An Introduction to Urban Governance
The introduction is intended as an introductory statement of urban governance. It
addresses the theoretical and methodological foundations for urban governance as
well as applications of these foundations to solving real world urban governance
problems. The introduction is therefore divided into three parts: Theories,
Methodologies, and Applications. In the Theories part, we explain the theoretical
foundation for urban governance. In particular, we depict how cities work in terms
of the complexity and economic approaches to urban development, and how we can
management cities through plans, governance, regulations, and administration. In
the Methodologies part, we first introduce the complexity approach to explaining
how cities work and based on this introduction, we then introduce analytical
methods that can help city managers to cope with various urban problems, including
decision analysis, policy analysis, and planning analysis. We consider city modeling
as an effective way of not only understanding and gaining insights into the urban
development process, but also providing a powerful tool to analyze how urban
phenomena emerge. In addition, based on such understanding, a general
discussion of planning support systems is provided as a basis for further developing
possible technologies for city managers to cope with various urban problems. With
the theoretical and methodological foundations introduced in Parts 1 and 2, in Part 3,
Applications, we demonstrate how the ideas derived from these foundations can be
used to deal with urban issues, spatial or non-spatial. These issues are selected so
that they cover the most important application areas related to urban socio-spatial
processes. Together they provide a coherent set of concrete examples of how cities
should be planned, governed, regulated, and administrated.
Table of Contents
Part 1:
1
2
3
4
5
6
7
Theories
Urbanization and Urban governance
Scope of Urban governance and Related Fields
How Cities Work: Property Rights and Complexity
Planning Cities
Governing Cities
Regulating Cities
Administrating Cities
Part 2: Methodologies
8
9
10
11
12
13
Cities and Complexity
Decision Analysis
Policy Analysis
Planning Analysis
City Modeling and Analysis
Planning Support Systems
Part 3:
Applications
14
15
16
17
18
19
20
Transportation
Land Use
Sanitary and Infrastructure
Building and Constructing
City Design and Landscape Architecture
Real Estate and Housing
City Renewal and Regeneration
21
22
23
24
25
26
27
28
Ecological Environment
City Disaster Management
Slums and Homelessness
City Finance
Crime
Social Welfare
Education
City Institutions
29 Governmental Organization and Administration
30
31
32
33
34
Information City and Technology
Globalization and City Competitiveness
Global Climate Change and Energy
Comparative Studies
Conclusions
Part 1:
Theories
For any discipline to thrive, a sound theoretical foundation is a must. This part of
the introduction provides such a foundation for the discipline of urban governance.
A theory is an explanation of a particular phenomenon. For example, a theory can
be constructed to depict a particular phenomenon using mathematical models,
verbal arguments, computer simulations, and psychological experiments.
Regardless of its format, it must convey a coherent set of ideas that would not be
observable through our common sense reasoning. We can observe how the bodies
move in the world, but only through Newtonian mechanics can we explain why they
interact in such a way that we can make sense of these movements. A theory of
explanation can help us to predict what will happen and take appropriate preventive
actions ahead of time. If we know how the bodies interact through gravity in the
world, we know how to construct buildings and even design aircrafts that can fly.
Theories in urban governance function as both explanations and justifications for two
sets of phenomena: cities and management. Explanations for cities beg objective
expositions how cities do work, while those for management target at depicting how
decisions are made regarding urban issues. Justifications imply value judgments
and are subjective in nature. Justifications for cities prescribe subjectively how
cities should work, while those for management focus on how decisions should be
framed and made. Explanations and justifications for urban governance can be
framed as four sets of theories as shown in Table 1.
Table 1 A Typology of Theories for Urban governance
cities
management
explanations How do cities work?
How are plans and decisions made?
justifications How should cities work? How should plans and decisions be made?
Management broadly defined here includes planning, governing, regulating, and
administrating cities. Planning is narrowed defined as making multiple, linked
decisions in face of uncertainties; governance means making and taking collective
decisions and actions; regulations delineate rights in making decisions; and
administration focuses on making daily decisions, routine or irregular, in
organizational setting. The four modes of actions, that is, plans, governance,
regulations, and administration, in urban governance constitute the activities carried
out by city managers in dealing with physical and non-physical issues in cities. A
useful, effective set of theories of urban governance must cover the four research
questions as depicted in Table 1. More specifically, they should provide a thorough
understanding of how cities do and should work as well as how city managers do and
should make decisions and take actions accordingly through plans, governance,
regulations, and administration.
1. Urbanization and Urban governance
How do cities come about and how they function once exist? There is no definite
answer yet, but we are just beginning to understand and answer the long-lasting
question. Evidence shows that large metropolitans tend to get larger, and more and
more people tend to reside in cities rather than rural areas worldwide. The
question of the emergence of cities is equivalent to the question of how cities grow.
Increasing returns are the key factor. Put simply, increasing returns argue that the
greater the number of persons adopting a particular technology, the more advantage
for the newcomers to use that technology. If we replace the technology with
location, we can say that the more persons residing in a particular location, the more
advantage for the newcomers to reside in that location. In other words, with an
increasing incoming population moving in, a city becomes more attractive due to
improvement of services in public facilities and job opportunities. This
phenomenon immediately leads to the question of whether there is an optimal size
for cities. This question remains yet fully unanswered.
In complex systems, which cities are no doubt an example, sizes matter, as
manifested by the axiom of “More is different.” Living in large cities is different
from living in small ones, simply because cities are composed of interacting agents
and the sizes of the amounts of agents and the intensities of the interactions
between them give rise to qualitative changes in the physical and non-physical
settings in cities. Large cities, such as Beijing and Shanghai, provide more job
opportunities and public facilities, such as transit systems, are more accessible than
smaller cities, such as Hangzhou. However, large cities cause more severe urban ills,
such as air and water pollution and traffic congestion. Whether a particular size of
cities is desirable depends, therefore, on pros and cons of living there, that is, the
tradeoffs between gains and losses in living cities with different sizes. Because
these gains and losses are difficult to measure precisely, the optimal size of cities is
difficult to decide.
What is peculiar about city sizes is that there is regularity. Not only are large cities
fewer than smaller ones, but also that if we take the logarithmic scales of the ranks
and sizes of cities and plot these cities in a plane, they would show as a straight line.
This is called the well-known rank-size rule. The rank-size rule of cities is robust in
time and space. It exists in cities with histories of thousands of years and persists in
many countries.
Cities are complex systems that are difficult to tame, but this difficulty enhances the
usefulness of urban governance in face of complexity, rather than undermining it.
The crux is that only when we have found the deep regularities of how cities function
by theorizing, such as the rank-size rule, can we start to think about how to make
rational choice in complex systems, such as cities, in order to survive, even better, to
thrive. This introduction is targeted at such theorizing practice in hope of dealing
with real urban issues based on a sound theoretical basis.
2. Scope of Urban governance and Related Fields
Urban governance is an interdisciplinary field and concerned with understanding
how urban phenomena come about and what we can do about them. These
phenomena can be roughly divided into physical and non-physical components.
The physical component is something that can be visually perceived with a focus on
urban morphology. Traditionally, it includes, but is not limited to, land/urban
development, real estate investment, infrastructure construction, and ecological
systems. As to the non-physical component, it has to do with structural constraints
within which people behave, including, but not limited to, economic structure,
sociological structure, political structure, and regulatory structure. The physical and
non-physical components interact through people, or more technically agents,
exchanging information and taking actions, so that the city can be viewed as a whole.
Urban governance is concerned with both the physical and non-physical phenomena
and seeks appropriate ways to deal with issues that emerge from the workings of
cities.
Four modes of taking actions are considered: regulations, plans, governance, and
administration, with different focuses. Regulations focus on rights; plans on
decisions in relation to interdependence, irreversibility, indivisibility, and imperfect
foresight, and governance on collective actions. More specifically, regulations deal
with identification of rights within which one is allowed to take actions. Issues such
as evolution, origin, and delineation of rights are considered. Plans as manifested
as policies, visions, strategies, designs, and agendas are made to craft decision
making in the face of interdependent, irreversible, and indivisible decisions with
imperfect foresight. The urban development process is characterized by the four I’s,
and thus plans are effective in coordinating decisions under such circumstances.
Governance is concerned with collective actions, both formal and informal. Formal
collective actions include actions taken by local governments and informal ones
those taken by citizens through participation. Administration focuses on making
daily decisions, routine or contingent, in organizational settings. Urban governance
focuses on both physical and non-physical components of cities, and therefore, all
four modes of actions, i. e., regulations, plans, governance, and administration are
important in order to improve human settlement.
Urban governance is identified as a scientific pursuit to explore in depth and
completeness of how to improve cities by addressing four fundamental research
questions scientifically, or four H’s: 1) How do cities work? 2) How should cities work?
3) How are plans and decisions made? and 4) How should plans and decisions be
made? Together, the four research questions lead to the ultimate question of how
to make rational choice in complex systems, including cities. Two disciplines are
closely related to urban governance: urban planning and public administration. The
former focuses on the physical aspects of cities, whereas the latter on the
non-physical aspects. Urban governance should deal with both the physical and
non-physical aspects of cities through scientific approaches.
3. How Cities Work: Property Rights and Complexity
Cities function in a complex way with numerous actors interacting in and evolving
with physical and non-physical settings. There is no satisfactory theory yet to
explain all aspects of urban activities, but the property rights approach together with
complexity theory provides a promising perspective to understand how cities work.
The physical settings of cities are the outcome of interacting land development
decisions, whereas the non-physical, or institutional, settings, are the outcome of
collective actions on regulations, formal and informal. The physical and
institutional settings interact with each other and agents behave in these constraints
to maximize property rights. Property rights are costly to delineate and the physical
and institutional settings can be perceived as such delineation with some property
rights left in the public domain. Economic agents are motivated to acquire these
property rights left in the public domain. For example, why do cities grow along
transit lines? A property rights approach would argue that transit development
creates additional property rights of accessibility and in adjacent land, developers
construct buildings exactly to acquire these property rights left in the public domain.
In essence, the physical forms of cities reflect to some extent the spatial distribution
of property rights.
Complexity theory deals with complex systems that are far from equilibrium. Cities
are complex systems and, because of interdependence, irreversibility, indivisibility,
and imperfect foresight, they are far from equilibrium as traditionally perceived by
urban economists. To understand how cities work, the traditional economic theory
focusing on equilibrium analysis is insufficient, a new way of looking at cities is
needed that can cope with both phenomena in the equilibrium and far from
equilibrium states. The main question complexity theory intends to address is:
Whether complex systems with seemingly chaotic processes behave in a
predetermined, regular ways. Many evidences to this date show that cities do
follow some principles to function, such as the rank-size rule depicted earlier. The
implication is that a general covering law of urban development might not be
possible, what we need might be a set of theories explaining different aspects of the
workings of cities in order to make appropriate decisions to guide urban
development.
A third theme of the introduction in developing the theoretical foundation for urban
governance is related to rationality. In particular, we argue for a reconsideration of
the meanings of rationality and propose a new way of defining it: framed rationality.
Framed rationality does not refute the traditional standard of rationality of
maximization of subjective expected utility. It simply recognizes the fact that the
utility maximization principle can be valid only in particular frames. With the
conceptions of property rights, complexity, and framed rationality, we argue that
cities work by agents interacting with each other to maximize their utilities in
particular frames, constrained by physical and institutional settings, in order to
acquire property rights left in the public domain.
4. Planning Cities
Urban planning has a long history at least for one hundred years. Though the scope
of planning education and research becomes larger, the emphasis on physical design
of cities remains as a central topic in the discipline. Urban planning can mean many
things, from site planning to globalization, and the term is being used with many
connotations. Urban planning defined here is simply making plans in order to
influence or even guide urban development. Plans are defined narrowly here as
multiple, linked decisions. Evidence shows that when faced with uncertainties, it is
to the decision maker’s benefits to consider more than one decision in relation to
others, rather than make these decisions independently, as argued by the strategy of
divide and conquer. There are two fundamental reasons of why cities need plans.
On the one hand, making plans is particularly useful when the system under
consideration is complex, rather than simple. Complexity means that the elements
in the system are connected with each other in a clustered, rather than random, way.
Cities are complex systems; therefore, making plans is useful in dealing with urban
issues. On the other hand, as argued by Hopkins (2001) depicted earlier in this
introduction, plans are most effective when decisions are interdependent,
irreversible, indivisible, and with imperfect foresight.
Unlike governance and regulations that focus on actions and rights, plans provide
information only. Once publicized, they show the intentions of the planner as to
when and where to take what actions. Plans can be formal documents and informal
ideas residing in the decision maker’s head. Owners of plans share the contents
strategically. In cities, many actors make plans, including developers, public officials,
voluntary groups, and local governments. Plans for urban planning can be
conceived as public, but they could yield benefits to local governments if these plans
are secret, as exemplified in most cities in China. The traditional view of a single
plan for the development of the city under consideration should be replaced by a
web of plans that interact with each other because evidence shows that the latter
conception about plans is closer to reality. The physical setting of cities and the
web of plans for urban development interact with each other, again in a complex
way.
Urban planning should be perceived in a broader context for city managers. Not
only is planning concerned with both physical and institutional settings in cities,
planning should also be explained and prescribed in relation to governance and
regulations. We must make clear the distinction between plans, governance, and
regulations and understand how they complement each other and make cities a
better place to live. For example, we could plan for collective actions and
regulations, and we could also regulate how to plans. Plans can be made both
external and internal to organizational settings, so administrative behavior is also
closely related to planning. In short, city managers must learn when to plan for
urban development and socio-spatial processes in order to take appropriate actions
accordingly, recognizing that plans are only one limited way of improving human
settlement.
5. Governing Cities
As argued earlier, agents in cities are motivated to acquire the property rights left in
the public domain. In particular, most of these property rights are collective goods,
or common pool resources. Collective choices and actions must be made and taken
regarding how to make use of them, the essence of city governance. City
governance thus begs mechanism design through which collective choices can be
made regarding collective goods provisions and common pool resources allocation.
On the one hand, collective goods provision requires commitment from the
participating parties. This can best be demonstrated by a two-person prisoner’s
dilemma. Each of the two players can either cooperate or defect without knowing
which strategy the other player would adopt. When one player cooperates and the
other defects, the former will lose a significant amount of payoff, while the latter will
gain. Both players are motivated to defect, and the Nash equilibrium of the game is
for both players to defect. However, if both players cooperate, they would be
better off than if both of them defect, thus a dilemma. One way to make sure that
both would cooperate is through commitment. Collective goods provision is like
the prisoner’s dilemma game in that each participant is likely to defect, that is, adopt
the free-riding strategy without contributing to the provision, and thus the amount
of collective goods is usually insufficient if no coercive actions are taken.
On the other hand, common pool resources allocation requires an appropriate
mechanism through which these resources are effectively and efficiently allocated to
the affected actors. There are traditionally three modes of allocation of such
resources: governments, contracts, and markets. Common pool resources could be
allocated by local governments in that local governments acquire all such resources
and allocate them to the actors to enhance efficient us of such resources. This
mode of allocation causes high administrative costs of managing common pool
resources. Some argue that common pool resources should be allocated through
market mechanisms, but this mode of allocation would incur high transaction costs.
Alternatively, common pool resources could be allocated through contracts that are
designed collectively by the affected actors. This mode is said to be most desirable
because it would have merits of both the allocation modes by governments and
markets.
A final issue concerning city governance is related to social choice. The well-known
impossibility theorem originally proposed by Arrow (1965) renders any mechanism of
social choice as violating democratic principles, but under some designs, such as a
two-party system of representative government, indirect voting through legislators
would yield the outcomes of social choices consistent with those derived from direct
voting from the actors. City managers must understand alternative ways of making
decisions and taking actions collectively regarding provision of collective goods and
allocation common pool resources, recognizing however that we live in an imperfect
world where no mechanism of social choice fulfill the principle of democracy.
6. Regulating Cities
Regulations identify rights which confine the range of choices the actors in cities can
make. There are two fundamental reasons for need of regulations. On the one
hand, setting regulations circumscribes individual actors’ freedom to enhance
collective efficiency. If the gain of collective benefits derived from regulations
outperform the loss of individual actors’ freedom of choosing, people are motivated
to regulate themselves. On the other hand, setting regulations reduce transaction
costs in market. Regulations delineate property rights, albeit incompletely, so that
transaction cost due to incomplete delineation of rights during any exchange can be
reduced. Zoning is a land use regulation by identifying land use rights to particular
land, and it reduces transaction cost of information gathering in land market if the
developer knows which use is designated in a parcel of land under consideration.
Regulations are a formal type of institutions of enforceable nature; therefore,
regulations constitute partially the institutional settings of cities, along with the
physical ones. Like informal institutions, such as cultural norms, regulations evolve
with cities, meaning that they are not static, but change over time as cities grow.
Due to the costly delineation of property rights, regulations can never clearly specify
the range of permissible rights and need be administrated. Due to the same reason,
once set, regulations usually render some property rights left in the public domain
for the actors to acquire. Enacting building code is a case in point. Though
building code specifies the standard of design and structure for housing and office
constructions, there is always leeway in which the contractor could gain by lowering
the construction cost.
Regulations are different from plans in that they are enforceable and directly affect
the actors’ behaviors, while plans change these behaviors by providing information.
Therefore, in some sense, regulations are irreversible, and plans are not. Both
regulations and plans face interdependence, indivisibility, and imperfect foresight.
Effective regulations lead to desired outcome, but this is difficult because actions
(setting regulations) usually lead to uncertain outcomes due to imperfect foresight.
Therefore, the technique of designing systems of regulations requires prediction of
regulated behaviors, which are usually strategic in response to selected regulations
and can be analyzed through game theory.
City managers must appreciate the usefulness of regulations in shaping how cities
work in a broad context in relation to plans and governance. In particular,
regulations, plans, and governance interact with each other, shaping and being
shaped by the physical and institutional settings within cities. On the one hand,
plans and governance need enforceable regulations to achieve desired outcomes.
Regulations as actions are thought through and taken collectively by plans and
governance. Together, they form the basis of the managerial skills for city managers
to deal with complex urban issues.
7. Administrating Cities
Plans, governance, and regulations usually take place in organizational settings,
which are complex systems with much smaller sizes than cities. An organization can
be perceived as four independent streams of elements interact chaotically with each
other within pre-specified constraints: problems, solutions, decision makers, and
decision situations. Solutions may exist before problems emerge. Decision
makers take part in and leave particular decision situations. Decisions may be made
with no problems to bear on. In some extent, plans, governance, and regulations
are decisions related to urban development and made in such chaotic, organizational
settings. Organizational administration is concerned with how to make such daily
decisions appropriately when faced with uncertainty and complexity.
The traditional view that organizations optimize and administrative behavior is in
order is being challenged. The fact that local governments do not provide
optimized services, rather they opt for votes, is not new to us. Public officials do
not pursue “public interests”; rather they seek private or personal interests. In the
urban governance context, a city manager acts as the principal in representation of
the interests of his constituencies, or agents. This principal-agent relationship
creates difficulties in urban governance administration similar to the representative
government acts in representation of his constituencies. Unlike firms where the
owners are the residual claimers, no one owns local governments as the residual
claimers. As a result, the administrative process in local governments is more like
what garbage can model depicts than as traditional view of optimizing firms.
In the stream of opportunities, the administrative behavior should be different from
that as traditionally perceived. In particular, the city manger as an administrator
should look for opportunities actively to make something happen. For example,
solutions may be made available long before problems and decision situations, or
opportunities, come about. In such a chaotic, uncertain administrative process,
making plans would yield benefits, if decision situations and their outcomes are
interdependent, irreversible, indivisible, and with imperfect foresight.
Organizations complement with plans in that both coordinate decisions to reduce
uncertainties. Like regulations, organizations are structured to streamline decisions,
but they are more apt to changes than regulations. In order to make effective
decisions in relation to plans, governance, and regulations, city managers must
understand how organizations work and constantly seek opportunities where
solutions find themselves. Innovative techniques for making multiple, linked
decisions, that is, making plans in the organizational context are also useful.
Organizations are the microcosm of cities, both being complex systems, but with
much different sizes. Sizes of complex systems matter, so do managerial skills for
these systems. Skills for managing cities are thus different from those for
administration. For large, complex systems, city managers need to seek tipping
points in order to make changes.
Part 2
Methodologies
Methodologies are designs of methods to analyze and deal with particular problems.
They are different from theories in that theories explain phenomena, while
methodologies target at solving problems. Theories provide the underlying
understanding of particular phenomena based on which methods of dealing with
these phenomena are derived.
The recurring theme of the introduction is that cities are complex systems and
complexity theory provides a useful framework for explaining how cities work.
Section 8 discusses in depth the relationship between cities and complexity as a
starting point for the ensuing discussions of the methodologies in urban governance.
We do not aim at providing a general, covering law of how urban issues can be dealt
with, because such law would be too abstract to be useful in solving real world
problems. Alternatively, in Part 2 we address a set of analytic tools that are
commonly used and related to our theme that cities are complex systems. They
include, but are not limited to, decision analysis, policy analysis, planning analysis,
city modeling and analysis, and planning support system.
Decision analysis aims at making single, independent decisions usually involves one
decision maker. It is the simplest analytic framework of choice theory that
pervades many disciplines, including, but not limited to, economics and operations
research. The merit of decision analysis is that it makes crystal clear how a rational
decision maker should think through preferences and uncertainties in order to
choose the best alternative to maximize his or her utility. The logic is water tight,
but the application of such logic is difficult in reality where complexity and
uncertainty reign, rather than simplicity. Regardless, it is worth introducing decision
analysis simply because it is a solid foundation from which other methodologies are
built.
Policy analysis is similar to decision analysis in that it also argues for rational choice,
but in a broader context. Policy analysis tends to be messier and qualitative
oriented; therefore it has a wider range of applications and commonly used in the
field of public administration. According our definition of plans, planning analysis
focuses on making multiple, linked decisions that involve multiple actors. It is much
more demanding than decision analysis in terms of cognitive and computational
efforts. Decision analysis, policy analysis, and planning analysis together provide
the structural framework for the problem solving methodologies of urban
governance. City modeling and analysis links the ontology of urban development to
observed phenomena and through the structural framework, provides a systematic
way of analyzing and dealing with urban issues. Planning support system puts
together the structural framework as well as city modeling and analysis onto a
computational platform, as a set of automated planning tools based on which city
managers can understand and cope with various urban issues. The crux of these
methodologies is logic, without which city managers would be lost in the sea of
methods.
8. Cities and Complexity
Cities are composed of physical and institutional settings in which numerous actors
interact through information exchange to acquire property rights, mostly left in the
public domain. Cities are thus complex systems characterized at least by
emergence and self-organization. Emergence means two things. On the one hand,
simple rules based on which the actors interact create complex outcomes. On the
other hand, these complex outcomes tend to self-organize themselves from which
simple rules emerge. Regardless, collectivity emerges from individuality and the
former cannot be deduced directly and is qualitatively different from the latter. The
behavioral rules for land development are simple in that developers maximize their
utilities by acquiring property rights associated with the land under consideration
and mostly left in the public domain. However, the interaction among developers
shapes complex urban settings, physical and institutional, that defy any existing
measures to depict precisely.
We are just beginning to look at cities in a new way of complexity. Different from
the traditional top-down approach, the complexity approach looks at cities from the
bottom up. It starts with the individual actors by imposing simple, interactive rules
for these actors, and then looks at what collective patterns would emerge from such
interaction. This new way of looking at cities has significant impact on how we
should plan, govern, and regulate, that is, manage cities. The traditional, top-down
approach to cities assumes an average actor ignoring differences among the actors
and perceives the rules governing urban development as given. The complexity,
bottom-up approach to cities takes into account the idiosyncratic characters of the
actors and considers the rules on which urban development relies as emergent.
The traditional, top down approach prompted an idealized way of managing cities by
seeking a covering-law-like comprehensive rationality to make plans for urban
development. Like decision analysis, this perfect rationality is beautiful in theory,
but when put into use, it encounters difficulties. The complexity, bottom-up
approach implies a less ambitious way of managing cities by looking for a coherent
set of theories and methods in explaining cities and dealing with urban issues.
Instead of looking for a theory of everything, the complexity, bottom-up approach
seeks theories of things.
At crossroad of the paradigm shift in sciences in general, and city theories in
particular, city managers must keep looking for new ways of looking at cities, while
recognizing the merits of the traditional approach, such as city economics. New
theories prompt new real world applications. We need innovative, effective ways of
planning, governing, and regulating cities that are derived from new discoveries of
how cities work. Network science, cellular automata, agent-based modeling, and
fractal geometry, to name just a few, are such new discoveries of how cities work.
We have a long way to go from these new theories to applications, but they shed
useful lights into how we can deal with complexity.
9. Decision Analysis
Decision analysis is an interdisciplinary field that focuses on how to make appropriate
decisions in face of uncertainties, drawing on work in, among others, economics,
operations research, system analysis, and psychology. Decision analysis has become
a specialized field with its own institutions and journals. It aims at helping decision
makers to frame decision situations and select the best actions according to solid,
rational procedures. Traditionally, there are three camps of decision theories:
descriptive, normative, and prescriptive. Descriptive decision theories purport to
explain how people actually do make decisions. Normative decision theories aim at
constructing the theoretical foundation for depicting how people should make
decisions. Prescriptive theories intend to help people to make decisions
conforming to normative the normative standard of rationality. The standard of
rationality that makes the distinction between descriptive, normative, and
prescriptive decision theories is the subjective expected utility (SEU) model. The
SEU model stipulates that the rational decision maker choose the best alternative in
order to maximize his or her expected utility. Though the SEU model provides a
sound theoretical basis for normative decision theories, it has been invalidated by
numerous psychological experiments, and thus others suggest variants of the SEU
model in describing how people do make decision, including prospect theory and
bounded rationality.
We argue that the traditional distinction between descriptive, normative, and
prescriptive decision theories enhances rather than dispels the confusion about our
understanding of rationality. In this introduction, we propose an alternative view of
rationality, called framed rationality. Rather than refuting the SEU model, we argue
that that model is universally valid, but only subject to particular frames. Put
differently, people in making decisions are rational depending on how the problems
are framed. Therefore, the distinction between descriptive and normative
perspectives of explaining behaviors is unnecessary because they interpret observed
behaviors from different frames. We cannot conclude that if the decision maker’s
choice violates the normative standard, he or she is not rational. He or she may still
be rational in his or her frames of understanding the problems faced and act
accordingly. Experiments show that framed rationality is valid in that drawing on
the elicitation questions used in prospect theory, preference reversals can be
explained by the SEU model.
Decision making is a central task for city managers, so they must understand the
underlying logic of how people make decisions, not only to improve their decision
making skills but also to understand the decision situations in which people interact.
Decision analysis is a useful theoretical framework to make sense of rational choice
behavior, but when faced with complexity, decision analysis has limitations.
Rationality is a long-lasting question not yet fully answered, but framed rationality as
proposed in the introduction sheds new light into our understanding of rationality
and effective decision making tools can be derived from such understanding.
10. Policy Analysis
Policy analysis can be viewed as applications of decision analysis to make real world
public policies. If decision analysis is the hard, deductive logic of making such
policies, then policy analysis is the soft, empirical process of making these policies.
Policy analysis is therefore messier and more qualitative oriented than decision
analysis. Policy analysis is an art in that the policy maker needs to make clear
decision situations and frame the policies in an appropriate way so that useful
decision models can be applied to the situations under consideration.
Policy analysis draws on a wide range of decision tools to deal with real world
situations, including, among others, linearly programming, cost-benefit analysis,
multi-attribute decision making, and decision analysis. Different from planning
analysis that focuses on multiple, linked decisions, policy analysis emphasizes single
decisions, but sometimes in a very broad context. Different from decision analysis
that can be applied to personal decisions, policy analysis aims at making policies in
the public sector that affect a wide range of actors. Thus the issues faced by the
policy maker are usually much more complex than the decision maker who intends to
apply decision analysis to solve the problems he or she is concerned. Policies must
take into account broader issues related to the society, such as social welfare, justice,
equity, and esthetics.
Policy analysis is concerned with a wide range of issues related to cities, regions,
states, and international affairs, from the public sector perspective. It is one of the
core areas in public administration, a field that pursues excellence in managing public
affairs. Policy analysis applied in urban governance can fill the gap between
decision analysis dealing with simple problems and planning analysis coping with
complex problems in that policy analysis applies the logic of both to a wide range of
real world urban issues.
Policies, if narrowly defined as rules to follow by actions, can serve as one of five
mechanisms through which plans function, that is, agendas, visions, policies, designs,
and strategies. In other words, policies are decision processes through which plans
influence urban development. Though understanding the logic of making decisions
and plans is a must for effective city managers, how to seek opportunities to apply
the logic to deal with real world urban issues is another challenge that city managers
must face. Bargaining and negotiation of policies are quite common in the public
arena.
City managers should know how to make effective urban policies, not just by the
logic of decision analysis and planning analysis, but gain insight into how the three
methodologies work together to make rational choices in complex systems of
interest. Decision analysis focuses on making single decisions, planning analysis on
making multiple, linked decisions, and policy analysis on applying the underlying
logic of decisions and plans to a seemingly chaotic, complex urban processes.
11. Planning Analysis
Making plans, or planning, is precisely defined in this introduction as making multiple,
linked decisions. Different from decision analysis that focuses on making single,
independent decisions, planning analysis looks into ways of making more than one
decisions that are linked to each other. The presumption is that making multiple,
linked decisions yields more benefit than making these decisions independently.
Though this presumption has not been proved deductively and empirically, numerical
examples show that the presumption works. For example, in land development,
considering both housing and infrastructure decisions at the same time yields higher
net benefit to the developer; in the inventory approach to urban growth boundaries,
making linked expansion decisions in time as manifested by the event-driven system
gives rise to lower total cost than making these decisions independent in time as the
time-driven system. It is highly plausible that making multiple, linked decisions in
time and space would yield higher payoffs than making these decisions
independently. In addition, city managers are faced with a complexity of urban
development. The traditional choice theory emphasizing on making single
decisions is insufficient in dealing with such complexity. What is needed is a way of
exploring the relationship between multiple decisions with multiple actors, problems,
solutions, and decision situations.
One approach to making multiple, linked decisions in face of uncertainty is Decision
Network. Decision Network is derived from garbage can model, the strategic choice
approach, and decision tree by focuses on contexts, relationship, and sequence of
decisions. There are four elements in a decision network: problems, solutions,
decision makers, and decision situations. Problems, solutions, and decision makers
are associated with decision situations given certain structural constraints. For
example, city managers, urban planners, and the mayor have different authorities in
attending which decision situations to make decisions. Expansions of urban growth
boundaries and transit systems as problems are discussed in different decision
situations. The structural constraints imply the relationship between the elements
in the decision network. Problems give rise to negative effects, whereas solutions
and decision makers positive effects. Given the decision network of depicting the
context, relationship, and sequence of decisions, and the measurement of the
negative and positive effects, Decision Network requires the city manager to find an
optimal solution to the network problem in order to maximize the overall positive
effects.
City managers must learn to make multiple, linked decisions in face of complexity
and uncertainty. The traditional choice theory of making single, independent
decisions based on which decision analysis and policy analysis are developed is
insufficient. Making multiple, linked decisions viewed as a design problem of
determining which problem, solution, or decision maker should be related to which
decision situation is insufficient in dealing with complexity. Decision Network
should be developed in such a way that it can deal with complexity as strategies.
12. Urban Modeling and Analysis
Modeling is a way of understanding the ontology of phenomena under consideration.
Without modeling, we are unable to represent and communicate ideas about the
phenomena of interest; thus models themselves are languages for communication.
City modeling has a long history and can be traced as early as 1960s. Models about
cities are constructs of explaining how cities work, whether through mathematics,
graphics, computer simulations, or structured experiments. Models about cities are
useful if they yield insights into what actions we should take to prevent something
from happening. If we anticipate population growth at particular locations in
particular time, we should build sufficient infrastructure to serve that population
before they come about. City modeling thus is related not only to explaining but
also to forecasting.
The approach to city modeling evolves from graphics, through mathematics, to
computer experiments. Graphic city models, as manifested in urban design, are
iconic models that represent how cities actually look like into the future by graphics.
Mathematical city models, as manifested in urban economics, mainly follow the
economic approach to market systems by constructing mathematical equations to
depict the workings of cities through, for example, land rents and transportation
costs. Computer experiments, as manifested in complexity theory, look deep inside
cities for how individual actors behave and interact, and construct computer
simulations to explore into policy implications in order for city managers to take
appropriate actions ahead of time.
City models are useful if they can represent the essence of how cities work. All city
models suffer from simplicity because no models can represent completely how
cities work. City modeling to some extent is like story-telling. Good city models
should cover the essential elements of cities and depict their relationship at least in a
realistic way. With the advance of the computing technology, city modeling now
can be run on a computer with the city manager playing god of the city system,
manipulating the parameters of the system, and observing what would happen.
Numerous computer simulations and experiments now have been conducted to
emulate how cities work. Evidence has shown that underlying the seemingly
chaotic process of urban development lies the deep, collective regularity of city
structures, physical or institutional. We are just beginning to uncover these deep
regularities and seek their implications regarding how cities should be managed.
City managers must be acquainted with various modeling techniques, be they
graphic, mathematical, or computational, and make use of these models in urban
governance practice. Without city modeling, we might lose sight of what
appropriate actions to take by delving too deep into idiosyncratic happenings.
Constructing useful city models may help us to not only understand how the world
works, but also how we should respond to it.
13. Planning Support Systems
Planning support system is an idealized computer system for helping city managers
to make plans for urban development and take appropriate actions. No such
system exists for daily use in real cities, but the idea of planning support system has
been developed for at least 25 years. In essence, a planning support system is to
incorporate the methodologies for urban governance we introduced so far onto a
computer platform. Simply put, it includes at least a database system, a city
modeling system, and a planning tools system. The database system includes the
most updated data about the city under consideration, including, but not limited to,
population, land use, transportation, housing, real estate, and environment. The
data can be physically scattered among and managed by various government units,
but integrated through the internet, such as a data warehouse system. The
database system itself provides the most recent data about the city in various
conditions in order for the city manager to monitor urban affairs and take
appropriate daily actions. In particular, the database system should include
relevant plans that are created by various entities, be they transportation, land use,
infrastructure, and housing. The idea is that using these plans the city manager
would realize the implication of actions in relation to these plans.
The city modeling system captures the urban process of the city of interest in order
to answer the what-if type of questions. For example, what effects would a
construction of new highway be on local land use patterns? To answer this
question, we need to model the urban development process using the techniques
depicted in the previous section, change the spatial, socio-economic configurations
of the city system caused by the construction of highway, and see what happens.
The city modeling can be done through agent-based modeling in that the spatial
interaction of developers, the local government, landowners, households, and firms
is taken into account explicitly. The planning tools system provides a set of tools
derived from decision analysis, policy analysis, and planning analysis as to what
actions to take, given the answers to the what-if type of questions. If the highway
construction would result in deteriorated downtown development, should the city
manager propose alternative routes and interchanges of the highway, or should
there be a new city center in place of the old downtown? Regardless, the database,
city modeling, and planning tools systems should be closely coupled in a planning
support system so that the output from one system may serve as the input of
another.
City managers must acquaint themselves with the cutting-edge of computation
technology in order to manage cities in a timely fashion. Though the idea of
planning support system has not be fully explored in practice, with the increasing
need of accurate, timely decisions, the system provides a promising platform where
the methodologies depicted here can be integrated efficiently. In particular, with
the advance of the internet technology, public participation would be made easier
through a planning support system.
Part 3: Applications
This part of applications provides a set of application areas based on the theories and
methodologies depicted in Part 1 and Part 2. Each application area is introduced by
the general considerations of managing the subsystem in relation to urban
governance, with conclusions at the end.
14. Transportation
This section introduces general considerations of managing city transportation.
15. Land Use
This section introduces general considerations of managing city land use.
16. Sanitary and Infrastructure
This section introduces general considerations of managing city sanitary and
infrastructure systems.
17. Building and Constructing
This section introduces general considerations of managing city building and
constructing projects.
18. Urban Design and Landscape Architecture
This section introduces general design principles for city design and landscape
architecture in urban governance.
19. Real Estate and Housing
This section introduces general principles for making real estate investment and
housing policies in urban governance.
20. Urban Renewal and Regeneration
This section introduces general considerations of managing city renewal and
regeneration in urban governance.
21. Ecological Environment
This section introduces general principles of ecological and environmental planning
in urban governance.
22. City Disaster Management
This section introduces general principles of managing city disastrous events in urban
governance.
23. Slums and Homelessness
This section focuses on slums and homelessness to eliminate poverty in urban
governance.
24. City Finance
This section introduces how city finance systems work and how to manage them.
25. Crime
This section introduces city crimes and how to prevent them from happening.
26. Social Welfare
This section introduces general considerations of how to make social welfare policies
in urban governance.
27. Education
This section introduces the education systems and how to manage them in urban
governance.
28. City Institutions
This section introduces various city institutions and how they interact with the
physical settings in urban governance.
29. Governmental Organization and Administration
This section introduces the working of governmental organizations and
administrative behaviors take place in these organizations.
30. Information City and Technology
This section introduces the notion of information city and how technology affects
urban development.
31. Globalization and City Competitiveness
This section introduces the trend of globalization and general principles of enhancing
city competitiveness.
32. Global Climate Change and Energy
This section introduces the effects of global climate change on cities and discusses
energy policies regarding the global climate change.
33. Comparative Studies
This section conducts comparative studies regarding urban governance in different
cultural and socio-economic settings.
34. Conclusions
This section concludes.