Characteristics of network

Policy community/territorial community Stability, highly restricted membership. Vertical

interdependence, limited horizontal articulation

Professional network Stability, highly restricted membership. Vertical

interdependence, limited horizontal

articulation, serves interest of profession

Intergovernmental network Limited membership, limited vertical

interdependence, extensive horizontal

articulation

Producer network Fluctuating membership, limited vertical

interdependence, serves interest of producer

Issue network Unstable, large number of members, limited

vertical interdependence

Table 11: Types of policy networks compared (Marsh and Rhodes (1992), adapted from Vigar, 2002)

Dimension Policy community Issue network

Membership

Number of participants Very limited, some groups

consciously excluded

Large

Type of interest Economic and/or

professional interest

dominate

Encompass range of affected

interests

Integration

Frequency of interaction Frequent, high-quality,

interaction of all groups on

Contacts fluctuate in

frequency and intensity

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all matters related to policy

issue

Continuity Membership, values, and

outcomes persistent over

time

Access fluctuates

significantly

Consensus All participants share basic

values and accept the

legitimacy of the outcome

A measure of agreement

exists, but conflict is ever

present

Resources

Distribution f resources

(within network)

All participants have

resources; basic relationship

is an exchange relationship

Some participants may have

resources, but they are

limited, and basic

relationship is consultative

Distribution f resources

(within participating

organizations)

Hierarchical; leaders can

deliver members

Varied and variable

distribution and capacity to

regulate members

Power There is a balance of power

among members. Although

one group may dominate, it

must be a positive-sum game

if community is to persist

Unequal powers reflecting

unequal resources and

unequal access. It is a zero-

sum game

9. Conflicts in policy making

Policy making is a very diverse and complex process thus it is evident that the existence of

various types of conflicts is more than anticipated. Many factors can contribute to this

situation, as for example different types of overlaps that create conflicting interests, power

conflicts, or even value conflicts.

As Gigerenzer (2001) puts it, optimization of goals and aspirations is a difficult and often

impossible task, due to a number of reasons, including:

• If multiple competing goals, optimization can become a heavy and unbearable

computational burden,

• If incommensurable reasons (or cues) exist, optimization can be impossible,

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• If the alternatives are unknown and need to be generated in a lengthy process of

search, optimization models assuming a finite, known choice set do not apply.

• If the cues or reasons are unknown and need to be generated in a lengthy process of

search, optimization models assuming a finite, known set of predictors do not apply.

• If future consequences of actions and events are unknown and need to be generated

in a lengthy process of search, optimization models assuming a finite, known set of

consequences do not apply.

• If optimization is attempted for the multitude of decisions an organism faces in real

time, this can lead to paralysis by computational explosion.

As mentioned before, the existence of overlaps in the institutional and organizational

structure of the policymaking system is usually a probable source of conflicts. McConnel

(2010) identified the following types of overlaps in the policymaking context:

• Overlap between policy sectors (e.g. industry, environment, transport, commerce,

trade)

• Overlap between constitutional areas of responsibility (e.g. national, state/province,

regional, local)

• Overlap between quasi-constitutional areas of government (e.g. quasi-autonomous

non-governmental bodies, public private partnerships

• Decision-making tradeoffs that need to be made (e.g. allocating resources to one

policy area and not to another.

Furthermore, other important aspects of policy making are the ethical issues and the value

conflicts that that rise during the process. In the case of the policy analyst whose functions

are characterized by a principal-agent relationship, the challenge of value conflicts can be

more evident. Indeed, Weimer and Vining (2011) identified two examples of value conflicts,

i.e. the demand by the employer/client for cooked results and misrepresentation of results to

other participants in the decision-making process.

The question of how the agent can overcome this ethical conflict could be addressed by

Weimer and Vining’s (2011) framework for alternative responses to Value Conflicts5 (Figure

7), where the analyst/agent chooses pure or mixed strategies from an action set of three major

alternatives: protesting (voice), resigning (exit) or sabotaging (disloyalty to the client).

5 This framework draws heavily on Hirschman’s (1970) work (Weimer and Vining, 2011)

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Figure 7: Alternative responses to Value Conflicts (adapted from Weimer and Vining (2011))

10. Public Policy Analysis Models

Public Policy research demonstrates a collection of Public Policy Analysis models that have

been developed in order to address its complexity and disaggregate the process and so as to

identify causal relationships among its various components. Herewith we present a summary

of the main theories, models and frameworks, that have been developed to address certain,

and most often, different, parts (or stages) of the whole public policy process. Furthermore, a

number of indicative examples, whenever available, are presented so as to show the

implementation of the models in the various transportation policy aspects. However, it

should be noted that although there is rich literature on the use of these models in various

policy arenas, transportation, exhibits significant limitations in the body of this part of the

literature. Hopefully, this gap in the literature will be gradually filled in, as scholars

understand the importance of “good” public policy formulation and implementation in all

areas, modes and levels transportation.

10.1. Stages or Policy Cycle model

The Stages or Policy cycle model has been the most widely accepted model for the analysis of

public policy. The fist decision-making models, such as Simon´s (1947) can be considered the

far origin of this linear approach. Through time and evolution, Lasswell (1956) introduced it

in the public policy realm, identifying seven stages; Intelligence, Promotion, prescription,

Invocation, Application, Termination and appraisal. Since then a great number of variations

was developed by various actors (e.g. Table 12), with a varying degree of differentiation from

Lasswell´s model.

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Table 12: Evolution from Simon´s decision making model to the stages or policy cycle model (various

sources)

MODEL DESCRIPTION AUTHOR

� Intelligence

� Design

� Choice

Simon (1947)

� Intelligence

� Promotion

� Prescription

� Invocation

� Application

� Termination

� Appraisal

Lasswell (1956)

� Deciding to decide: problem recognition

� Formulating alternatives and criteria

� Decision Proper

� Effectuation

� Correction and Supplementation

Mack (1971)

� Public recognition of a policy to exist

� How issues are placed on the agenda of public controversy

� How demands are advanced

� The form of government involved in policy making

� Resources and constraints

� Policy decisions

� What determines governmental choice

� Choice in its context

� Implementation

� Outputs

� Policy Evaluation

� Feedback

Rose (1973)

� Initiation

� Information

� Consideration

� Decision

� Implementation

� Evaluation

� Termination

Jenkins (1978)

� Deciding to decide (issue search or agenda setting) Hogwood and Gunn

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MODEL DESCRIPTION AUTHOR

� Deciding how to decide (issue filtration)

� Issue definition

� Forecasting

� Setting objectives and priorities

� Options analysis

� Policy implementation, monitoring and control

� Evaluation and review

� Policy maintenance, succession and termination

(1984)

� Identify issues

� Policy analysis

� Policy instruments

� Consultation

� Coordination

� Decision

� Implementation

� Evaluation

Bridgman and Davis,

1998; adapted from

Nutley and Webb,

2000)

� Define the problem

� Assemble some evidence

� Construct the alternatives

� Select the criteria

� Project the outcomes

� Confront the trade-offs

� Decide!

� Tell your story

Bardach (2005)

� Initiation

� Estimation

� Selection

� Implementation

� Evaluation

� Termination

Fox et al (2006) –

Table 13

Table 13: The six basic phases of public policy process, according to Fox et al. (2006)

Phase Characteristics

Initiation Creative thinking about a problem

Definition of objectives

Option design

Tentative and preliminary exploration of concepts, claims and possibilities

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Estimation Investigation of concepts and claims

Examination of impacts

Normative examination of likely consequences

Development of program outlines

Establishment of expected performance criteria and indicators

Selection Debate of possible options

Compromises, bargains and accommodations

Reduction of uncertainty about options

Integration of ideological and other non-rational elements of decision

Decisions among options

Assignment of executive responsibility

Implementation Development of rules, regulations and guidelines to carry out decision

Modification of decision to reflect operational restraints

Translation of decision into operational terms

Setting up programme objectives and standards, including schedule of

operations

Evaluation Comparison of expected and actual performance levels in terms of

established criteria

Assignment of responsibility of discovered discrepancies in performance

Termination Determination of costs, consequences and benefits for reductions or

closures

Editing as necessary and required

Specification of new problems created during termination

For reasons of establishing a working hypothesis, we adopt the conventional way to describe

the chronology of a policy process (Jann and Wegrich, 2007)

• agenda-setting,

• policy formulation,

• decision making,

• implementation, and

• evaluation (eventually leading to termination)

10.2. Garbage can model of organizational choice

Cohen et al (1972) developed the “garbage can model” so as to analyze organizational choice,

which later on was extended to other scientific areas such as institutional analysis (March

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and Olsen, 1989), governance (Peters, 2002) and public policy (Kingdon, 1984). This model

lies between the decision making and public policy analysis spectrum of models, and is

directly related to the Multiple Streams model, that is reviewed in the following paragraph.

The primary concept that dominates this model is the unstructured character of decisions.

The generic model structure is based on four variables, namely; problems, solutions, participants

and choice opportunities. Thus, a simple model, as presented in Cohen et al´s (1972) seminal

paper, includes four streams, each one a function of time, and a set of three garbage

processing assumptions:

1. A stream of m (fixed) number choices, characterized by:

• an entry time (the calendar time at which that choice is activated for

decision),

• a decision structure, a list of participants eligible to participate in making

that choice.

2. A stream of w problems, characterized by:

• an entry time (the calendar time at which the problem becomes visible),

• an energy requirement (the energy required to resolve a choice to which the

problem is attached and

• an access structure (a list of choices to which the problem has access).

3. A rate of flow of solutions

• a solution coefficient, ranging between 0 and 1, which operates on the

potential decision energies to determine the problem solving output

(effective energy) actually realized during any given time period is specified.

4. A stream of energy from participants.

• there is some number, v, of participants and in each time period, each

participant can provide some specified amount of potential energy to the

organization

The three model assumptions are the following (Cohen et al, 1972):

1. Energy additivity assumption (each choice requires as much effective energy as the

sum of all requirements of the several problems attached to it)

2. Energy allocation assumption. (The energy of each participant is allocated to no more

than one choice during each time period)

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• Problem allocation assumption. Each problem is attached to no more than one choice

each time period)

10.3. Multiple streams model

The multiple streams model of policy process was developed by Kingdon (1984) and it aims

at explaining the agenda setting process in public policy making, adapting Cohen et al´s

(1972) “garbage can model” of organizational choice (Mucciaroni, 1992). The framework is

structured on five elements (Figure 8):

• Problem stream

• Politics stream

• Policy (Solution) Stream

• Policy Window

• Policy entrepreneurs

Figure 8: Kingdon´s Multiple Streams Model (in Zachariadis, 2003; adapted from Zachariadis, 2007)

In summary, if the three independent (see assumptions later on) streams of problems, politics

and policies are (successfully or not) coupled by a policy entrepreneur (individual or

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corporate actor) at a critical moment in time (policy window), then there is a high

probability of the specific problem to enter the political agenda (Kingdon, 1995; Zachariadis,

2007).

Elaborating more on the three stream and following Zachariadis (2007), it can be said that

issues are identified (or not) as problems, through a series of indicators or through a

“focusing event” or crisis (i.e. an incident that drew attention, e.g. an accident etc), or

through feedback from other areas or policies (such as spillovers, successes or failures etc).

The problem load, namely the “number of difficult problems” influences the level of attention

given to an issue-problem by the policy maker(s) (Zachariadis, 2007).

In a parallel stream, the national mood and the ideology of the parties create certain political

culture conditions. Zachariadis (2007) specifies further the elements that comprise this

stream into national mood, pressure group campaigns and administrative/legislative

turnover, arguing that the combination of national mood and governmental turnover is the

most influential in the agenda setting process.

The third parallel stream of policies or solutions to the policy problems that succeeded in

receiving attention, complements the streams environment. These solutions, which can vary

in number and content, are evaluated against certain criteria, such as the proximity to the

decision makers´ values or the technical feasibility of the proposed solution. Furthermore,

Zachariadis (2007) points out, the role of the policy networks and the level of their

integration, in terms of access, mode, size and capacity.

Policy entrepreneurs are active both in the problem and the policy stream (Guldbrandsson

and Fossum, 2009), and their success relies on their access to resources and people, as well

as the specific strategies they use to achieve the promotion of the policy issues, always in

relation to the policy window that opens when the conditions are favorable for the coupling

of the streams.

There are a number of assumptions that underlie the model, summarized by Zachariadis

(2007) as:

• Individual attention or processing is serial, which means that an individual policy-

maker level, there is a limited capacity in issue consideration. Conversely, systemic

attention or processing is parallel, meaning that in a system or organization level, the

capacity to process issues is larger (up to a certain limit of course).

• Policy makers operate under significant time constraints

• The streams following through the system are independent

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Kingdon´s model exhibits similarities to Simon´s bounder rationality approach (esp the

satisficing strategy), in the sense that “the sequence in which solutions are considered

strongly affects the decision outcome” (Zachariadis, 2007). However, as Zachariadis (2007)

argues, the two frameworks differ in the theorizing direction (micro-to-macro in the case of

bounded rationality, instead of macro-to-micro level in the case of the multiple streams

model).

Mucciaroni (1992) criticized Kingdon´s model as being indeterminate to provide fully

satisfactory explanations about the attention that some issues receive in the political arena

against others, using two case studies, namely tax reform and deregulation to support his

arguments. Similarly, Sabatier (1999) (in Zachariadis, 2007) argues that the Multiple

Streams framework underspecifies the causal processes driving choice, limiting them to

attention, search and selection.

As far as implementations of the framework in the transportation sector are concerned, some

examples are presented herewith. Khayesi and Amekudzi (2011) studied the problem of

automobile dependence in the city of Curitiba in Brazil, using the Multiple Streams

Framework. They concluded that the political system in Curitiba was mostly responsible for

the opening, closing and maximization of policy windows and they highlight the role of the

city leaders who have strongly supported transport policy change.

Chen (2011) used the Multiple Streams Model to study Policy Windows for High-Speed Rail

(HSR) in the US. He states that although HSR has been a policy option for some time,

economic recession as well as the transition of the federal government administration that

finally opened the policy window. The fact that two perspectives are used to evaluate the

HSR policy, namely, long-term (sustainable median distance travel service), and short-term

(job creation and economy stimulation) will play a part in the utilization of the window or

not and the final implementation of the policy or not.

10.4. Advocacy Coalition Framework

The Advocacy6 Coalition Framework (ACF) was developed by Sabatier and Jenkins Smith

(1988), aiming at explaining American Public Policy change that was dominated by coalitions

and conflictual relationships. The ACF framework was enriched and modified throughout

the years, based on empirical findings, reaching its most recent form that is presented in

Figure 9 (Sabatier and Weible, 2007).

6 Policy advocacy “involves research and arguments which are intended to influence the policy agenda inside and/or outside government” (Parsons, 1995)

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In a nutshell, the unit of analysis is the policy subsystem and the three “foundation” stones of

the framework are the following (Sabatier and Weible, 2007):

1. A macro-level assumption that the broader socioeconomic and political factors affect

the behavior of the policy making specialists within the policy subsystem.

2. A micro-level model a socio-psychological approach to individual behavior

3. A meso-level belief that “advocacy coalitions” are to solution to the successful

integration of the multiple actors in the policy subsystem.

Figure 9: 2005 diagram of the Advocacy Coalition Framework (adapted from Sabatier and

Weible, 2007)

This multiplicity of actors can be described as a number of interest groups, which share

common policy beliefs and values, and who support certain interests, which interests are

served by a policy change or not. Thus, they form alliances and/or compete in the policy

subsystem, utilizing the available resources.

The role of the policy broker, who is a form of a mediator, is of particular importance, since

(s)he is trying to achieve compromise, in light of the conflicting beliefs, interests and

positions of the coalesced parties. As Birkland (2005) notes, “[p]olicy change is much less

likely if polarization of advocacy coalitions is so great that there is no room in the periphery

of the groups´ belief system in which compromise can be found”. The role of policy brokers is

illustrated in Ingold and Varone´s (2012) study on Swiss Climate Policy, who tried to

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complement the discussion on public brokers with empirical insights on who the policy

brokers are and which institutional rules influence their activities.

As mentioned before, the exogenous factors that influence the policy subsystem (macro-level

assumptions) are also very important, and can be classified into two categories; the relative

stable and the dynamic exogenous factors. Furthermore, these factors influence the policy

subsystem through the opportunity structures, defined as “relatively enduing features of a polity

that affect the resources and constraints of subsystem actors (Sabatier and Weible, 2007)”.

This is the policy change path, namely the exogenous shock path that dominated the original

version of the model. Two alternative paths to major policy change were also considered,

leading to the modification of the ACF framework. These are the internal shocks path and the

negotiated agreement path (Sabatier and Weible, 2007). Finally policy-oriented learning is also

an important element of the framework, in the sense of “relatively enduring alterations of

thought or behavior intentions, which result from experience and which are concerned with

the attainment or revision of the percepts of one´s beliefs system” (Sabatier, 1995).

Sabatier and Weible (2007) summarize the basic criticisms of the ACF framework found in

the literature, as:

1. Obviousness

2. Constant revision and modification of the framework

3. Collective action problem is not addressed (Schlager, 1995)

4. Lack of conceptualized and operationalized institutional variables , compared to the

IAD framework (Ostrom, 2005)

5. Limitations in the explanatory power of the framework regarding the causal

processes

The main criticism of the original framework that it was created on the basis of the American

public policy reality was addressed by the revision of the framework (see Sabatier, 1998).

Although there is a great number of publications that use the AFC framework to analyze

public policy change in various policy subsystems, there is limited bibliographic evidence on

implementation in the transportation sector. Dudley and Richardson (1996) investigated

British trunk road policy change during the years 1945-1995, under the adversarial effects of

the road and environmental lobbies, concluding that although a coalition might hold an

advantage during a certain period of time, the situation can change and that factors

exogenous to policy communities are more probable to invoke radical changes.

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Furthermore, Dudley (2003) analyzed the Oxford Transport Strategy (OTS), where the

element of policy learning process was introduced through the policy broker role (or OTS

troubleshooter, as the authors call him) whose responsibility was to reverse the adverse

climate and alter the perceptions of the Strategy as “repressive “anti-car” regime”. Finally,

Stich and Miller (2008) studied US freight transportation policy change towards

intermodalism, through the lenses of the advocacy coalition framework and concluded that

the formation of a new intermodal coalition would be beneficial to tackle the adversarial

relationships between the road and rail coalitions.

10.5. Punctuated Equilibrium Framework

The Punctuated Equilibrium Framework was developed by Baumgartner and Jones (1993)

and using evolutionary biology7 concepts, it aims at explaining public policy change as a

combination of stasis and crisis (True at al, 2007). More precisely, the objective of this

framework is to “capture this tendency of political systems to drift incrementally most of the

time, only to be roused to major action when collective attention became galvanized around

an issue” (Baumgartner et al, 2006). Furthermore, the role of institutions in this interchange

of stability and crisis is pointed out by True at al, (2007), who note that the periods of

instability and major policy change that perturb the long periods of incremental change

(considered as stability periods), significantly affect the institutional arrangements, while the

new institutions create the basis for a new period of stability.

The main elements of the punctuated equilibrium framework are (Baumgartner and Jones,

1993; Birkland, 2005; True et al, 2007):

• Policy monopoly (policy subsystem, dominated by a single interest and definable

institutional structure responsible for policymaking in an issue area)

• Policy image (empirical information and emotive appeals; driver or change)

• Institutional policy venues (drivers of change; differentiated according to the

context)

Furthermore, Howlett (2009) identified two competing models of punctuated equilibrium

policy dynamics, whose differences lie in the different assumptions about the nature, origins

and effects of both policy punctuations and the stability of policy equilibria.

• Path Dependency

7 For a review of the conceptual differences between Punctuated Equilibrium in Biology and Public Policy, see Givel (2010)

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Although the sequence of events is not a strictly necessary one, predictable from the

conditions of the starting point according to general laws, there is nonetheless an

explicable pattern which relates one point to another, especially in the later part of

the sequence (Howlett, 2009).

• Process-Sequencing

Describes a situation whereby normal policy-making involves fairly common,

routine, non innovative changes at the margin of existing policies utilizing existing

policy processes, institutions, and regimes (Howlett, 2009).

The role of path dependency in agenda-setting research is highlighted by Baumgartner et al

(2006), who also claim that it should not be the only way to consider policy agendas, and

they also support strongly the application of comparative public policy.

An empirical example of the Punctuated Equilibrium Framework in the transport sector is

Perl and Dunn´s (2007) study on the auto fuel efficiency policy in the USA and Canada.

Regulation, taxation, market, voluntary agreements, incentives and negotiations are analyzed

in the context of the US Corporate Average Fuel Economy (CAFE) regulatory standard for

light-duty vehicles.

10.6. Institutional Rational Choice

The model of institutional rational choice is commonly used in order to explain public policy

processes and at the same time analyze the institutions that underlie these processes. Thus,

since I consider than conceptually it belongs to the institutional models that are presented in

the following paragraphs, the reader is prompted to paragraph 13.2.1, for a more detailed

analysis of the institutional rational choice framework of Elinor and Vincent Ostrom´s

Institutional Analysis and Development (IAD) Framework.

10.7. Policy Process Networks (PPN) framework

Parag (2006) proposed the Policy Process Networks (PPN) framework that is based on the

combination of systems thinking (especially the concepts of dynamic process and

interdependencies), Policy Cycle and Policy Networks perspectives. The benefits of this

combination lie on the combined neutralization of the individual drawbacks of each

perspective. More precisely, she argues that the policy process involves several different

networks - the Policy Process Networks (PPN), and that each stage of any policy process is

governed by a specific network – the Stage Network. “This network structure and

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characteristics are shaped by the institutions and the procedures that govern the stage and

by the interactions between actors who have interest in the specific stage and who have

access to relevant decision making for[a]” (Parag, 2006). The main steps of the framework are

the following and it was implemented in the context of Air Emissions policy formation in

Israel (Parag, 2006):

1. policy process is disaggregated to its sequence stages

2. for each policy stage the following actions are taken:

a. the essential resources are identified

b. the set of outcomes is detected

c. the network is identified and examined

d. the outcomes are explained by the unique stage’s network characteristics,

and

e. the network characteristics are viewed and explained in the context of the

other stages networks.

11. Policy implementation

After the analysis of public policy making in the preceding paragraphs, the question that

emerges is how to implement the decisions that have been made in the previous steps of the

process, or alternatively, what is the relationship between policy formation and

implementation? Indeed, many times, the success or not of a policy or a package of policies,

although carefully selected, are finally judged by their efficient implementation. Bardach

(2005) identified some of the possible adverse policy implementation outcomes, such as:

• Long delays.

• Capture of program or policy benefits by a relatively underserving and unintended

constituency.

• Excessive budgetary or administrative costs

• Scandal from fraud, waste and abuse that undermines political support and

embarrasses supporters.

• Administrative complexities that leave citizens (and program managers) uncertain as

to what benefits are available or what regulations must be complied with.

From a theoretical point of view, Hill and Hupe (2009) point out that the debate regarding

this relationship lies mainly between the top/down and bottom/up approaches (Table 14),

while mixed approaches have also emerged.

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Since the description of each of these models is out of the scope of this report, the reader is

prompted to the original references, as well as Hill and Hupe (2009). For illustration

purposes, in order to draw attention on the complexity of the policy implementation process,

I shortly present an overview of Van Meter and Van Horn´s (1975) model, who building up on

Pressman and Wildavsky´s work, proposed a top/down policy implementation model that is

structured upon six (clusters of) variables, as can be seen in Figure 10 (Hill and Hupe,

2009;2009). This model doesn´t include feedback relationships, since according to the

authors, in implementation studies “relationships identified at one point in time must not be

extended causally to other time periods” (Van Meter and Van Horn, 1975; cited by Hill and

Hupe, 2009). Thus, according to the model, the following variables should be taken into

account when it comes to top/down policy implementation studies (Hill and Hupe, 2009):

1. Policy standards (for performance assessment) and policy objectives

2. Available resources and incentives

3. Quality of inter-organizational relationships

4. (organizational and inter-organizational ) characteristics of the implementation

agencies

5. Economic, social and political environment

6. Disposition or response of implementers, described by their cognition

(comprehension, understanding), direction (acceptance, neutrality, rejection) and

intensity

Table 14: Top/down and bottom/up approaches in public policy implementation (based on Hill

and Hupe, 2009; tabulated by the author)

Key figures Main points

To

p/d

ow

n

Pressman and

Wildavsky

(1984)

• Concept of “Implementation deficit”, based on the degree of cooperation

among organizations that are interlinked in the process

• Mathematical representation of implementation (probability theory8)

• “rational model” approach (original edition)

• “learning, adaptation and exploration” approach (second edition)

Van Meter and

Van Horn

(1975)

• Amount of change required and level of consensus

• Six clusters of variables (Figure X) are dynamically linked so as to

produce an outcome (”performance”)

8 Bowen (1982) argues that the repeated character of interactions makes game theory a more suitable mathematical tool (Hill and Hupe, 2009)

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Key figures Main points

• Significance of participation at a prior policy-formation stage

Bardach (1977,

1998)

• Implementation needs to be perceived as involving “games”, in a political

process, where a full “follow-through” must be involved.

• Attention should be given to the “scenario writing” process and the

“fixing” of the game

Sabatier and

Mazmanian

(1979, 1980)

• Consistency among implementation actions and policy decision, impacts

and objectives)

• Principal factors affecting policy outputs and impacts (“tractability of

the problem”, “non-statutory variables” and “statutory structure

implementation”)

• Retrospective reformulation of policy based on experience

Hogwood and

Gunn (1984)

• Unattainability of “perfect implementation”

• Inherent limits to (top/down) control in complex systems

• A normative analytical model against which to measure reality

Bo

tto

m/u

p

Lipsky (1971,

1980)

• Street-level bureaucracy (front-line staff in policy delivery agencies)

• Control from the top to combat alleged failures of street-level staff

(accountability) involves intensification of the pressures upon them

(aleniation, uncertainty, inadequate time etc) and increases their

tendency to stereotype and disregard client needs

Hjern (1982)

• “Implementation structures” formed from “within pools of

organizations” and “formed through consensual self-selection” (Hjern

and Porter, 1981)

• Network analysis approach

Barrett and

Fudge (1981)

• Challenge hierarchical perspectives

• “negotiated order” (Anselm Strauss)

• Policy-action relationship

• Difficulty to separate implementation from policy formation because of

continuing political processes

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Figure 10: Van Meter and Van Horn´s model of policy implementation process (adapted from Hill and

Hupe, 2002)

Smith (1973) proposed a similar model for the context of the developing countries, arguing

that policy implementation can be seen as a tension generated between and within the

following components of the implementation process: idealized policy, implementing

organization, target group, and environmental factors, and concluded that policy makers

need to minimize disruptive tensions so as to ensure the success of the policy outcomes.

Figure 11 presents a graphical representation of his model and what should also be

highlighted, except for the relation between policy making and policy implementation, is the

role that institutions and feedback play in this system.

Figure 11: Smith model of policy implementation (adapted from Smith, 1973)

Finally, Charles (2005), in his study on the implementation of Regional Transport Strategy,

proposes a theoretical policy implementation framework, building up on the work of some

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prominent scholars, representatives of the top-down approach. His framework is structured

on nine elements: context, resourcing, theory, leadership, clarity, coordination, compliance,

support and monitoring (Table 15). Through the implementation of this framework to the

Brisbane regional traffic incident management program, the impact of the model´s elements

as success factors was verified.

Table 15: Theoretical Policy Implementation Framework (adapted from Charles, 2005; editing

modified by the author)

Context: external

circumstances

• Circumstances external to the implementing agency do not impose

crippling constraints (Hogwood and Gunn, 1984);

• Relative priority of objectives not undermined over time (Sabatier

and Mazmanian, 1979);

• Political stability (Ison and Rye, 2003)

Resourcing: time,

skills, funds

• Adequate time and sufficient resources are made available; &

required combination of resources is actually available (Hogwood

and Gunn, 1984);

• Leaders of implementing agencies possess significant managerial and

political skills (Sabatier and Mazmanian, 1979);

• Rationalise financing and investment streams: allocate funding in a

balanced way (ECMT, 2002);

• Program timing (Ison and Rye, 2003)

Theory: cause and

effect

• Policy based upon a valid theory of cause and effect; & Relationship

between cause and effect is direct (Hogwood and Gunn, 1984);

• Program based on sound theory (Sabatier and Mazmanian, 1979)

Leadership:

governance,

institutions

• Single implementing agency (Hogwood and Gunn, 1984);

• Provide a supportive legal and regulatory framework: ensure the

rules and regulations clearly specify roles (ECMT, 2002);

• Policy champion dedicated to the task of implementation (Ison and

Rye, 2003)

Clarity: clear policy

and strategy

• Complete understanding of, and agreement upon, the objectives to be

achieved, and that these conditions persist throughout the

implementation process; & tasks are fully specified in correct

sequence (Hogwood and Gunn, 1984);

• Policy contains unambiguous directives and structure the

implementation process to maximize success (Sabatier and

Mazmanian, 1979);

• Establish a supporting policy framework (ECMT, 2002)

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Coordination: good

communication and

coordination

• Perfect communication and co-ordination, between the various

elements or agencies involved (Hogwood and Gunn, 1984);

• Improve institutional coordination and cooperation: with

responsibilities commensurate with resources for implementation to

occur (ECMT, 2002);

• flexible and open attitude toward public reaction (Ison and Rye,

2003)

Compliance: require

and obtain

compliance

• Those in authority can demand and obtain perfect compliance

(Hogwood and Gunn, 1984)

Support: stakeholder

support

• Program is actively supported by constituency groups (Sabatier and

Mazmanian, 1979);

• Encourage effective participation, partnerships and communication

(ECMT, 2002);

• Public trust and support (Ison and Rye, 2003)

Monitoring: data

collection and

monitoring

• Improve data collection, monitoring and research: carry out

consistent monitoring (ECMT, 2002);

• Monitoring outcomes (Ison and Rye, 2003)

A number of studies have tried to investigate the parameters that influence and finally lead to

a successful policy implementation. There are two streams of literature in this topic, the one

that focuses on the ex-ante improvement of public policy implementation and at the other

extreme, the one that focuses on the ex-post evaluation and the feedback information that

improves implementation in a future stage. An inventory of the empirical studies on public

policy implementation is not possible, but the following paragraphs will provide the reader

with some literature examples that represent these two streams of policy implementation

literature.

Mehrizi et al (2009), applied stakeholder mapping (SM), a form of stakeholder analysis, to

the ex-ante evaluate of e-commerce policy in Iran. Their proposed framework is divided into

six steps (determination of policy goals, identification and description of stakeholders,

development of the Stakeholder–Goal matrix, vertical analysis, horizontal analysis, and

holistic analysis). Evaluating the strengths (systemic, multi-level and scalable tool;

integration of structural and behavioural approaches) and possible limitations (analytical

tool, insufficient attention to inter-institutional dynamics, policy goals as inputs etc), the

authors support the power of the framework towards consistency, completeness, fitness,

redundancy and possible deficiencies in policy implementation.

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The 5th Framework European Project under the title “Transport Institutions in the Policy

Process” (TIPP) examined three groups of implementation issues (insufficient acceptability,

inappropriate or non-optimal government structure, endemic industry characteristics) in the

context of 20 European case studies or all modes (Niskanen, 2005). They provide an

extensive number of conclusions and recommendations on the processes, structures, as well

as other issues such as information, public participation, conflict and advocacies,

highlighting the importance of these concepts in the effective implementation of the

established policy goals, in an ex-ante, as well as ex-post perspective.

Furthermore, a research study by Tuominen and Himanen (2007), regarding the interaction

between transport policy targets and policy implementation, in the context of Finnish

transport policy. Using target analysis methods and basing their analysis on the premises of

bounded rationality, they argue that the solution towards bringing transport policy targets

closer to policy implementation lies in the consideration of policy measures (in conjunction

with their acceptance) that meet the targets.

12. Information and evidence as determinants of Public policy

The role of information in public policy – and not exclusively – is stressed out by Hale (2011).

In her own words, “[…] integration between the [information] network and public

administrators extends deeply into the traditional understanding of the public policy

process; it implicates the network in many stages of the public policy process, from problem

definition to solution, through design, implementation, and evaluation”. Through her work

on the relationship between a national, nonprofit, information network, policy

implementation, and policy outcomes, she argues that the information brings a political

dimension to all stages of the public policy process. Her view of the role that national non-

profits play is summarized in a typology that is based on the particular initiatives for policy

change and distinguishes between champions, challengers, supporters, or bystanders (Figure

12).

Low

pre

fere

nce

to

hig

h p

refe

ren

ce Supporters Champions

Bystanders Challengers

Low engagement to high engagement

Figure 12: The Information Position Typology (adapted from Hale, 2011)

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Furthermore, as Nutley and Webb (2000) point out, “[t]he role of evaluation in the post-

decision phase provides an important source of evidence for subsequent rounds of policy

analysis”. Thus, information is not used as an input to the straightforward public policy

process, but it functions also as an input to the feedback process that corrects the process

regarding its path. The term evidence is used so as to highlight the elaborate character of the

information, i.e. the fact that it constitutes output of an analysis process. Thus, evidence-

based policy making goes most of the times hand in hand with research evidence. However,

the fact that evidence might exist, does not mean that it is properly utilized. In Nutley and

Webb´s (2000) words, “[a] problem arises when certain groups in society do not have

access to research evidence and, even if they did, their ability to use this evidence is

restricted due to their exclusion from the networks that shape policy decisions”. An overview

of evidence-based policy making in the context of road transport policy in the UK is

presented by Terry (2000) and the main points of his analysis are summarized in Table 16.

Table 16: Evidence-based policy making in the context of road transport policy in the UK (excerpt

from Terry (2000)

Transport (focus on roads policy)

Methodological

preferences and -

Multidisciplinary area. Policy related research is often rooted in

economic modeling and statistical forecasting methods.

Nature of the evidence

base

Tends to focus on technical and operational issues relating to the design

of the transport infrastructure.

Up until the late 1990s, largely reliant on internal government sources

only, chiefly the Transport Research Laboratory (TRL).

Dissemination strategies Initially centrally driven via the Department of Transportation (DoT).

Now more pluralist, for example,using professional networks.

Main initiatives for

ensuring that evidence

impacts on practice

Research results on operational issues passed to highway planners and

engineers in the form of guidance notes.

The implementation of research-based standards and codes of practice

are monitored and controlled.

Direction of diffusion of

EBP

Largely top-down diffusion of centrally determined practices.

Some horizontal diffusion of local innovations (such as city

pedestrianisation).

Role of central

government Very much hands-on and interventionist.

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13. Institutions and public policy

What is the influence of institutions on policymaking and vice versa? According to Weaver

and Rockman (1993) institutions matter and policy outcomes are determined by the

institutional constraints and decision-making attributes of political systems. Thus, the

different types of institutions involved in the policymaking process (political, social,

economic etc) and their interactions can be seen as the catalytic component for a successful

public policy, in terms of social welfare objectives, citizens’ needs identification and

implantation. Vigar (2002) provides a good overview of the relationship between institutions

and public policy, from a social institutionalism approach 9 , while Healey (1997)

distinguished two types of institutional infrastructure of policy making, i.e. hard and soft

institutional infrastructure (Table 17).

Table 17: The institutional infrastructure of policy making (Healey (1997), adapted from Vigar (2002))

Hard Infrastructure Formal organizational structures, departments, formal committees,

laws, taxes and subsidies

Soft infrastructure Social relations, informal networks, informal arenas, administrative

routines, professional cultures, social worlds

13.1. Some definitions

Institutions have been defined in various ways (Williamson, 2000) and an appropriate

definition of institutions is far from a settled issue (Kingston & Caballero, 2009). Indeed,

many scholars in the literature show different understanding of this concept, based primarily

on their beliefs and background in reference with the economic theory schools that they

follow. Aoki (2001) identified at least three different meanings that economists have attached

to the word ‘‘institution’, which he interprets into three conceptualizations, from a game-

theoretic point of view, i.e. analogizing economic process with a game. Thus, economists have

regarded an institution as comparable to either player of a game, the rules of a game, or

equilibrium strategies of the players in a game (Aoki, 2001). The most prevailing

9 Hall and Taylor (1996) identified three broad strands of new institutionalisms: historical, rational

choice and sociological institutionalism (from Vigar, 2002)

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conceptualization is the second one, with Douglas North as the most prominent

representative.

North (1990) defined institutions as “the rules of the game in a society, or, the humanly

devised constraints that shape human interaction. In consequence they structure incentives

in human exchange, whether political, social or economic”. He also argues that there is a

distinction between institutions, identified as rules of the game, and their players.

Furthermore, he defines these players as organizations, i.e. “groups of individuals bound by a

common purpose to achieve objectives”. The fact that this approach has been adopted by a

major part of the scholars might lie heavily on the fact that North´s perspective is considered

to bridge old and new institutionalism, or, according to Mantzavinos (2006), the

correspondent theory has greater empirical content. Nevertheless, North´s underlying

rationale and methodology, as well as his commitment to the neoclassical theory have

received some criticism (see Zouboulakis, 2004; Prasad and Tisdell, 2006).

Hurwicz (1994) focuses more on the enforcement aspect, expressing the rules of the game as

a triplet, which he calls ‘‘mechanism’’ or ‘‘game form”. Thus, specifications are required so as

to who plays the game, what actions players can choose (choice set) and what physical

outcome corresponds to each profile of the players’ choices (outcome function) (Aoki, 2001).

As far as the game equilibrium of institutions is concerned, Aoki (2001) identified two

streams of thought; one that lies on the development of the evolutionary and the repeated

game approaches, and another that relies on sophisticated concepts of equilibrium, such as

sub-game perfect equilibrium, in repeated prisoner’s dilemma games. Aligning more with the

game-theoretic perspective, along the economic, social, or political domains, he defines

institutions as “self-sustaining, salient patterns of social interactions, as represented by

meaningful rules that every agent knows and incorporated as agents’ shared beliefs about the

ways how the game is to be played” (Aoki, 2001).

In a similar context, Alexander (2007) defines institutional design as “the devising and

realization of rules, procedures, and organizational structures that will enable and constrain

behaviour and action so as to accord with held values, achieve desired objectives, accomplish

set purposes or execute given tasks”. By this definition, institutional design is pervasive at all

levels of social deliberation and action, including legislation, policymaking, planning and

program design and implementation (Alexander, 2007).

Many scholars provide classifications of the institutions based on various attributes, some

examples of which we provide herewith. North (1990) distinguishes between formal

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(sanctions, taboos, customs, traditions, and codes of conduct) and informal (constitutions,

laws, property rights) institutions and their enforcement aspect; Roland (2004) classifies

institutions as slowly and continuously (“slow-moving” – technology and culture, including

values, beliefs and social norms) or rapidly and irregularly (“fast-moving” – political

institutions) changing; Ostrom et al (1994) characterize institutions based on the aim of the

rules, classified as position, boundary, choice, aggregation, information, payoff and scope

rules;

Scott (2001) argues that regulative, normative and cultural/cognitive systems constitute vital

ingredients of institutions, denoting them as pillars. Thus, in this regulative-normative-

cultural/cognitive context, institutions: (i) constrain and regularize behaviour (rule-setting,

monitoring and sanctioning), (ii) develop normative rules that introduce a prescriptive,

evaluative, and obligatory dimension into social life (values and norms), also imposing

constraints on social behaviour and (iii) are primarily influenced by a socially mediate

construction of a common frame of meaning (ibid), respectively. He also considers that the

regulative and normative pillars can be mutually reinforcing (ibid).

Williamson (2000) provides a comprehensive contextual framework of institutional analysis,

presented in Figure 13. He also follows Douglas North and New Institutional Economics in

distinguishing between institutional environment (political, social, and legal ground rules of

the game and institutional arrangements (governance) (Williamson, 2000).

Although he tackles the issue from a broader perspective than usual transport-related

analyses, we consider it constitutes an appropriate approach as a starting point towards

analyzing the institutional setting of urban public transport. Furthermore, the hierarchy and

feedback elements of the system are also important since higher levels impose constrains on

lower levels and lower levels ‘‘feedback’’ to higher levels to provide adaptation to (Stone,

2008). Under this approach, we position the elements of funding and financing primarily in

the rules of the game, governance and resource allocation levels. In relation to transportation,

a great part of transportation-related authors refer primarily to the formal actors that

influence the “game” and corresponds to the governance level (L3) of Williams´ framework,

while the formal rules of the game (L2) are usually referred to as legal and/or regulatory

environment that complements the institutional arrangement it formulates and supports.

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Figure 13: Economics of Institutions (based on Williamson, 1996)

Decision-making plays also a vital role in institutional arrangements, whilst the structure of

the decision-making process (centralization, state intervention) is a strategic characteristic

which can influence and, to a certain extent, impose the features of the decision making

process (i.e., interest group influence, conflict resolution, knowledge and information

availability etc) (Zografos et al, 2004).

Aoki (2001) developed a comparative institutional analysis framework, arguing that the

nature of institutional dependencies is captured in explicitly evolutionary game-theoretic

ways, individual agents are not only constrained but also informed by institutions, and

institutional evolution may be characterized by path-dependence and novelty, as well as by

critical junctures and evolutionary selection (equilibrium). His analysis is based on a

definition of institutions that was presented earlier in this paper, and which was developed

along five building blocks: (i) endogenicity, (ii) information compression, (iii) robustness

with respect to continual environmental change and minor deviance, (iv) universality of

relevance and (v) multiplicity. From an organizational architecture perspective he identified

three generic modes of information connectedness among task units in an organization, i.e.

hierarchical decomposition, information assimilation and information encapsulation, on the

basis of complimentary or competitive tasks, as well as systemic and idiosyncratic segments

of the environment.

Lane and Ersson (2000) also sustain a game theoretic approach, arguing that the distinction

between institutions, on the one hand, and interests or preferences, on the other, are nested

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within a basic principal-agent interaction, where political leaders act as agents of their

principal, the population, with institutions regulating this interaction.

Institutional stability is also an important parameter in the framework of institutional

analysis. Furubotn and Richter (2000) state that an institutional equilibrium, if any, that

would represent a complete institutional arrangement, would mean that an original set of

formal rules remains in active use despite the fact that a supplementary set of informal rules

and enforcement characteristics has emerged to complete the total structure. They also

identify two states of institutional equilibrium; (i) when new informal rules evolve to reach a

stable endpoint without destroying the original formal framework and (ii) after a

disturbance of an initial institutional equilibrium a new equilibrium will be reached (ibid).

Furubotn and Richter (2000) also argue that the general perception on institutional change

is that it results from the institutional instability derived by bad institutional design, but in

reality this instability might emerge as a consequence of economic growth/decline, or even

technical, intellectual and cultural shifts (ibid). North (1993) identified five propositions on

institutional change:

• The continuous interaction between institutions and organizations in the economic

setting of scarcity, and hence competition, is the key to institutional change.

• Competition forces organizations to continually invest in skills and knowledge to

survive. The kinds of skills and knowledge individuals and their organizations

acquire will shape evolving perceptions about opportunities and hence choices that

will incrementally alter institutions.

• The institutional framework provides the incentives that dictate the kinds of skills

and knowledge perceived to have the maximum payoff.

• Perceptions are derived from the mental constructs of the players.

• The economies of scope, complementarities, and network externalities of an

institutional matrix make institutional change overwhelmingly incremental and path

dependent.

13.2. Institutional analysis frameworks

This paragraph provides the reader with a brief overview of the institutional analysis

frameworks that exist in the literature and are considered to be relevant to the topic under

study and the research questions in particular. In the end of this paragraph a table can be

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found that summarizes and attempts to compare the basic elements of each institutional

framework. At this point it has to be noted that there is no complete match between the

steps or stages, and these frameworks can function complementary one with the other in a

sense that there are some conceptual and procedural overlaps, but there are also elements

that each framework can contribute to the holistic perspective of this work.

13.2.1. Institutional Analysis and Development (IAD) framework

The Institutional Analysis and Development (IAD) framework was developed by Elinor

Ostrom and her colleagues in the Workshop in Political Theory and Policy Analysis at Indiana

University, in order to analyze common-pool resources and the known tragedy of the

commons. Before describing the framework per se it is worth mentioning some important

topics that delineate the way of thought and the underlying premises of the framework,

derived from various sources of Ostrom´s work throughout the years.

As Ostrom (2007) points out, there are certain challenges that the institutional analysis has to

face, when dealing with institutions and they are summarized herewith:

1. multiple definitions of the term of institutions in the literature,

2. invisibility of institutions, creating difficulties in their identification and measurement;

differentiation between rules-in-use (informal) and rules-in-form (formal).

3. Multiple disciplines an multiple languages,

4. Multiple levels of analysis (diverse analytical levels, diverse geographic domains, nested

structure of rules within rules, and constitutional, collective choice & operational

decisions)

5. Configural relationships; unlike other disciplines, institutional analysis cannot be based

just on the ceteris paribus principle, but a value of other variables is required, although the

relationship among element is not additive.

As mentioned before, there is a definitional ambiguity regarding the concept of institutions.

The definition of institutions adopted in Ostrom´s work and consequently to the IAD

framework that is described here, sees institutions as the “shared concepts used by humans in

repetitive situations, organized by rules, norms and strategies” (Crawford and Ostrom, 2005,

cited by Ostrom, 2007). There is one more conceptual distinction that is presented in the

outset by Ostrom (2007); that is the difference between frameworks, theories and models and

pinpoints the pitfalls that can arise from the misuse of the terms.

The Institutional Analysis and Development (IAD) framework is a multitier conceptual map

(Ostrom, 2007) that aims at the identification of the structural variables of the institutional

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arrangements (Figure 14). The description provided herewith lies heavily on the description

provided in Ostrom et al (1994), Ostrom (2005) and Ostrom (2007). The analysis starts with

the identification of a number of external variables, clustered into three categories:

1. Physical/material or biophysical conditions

2. Attributes of the community or culture

3. Rules in use (or working rules that might be different from the rules-in-form)

Figure 14: Institutional Analysis and Development Framework (adapted from Ostrom, 2005)

These variables are directly related to a conceptual unit called action arena, which consists of

the action situation and the actors in that situation (Figure 15). The action situation can be

further disaggregated into seven cluster variables:

1. Participants

2. Positions

3. Outcomes

4. Action-outcome linkages (or allowable actions)

5. Control the participants exercise

6. Information

7. Costs and benefits assigned to outcomes

The concept of (individual or corporate) actor presupposes the following assumptions:

1. The resources brought to an action situation by the actor

2. The valuation that actors assign to states of the world and to actions

3. The way actors acquire, process, retain and use knowledge contingencies and

information

4. The process actors use for selection of particular courses.

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Or in other words, preferences, perceptions, beliefs and decision rules of the actors, as

explained in the individual choice theory under the premises of bounded rationality.

The outcomes that are predicted within an action arena should be evaluated in light of a

number of different alternative institutional arrangements, while these evaluative criteria

should be applied to both the outcomes and the processes that lead to these outcomes. The

IAD framework focuses on the following six evaluative criteria, without excluding the use of

other relevant criteria:

1. Economic efficiency

2. Equity through fiscal equivalence

3. Redistributional equity

4. Accountability

5. Conformance to general morality

6. Adaptability

Figure 15: The internal structure of an Action Situation (adapted from Ostrom, 2005)

Focusing now on the rules, two issues need to be identified; the configurations of the rules and

the way these working rules affect the action situation variables. To answer the first issue, IAD

identifies seven types of working rules and it argues that “the cumulative effect of these seven

types of rules affects the seven elements of the action situation” (Ostrom, 2007):

1. entry and exit rules

2. Position rules

3. Scope rules

4. Authority rules

5. Aggregation rules

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6. Information rules

7. Payoff rules

13.2.2. Institutional decomposition and analysis (IDA) framework

The Institutional decomposition and analysis (IDA) framework was developed by R. Maria

Saleth and Ariel Dinar R. Maria Saleth to tackle the institutional economics of water

management through the work performed in the World Bank. The framework aims at

establishing the linkage between water institutions and performance.

Saleth and Dinar´s (2004) work is based on Ostrom´s IAD framework and New Institutional

Economics Theory. They adopt the common institutional perspective (Figure 16) and identify

the following features of institutions: subjective construction, path dependency, stability &

durability, hierarchic nature & nestedness, embeddedness and complementarity. Regarding

the last issue, they argue that “‘Institutional thickening’ in terms of increasing interlinkages

and complementarity among institutions determines their ultimate performance efficacy”.

Figure 16: Economics of institutions (adapted from Saleth and Dinar, 2004)

Furthermore, according to their view, the body of literature so far on institutional economics

neglected some important issues, such as reckon of the role of perception, underestimation of

the role of individuals, absence of an ex-ante approach, inadequate treatment of institutional

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linkages, need for institutional decomposition, and ignored supply side of institutional

change.

Figure 17: Subjective theory of institutional change (adapted from Saleth and Dinar, 2004)

Thus, using the decomposition approach, the analytical decomposition of water

institution is performed at two levels; firstly, the water institution is decomposed in terms of

its three broad institutional components (water law, water policy, and water administration

or organization) and secondly, these institutional components is decomposed further to

identify its constituent institutional aspects.

Furthermore, Institutional Performance is also decomposed into a set of performance aspects

that capture the overall effectiveness or performance not only of each of the three

institutional components but also of the water institution taken as a whole:. They are:

1. Overall effectiveness of water law

2. Overall effectiveness of water policy

3. Overall effectiveness of water administration

4. Overall effectiveness of the water institution,

which are further decomposed to their physical, financial, economic, and equity dimensions.

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Figure 18: Institutional linkages within a water institution (adapted from Saleth and Dinar, 2004)

In light of this framework, Saleth and Dinar (2004) developed a number of empirical models,

derived from a cross-country analysis of a number of water institutional and gerenal

environment variables. Because of the informative character of this document, the reader is

promted to the Saleth and Dinar´s work for more information on the structure of the

equations and the detailed description of the variables. In a nutshell, the variables used were

clustered in the following categories:

• Water law (L variables),

• Water policy (P variables),

• Water administration (A variables)

• Performance (W variables)

• exogenous variables

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13.2.3. Procedure for Institutional Compatibility Assessment (PICA)

The Procedure for Institutional Compatibility Assessment (PICA) was developed in the

framework of the EU SEAMLESS10 project, in the context of agri-environmental policies. It is

a standardized procedure for ex-ante modelling institutional aspects for policy

implementation, and as being an explorative tool, it enables policy-makers to identify, at an

early stage, potential institutional incompatibilities (Theesfeld et al., 2010a). In a nutshell, the

procedure provides indications on whether or not a new policy will be able to effectively

change the existing institutional arrangements (or establish new ones) that guide actors’

behaviour in such a way that the policy objectives can be reached (ibid).

Analyzing the approaches and tools for policy assessment, the gap of which PICA is trying to

fulfill, Theesfeld et al. (2010a) identified three main approaches in the literature:

1. approaches which do not explicitly consider institutional aspects at all, such as e.g.

Cost of Policy Inaction (COPI) method, Cost–Benefit Analysis (CBA) and other

supporting valuation methods for monetization of goods without market value.

2. approaches that consider institutional aspects, including multi-criteria analysis

3. experimental approaches, which are more comprehensive and much more flexible in

their choice of variables, yet do not entail a systematic search process for discovering

relevant institutional aspects.

The cornerstone of PICA is the concept of institutional compatibility, thus in this context

Theesfeld et al. (2010a) identified the following four broad categories of determinants for

institutional policy options’ (in)compatibilities:

1. Incentives, shaped by the formal and informal rules, can be affected by the existence of

countervailing rules or policies (designed at other administrative levels) that provide

incentives detrimental to the objectives of the newly introduced policy.

2. Suitable governance structures intended to monitor and coordinate the implementation

of a new policy, may not have the necessary capacities or the appropriate design to

reduce information asymmetries sufficiently, or may even be absent.

3. Institutional incompatibilities may occur if the design of the institutional

arrangements implemented with the new policy does not correspond with actors’

characteristics.

10 SEAMLESS stands for “System for Environmental and Agricultural Modelling; Linking European Science and Society”, the project was funded by the EU Framework Programme 6 (Global Change and Ecosystems) and it ran from 2005 till March 2009 (www.seamless-ip.org).

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4. The performance of institutional arrangements induced by the new policy is closely

related with the characteristics of the transactions targeted by this policy, which in

Williamson´s (1985) terms are characterized by asset specificity, uncertainty, and

frequency.

Figure 19: Scheme of the procedure for institutional compatibility assessment (adapted from Theesfeld

et al., 2010a)

Figure 20: Three dimensions of a policy type (adapted from Theesfeld et al., 2010a;2010b)

PICA comprises of the following four steps (see Figure 19) (Theesfeld et al., 2010a; 2010b):

Step 1: Classification of policy options

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The policy options are clustered to identify the generic structure of a policy option. They are

classified according to the type and area of intervention, the possibly induced property rights

changes and the attributes of the natural resource(s) addressed (Hagedorn et al. 2002;

Theesfeld et al., 2010b). Then, this formalized structure is used in the next step so as to

identify the relevant crucial institutional aspects (CIA). A policy type matrix is constructed,

where the policy instruments under study are allocated in one of three categories of

interventions (regulatory, economic and advisory/voluntary 11 ), and the three areas of

intervention, or governance structures (hierarchy, market and hybrid/self-organized

network12) a policy is supposed to have an impact on (see also Figure 13).

Step 2: Crucial institutional aspects (CIA)

Each policy type is characterized by a specific set of crucial institutional aspects (CIA).There

is an initial library of 42 CIA linked to respective policy types in agriculture, environment,

and rural development. These indicators, as well as the assumed relationships are derived

from a broad range of theoretical literature and empirical studies of institutional economics,

social theories as well as (particularly ex-post) policy assessment literature and studies.

Indicatively, two examples of crucial institutional aspects are the “Bargaining power of

farmers’ associations” and the “Information asymmetry between state and firms”.

Step 3: Indicators

Indicators help to evaluate the potential of respective CIA to constrain or foster the

implementation of a policy option. Currently, there is a library of about 100 indicators, i.e.

variables and proxies that are used as input to the institutional assessment within PICA. The

linkages between a CIA and the respective suggested sets of indicators are derived again from

the theoretical literature and empirical studies of institutional economics, social theories as

well as (particularly ex-post) policy assessment literature and studies.

Step 4: Aggregating information on institutional compatibility

The information provided by the indicators is used for a qualitative assessment of each

identified CIA and is further aggregated. This leads further to qualitative statements about

the probable effectiveness or not of a policy option and the institutional fit or lack thereof

between policy options and institutional contexts. This step combines many methodologies,

such as expert judgment, quantitative & qualitative analysis, benchmarking, focus groups

and other participatory methods etc. More precisely, the PICA expert team, based on the

11 Taxonomy is based on Stone (2002) 12

Taxonomy is based on Williamson (1995)

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information acquired in the previous steps, assesses qualitatively the institutional

compatibility between the policy option under scrutiny and the regional institutional

context. This is achieved by compiling the various indicator values, for each CIA, and

assessing them in relation to a reference value derived from comparing the indicator values

between the region under scrutiny, higher geographical scales or other regions at the same

geographical scale. Then, a qualitative statement on the extent of each CIA is derived by the

assessment of all indicator values related to this particular CIA. After that, a number of

thematic categories of institutional compatibility are defined by the PICA team members,

resulting in the grouping of at least one CIA and the respective qualitative statements, while

focus groups and/or scientific experts’ judgment may be used to assess the relative

importance of CIAs and thematic categories.

Since PICA was developed recently, there are some difficulties in the validation of the

process, while there are also limited applications so far. According to Theesfeld et al. (2010a),

another limitation is that the process doesn´t provide detailed insights into the concrete

causalities that lead to the institutional incompatibilities pointed out. Examples of the

implementation of PICA concern the assessment of trade liberalization of the agricultural

market and implementation of the EU Nitrate Directive (Council Directive 91/676/EEC) in

Auvergne, France (Amblarda and Mannb, 2011).

13.2.4. Social Fabric Matrix Approach

The Social Fabric Matrix Approach (SFM-A) (or influence map or matrix (Hayden, 1982)) is

a rigorous and comprehensive methodology for undertaking policy-relevant, research on

complex real-world problems, developed by F.G. Hayden (2006) (Fullwiler et al., 2009).

More precisely, the SFM is “an integrated process matrix, designed to express the

attributes and relationships of the parts, as well as the integrated process of the whole, in

order to define and appraise the real-world social, technological, and ecological system

context that contains the problem of interest” (Hayden, 2006).

According to Hayden (2006), “social beliefs are not vague abstractions, rather criteria

embedded in rules, regulations and requirements as expressed and enforced in contractual

obligations”. From an institutionalist perspective, this framework satisfies the following

three sets of concerns (Hayden, 2006):

1. the first set includes:

a. philosophical,

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b. theoretical,

c. statistical & mathematical techniques, as well as

d. policy concerns;

2. the second set includes concerns about

a. criteria,

b. transactions and

c. (evolutionary) transformations, expressed through social institutions;

3. the third set includes

a. cultural values,

b. social beliefs,

c. personal attitudes,

d. social institutions and

e. the ecological system.

The starting point for the development of the framework is Hayden´s (2006) argument that

there is a problem with utility maximization model of analysis for a number of reasons, which

he explains in his book. Among them, are the inexistence of utility in the real world, and the

fact that it represents action and bargaining among atomistic individuals in the marketplace

through fixed processes, while in policy analysis, interest should be shifted towards reaching

a reasonable consensus among overlapping institutional organizations and changes in the

procedures so as to reach the desirable outcomes. In his own words, “Ideas like utility

maximization ignore culture, social beliefs, institutions, power relations, traditions,

procedures, and so forth, and, therefore, are not useful with regard to real-world policy

analysis and decision making”.

In this framework, the process of policy analysis, as envisaged by Hayden is represented

schematically in Figure 21. Furthermore, SFM-A considers all components of a socioeconomic

system and their corresponding relationships, taking account the fact that all these

components need to be integrated in order to understand a problem, in a particular context,

and plan the policy that will solve this problem (Hayden, 2006). This is depicted in Figure

22, where the integrated perspective of the system is presented, along with the deliveries and

flows among components. The most prominent elements are the three normative sets of

criteria for the judgment of social institutions, that is social belief criteria (NB), technological

criteria (NT), and ecological system criteria (NE), which are expressed through institutional

structures and patterns, are necessary for a social system to establish efficiency and may

exhibit conflicts among various criteria (Hayden, 2006).

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Figure 21: Policy Analysis (adapted from Hayden, 2006)

Figure 22: Policy Analysis Paradigm with Primary Criteria (adapted from Hayden, 2006)

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Figure 23: Integrated system (adapted from Hayden, 2006)

Figure 24: Six Integrated Social Policy Areas (adapted from Hayden, 2006)

Other important issues, pointed out by Hayden (2006) is that the policy criteria for

evaluating one policy need to be consistent with the beliefs, policy criteria, and evaluation in

all the other societal areas while problem solving usually requires changes in institutions,

beliefs, and technology, aka in the context. To illustrate this, he provides a thorough

description and explanation of the framework and its implementation in 6 Policy areas

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(Figure 23), aiming at the design of policies and programs that more efficiently and effectively

solve problems, in light of the conceptual triad of context, criteria, and consequences13.

The basic premises of the framework are consistent with general systems analysis (GSA), and

more precisely the following twelve principles:

1. System definition (Objects, Attributes, relationships)

2. Openness (Non-equilibrium, State and environment)

3. Nonisomorphism

4. Equifinality

5. System Components (cultural values, social beliefs, personal attitudes, technology,

social institutions, and the natural environment)

6. Control and Regulation (through relationship and requirement linkages or system

control)

7. Hierarchy

8. Flows, Deliveries, and Sequences (or flows of sequenced deliveries)

9. Negative and Positive Feedback

10. Differentiation and Elaboration (evolution and higher complexity)

11. Real Time (timeliness and sequential events)

12. Evaluation

As far as the SFM-A is concerned, Social Fabric Matrix comprises of the following six (6)

components: cultural values, societal beliefs, personal attitudes, social institutions,

technology, and the natural environment. These components are integrated through the flow

levels and delivery among the component parts, creating an integrated process matrix,

designed to express the attributes of the parts as well as the integrated process of the whole,

as presented in Figure 18 (Hayden, 2006). Furthermore, after the identification of deliveries

in the cells, the matrix can be used to define the system sequence through a Boolean digraph

(closed or unidirectional) (Figure 25). Thus, generally speaking, SMF “provides a means to

describe the general context, to define connections among components in the context and to

convert cellular information to mathematical expression, where appropriate” (Hayden,

2006).

13 “The policy tool kit must be able to (1) define the context that is producing the problem and the context that will exist after policies and programs are implemented to solve the problem, (2) apply criteria in order to judge which programs will achieve the desired ends, and (3) judge program efficiency by the consequences resulting from the policy actions” (Hayden, 2006).

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NOTE: rows identified by i represent the components which are delivering, and the columns identified by represent the

components which are receiving.

Figure 25: Noncommon-Denominator Process Matrix (adapted from Hayden, 2006)

NOTE: Each node in the digraph represents a row and column entry in the matrix and each edge represents a cell delivery.

Figure 26: Simple Social Fabric Matrix Digraph (Hayden, 2006)

A summary of SFM´s characteristics are presented herewith (Hayden, 2006):

1. The matrix is based on the concept of delivery and process

2. The components listed on the left are delivering to those listed across the top.

3. It is a noncommon-denominator matrix without common flow properties and all the

information in the rows and columns are not summative

4. The empirical observations contained in the cells of the matrix are the flows of the

system (direct deliveries)

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5. The number and kinds of component entries in the rows and columns of the

matrix will depend on the problem being studied and the policy analysts'

interests.

6. The SFM approach defines the system as it exists

7. The matrix allows for model building and data collection consistent with theory

Herewith I present a number of applications of the SFM-A in various contexts, but the

sample is indicative and non-exhaustive.

Hayden (2006) in his book provides four examples of studies, using SFM. The first study is

related to the contracts and costs in a corporate/government system network (waste disposal

system) (Hayden and Bolduc, 2000). Through the analysis of the contracts per se, the

construction of SFMs and the application of a system dynamics tool, they concluded that

under the current contractual arrangement, there are excessive cost overruns, due to cost-

plus contract adders, which in turn indicates that for the 30-year analysis undertaken, the

policy alternative of building a new waste facility under these terms, is not viable.

The second study aims at the analysis of the daily Federal Fund´s Market, a crucial element

for the Federal Reserve Policy by using the SFM-A in a macroeconomic setting (Fullwiler,

2001; Hayden, 2006). Utilizing system dynamics and developing an extensive SFM and

model, he reached certain conclusions regarding the reserve balances.

The third study concerns a Socioeconomic Analysis of Rural Poverty and Livelihood

Strategies in the Indian Village of Theethandapattu, aiming at the identification and

understanding of the causal relationships among economic, social, cultural, and ecological

factors that cause and intensify poverty. Many insightful conclusions were drawn about

agriculture policy in rural India and the reader is prompted to the detailed study for more

information.

The fourth study relates to the assessment of Institutional Performance for Surface Water

Management of the Platte River in Nebraska and aims at showing how changes in rules and

regulations affect the extensive and complex policy network in water allocation systems

(Yang, 1996; Hayden, 2006). Briefly, this study investigates the structure, function and

performance of the surface water systems, from the instrumental efficiency of the

institutional authority and competing interests perspectives. By using SFM-A, digraphs and

Boolean algebra techniques, the system is analyzed and assessed in terms of the consequences

produced.

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Gill (1996) used an integrated SFM/system dynamics approach to policy analysis, in the

Australian honeybee pollination market context. The analysis is based on five general

influence groupings: institutions, technology, environment, beliefs and attitudes, and values,

and by representing the various uni- or bidirectional deliveries among these components, the

SFM and the corresponding digraph can be constructed. However, as Gill (1996) argues this

form of representation corresponds to qualitative system dynamics, so he proceeded one step

further, and created a quantitative systems dynamic model through which he tested various

policy options. More detailed information about the model can be found in Gill (1993).

13.2.5. Institutional and organizational development process (IO/DP)

The Department for International Development published on March 2003 the Institutional

and organizational development process sourcebook of tools and techniques, aiming at

assisting institutional developers. This framework is based on a cyclic process which begins

with the analysis and diagnosis of the institutional framework and the organizational

framework embedded in this institutional setting, moving on to the design process, the

implementation of the design and finally, the monitoring and evaluation phases of the

process. Various tools and techniques can assist towards the achievement of the tasks of the

process, and the authors are presenting some of them.

Figure 27: DFID’s Institutional Development Process Framework (based on DFID (2003) and modified by the

author)

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14. Discussion and conclusions

The complexity of the policy making process can be partly attributed to the numerous actors

and their attributes (objectives, interests and influence power) and partly to the environment

that they act and interact within, approximated by the institutional, organizational, cultural

and socioeconomic parameters that define this environment. Public policy addresses a great

variety of policy areas, thus what is next to be investigated, based on the theoretical

endowment of the various disciplines that were outlined here, is the way these issues play

out in the context of transportation policy, how policy is defined, its evolution throughout

the decision-making process and its final outcomes and impacts compared to a certain

performance concept that will indicate success of the policy per se and of process. Finally, the

various types of barriers and constraints, with emphasis on the decentralization of policy-

making, the role of policy networks with emphasis on participatory and collaborative and

evidence-based policy-making, are considered quintessential for analyzing the complexity of

policy-making and its success.

The policy models that have been presented in the previous paragraphs are characterized by

richness of approaches and assumptions, exhibiting sometimes similarities in basic

theoretical concepts, and sometimes differences, since they refer to different parts or stages of

the decision making process, whether formulation or implementation. Thus, the researcher´s

task is firstly to acquire an overview of the theoretical base in public policy, which is the

main objective of this document, and then select and adjust accordingly the methods, tools

and frameworks that fit better the specific research problem, or context of the public policy

problem or situation she wishes to analyze. The unit of analysis, the perspectives and

approaches adopted, the specific focus and the underlying assumptions are drivers for the

selection of the respective theoretical explanation. The indicative examples, wherever

possible, is a helpful link between public policy theory in general, public policy in

transportation and real world transportation problems that were analyzed throughout the

years. However, there is a gap between the theory formulation and the theory

implementation, as was made evident by our literature scan, thus there is a need to promote

empirical analysis.

The task of comparing these frameworks in confronted with the following issues. Which part

of the public policy making and implementation process do these frameworks refer to and

what are they trying to explain? What are the underlying assumptions for each model and

how do they function compared with each other? Are they alternatives for the study of the

same issue, adopting different approaches and perspectives or are they complementary in the

sense that combined they provide a powerful tool for achieving a holistic approach towards

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public policy analysis? Table 18 provides a macroscopic comparison of the frameworks,

which means for detailed criticism and epistemological-level remarks the reader is prompted

to the references and to the literature in general. In general, the Stages or Policy Cycles model

has been the prevailing model for public policy making research in the past years, although it

has been severely criticized for its linearity and ideal representation of the process

sequencing that in some cases is far away from the real system. All frameworks assume the

rationality of the individuals involved in the process, which, in light of information

asymmetries, is bounded and so are the choices that the individual is making in this context.

However, the stages model is more process-oriented than behavior-oriented. Thus, in general

terms, the Policy cycle model constitutes the starting point, and then depending on the

unit and level of analysis, as well as how policy change is initiated, the appropriate

framework is to be chosen. Another interesting fact is that sometimes different frameworks

provide different analysis outputs for the same case study, which is one of the benefits of

multi-lenses approach. Indeed, since policy issues are not clear cut and the influencing

factors are many, this practice is encouraged, at least for the cases that it makes sense.

Another conclusion is that the lack of empirical evidence on the implementation of the

various frameworks in real case studies, does not allow for the identification of the whole

spectrum of weaknesses and strengths. This is of particular importance, if we consider the

fact that some of these public policy making frameworks were revised and improved in light

of such empirical studies. For instance, the Advocacy Coalition Framework was revised so as

to incorporate the fruitful criticism of the scholar community, as well as to enhance its

applicability and entail the particularities of non-US policy making processes.

Similarly, as far as policy implementation is concerned, the theoretical implementation

models are either strategic or completely operational, with the tactical or planning level,

either overlooked or undertreated. Thus, the role of the planning processes and their

outputs, such as official planning documents, that are “fed” from the strategic or higher

level processes and then “feed” the operationalization of the planned policy objectives,

needs to be taken into account. Furthermore, the different particularities of implementing

policies in different administrative and spatial scales are another issue that needs to be taken

into account.

Finally, research in public policy will continue in quest of the identification of the causal

mechanisms driving policy change, and in a dynamic and evolutionary path, taking into

account actors, actions, structures, networks, behaviors, preferences and relationships, to

ensure efficient and effective policy making and implementation.

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The previous section of this report provided the reader with the basic theoretical and

empirical concepts that are related to many institutional and public policy making and

implementation issues. Thus, at this point, the implications of the public policy theory and

practice in the Bus Rapid Transit (BRT) context should be considered. BRT as a transport

system is characterized by a complex public policy process, since the nature of the

infrastructure and the services offered involve a great number of stakeholders and policy

areas (or arenas, or subunits). In generic terms, transport policy, needs to be aligned with

land use and urban development policies, as well as budgetary, labor and other policies. Thus,

the need for an integrated policy approach (in the form of policy measures, whose

implementation satisfies the public policy goals and objectives) is beyond any doubt.

Furthermore, the plurality of interests - most of the time conflicting ones - increase the

complexity of the process and require for careful and subtle choices in the policy measures

that will be adopted, whether considered from an acceptability or implementation

effectiveness perspective. Since each BRT system represents different socio-economic and

political context and, considering the implementation of the system as an act of policy

change, the frameworks that were presented earlier, provide useful analysis guidelines. For

instance, in cases of the existence of coalitions with high lobbying influence and political

entrepreneurs then the ACF should be preferred against Punctuated Equilibrium model,

where the policy monopoly is what characterizes the political monopoly.

As a final concluding remark, it should be noted that the tools that public policy literature

provides us should be used in an optimal and complementary way, so as to minimize the

individual limitations and weaknesses of the analysis frameworks and highlight the

particularities and synergies of the policy areas that need to be addressed. BRT systems are a

very good example of various socio-economic and political fermentations and stable,

dynamic, as well as turbulent environment, which demand careful analysis, design and

strategies and implementation actions, so as to achieve a sustainable and highly performing

BRT system, with all the beneficial implications to the user, the economy and the society as a

whole.

Table 18: Macroscopic comparison of Public Policy frameworks

Policy

stage

Focus Behavioral

assumptions

Change Weaknesses

Institutional

Rational

Choice

model

Decision

making

Institutions

Individuals

Bounded

rationality

(Expected)

utility

Incentives Rational choice does not guarantee

efficiency and might lead to

suboptimality (Miller, 2000)

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Policy

stage

Focus Behavioral

assumptions

Change Weaknesses

maximization

Stages of

Policy cycle

model

All

stages

Process More process-

oriented

Bounded

rationality

Feedback Linearity

Static, incorporation of feedback

increases dynamics

Incremental

ism or

muddling

through

Decision

making

Path

dependency

Organized

anarchy

Bounded

rationality

Satisficing

Small

increments

Short run, limited variations

(Etzioni, 1967),

Encouragement of inertia and

continuation of status quo (Dror,

1954),

May overlook the role of elites,

systematic stages in the process,

and possibility of innovative policy

changes (House, 1987)

Multiple

streams

model

Agenda

setting

Problem

Policy

Politics

Policy

window

Circumstantial (Howlett and

Ramesh, 1995; in Ridde, 2009)

etc

Advocacy

Coalition

Framework

Policy

subsystems

Advocacy

coalitions

Policy

brokers

Policy

Learning

Common or

competing

beliefs/values

Bounded

rationality

Dynamic

Policy

networks

External

events

Internal

events

Potential bias toward pluralistic

political

Systems (Weible et al, 2008)

etc

Punctuated

Equilibrium

Framework

Agenda

setting

Policy

monopoly

Policy image

Institutional

policy

venues

Bounded

rationality

Dynamic

Path

dependent

or process

sequencing

Sometimes difficult to

operationalize (Robinson, 2006)

Policy

Process

Networks

(PPN)

framework

Policy Cycle

and Policy

Networks

Bounded

rationality

Stage

networks

n/a

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