Table of Contents
Collaborative Development of Narratives and Models for
Steering Inter-Organizational Networks
Philip C. Emmi, Craig B. Forster, Jim I. Mills, Tarla Rai Peterson,
Jessica L. Durfee and Frank X. Lilly
University of Utah
College of Architecture + Planning
375 S. 1530 East, Room 235 AAC
Phone: 1-801-581-4255 Fax: 1-801-581-8217
emmi@arch.utah.edu
Abstract
The power to direct and manage change within metropolitan areas is increasingly
dispersed among a loosely interconnected set of mostly local organizations, agencies and
actors that form a special type of urban inter-organizational network. Increasingly, the
quality of metropolitan regional governance depends upon IO network capacity to
articulate systemically insightful urban development strategies, i.e., to exercise a
capacity for network steering. We outline an IO network steering capacity-support
process that combines collaborative learning, narrative storytelling, and system
dynamics modeling with the goal of deepening insights into urban human/biophysical
processes and securing greater resilience in metropolitan regional governance. Our
process promotes comprehension of complex urban processes through stories about past
trajectories and future growth scenarios that frame issues within collaborative learning
workshops for deliberation by local opinion leaders. This initiative is part of a larger
research study on greenhouse gas emissions in relation to human and biological
activities within metropolitan areas.
Keywords: Collaborative learning, narratives, system dynamics, steering inter-
organizational networks
Introduction
As our conception of government and its capacity for societal guidance changes, so too,
does our approach to planning and decision-making. Increasingly, we recognize that the
power to guide and direct change is dispersed among a variety of loosely interconnected
organizations, agencies and actors. Within an urban context, we recognize organizational
networks. Network members are typically aligned around a common set of concerns or
functions, interact with regular frequency and adjust their sense of the possible one
relative to the other in a pattern of mutual interdependency. This occurs, for example, in
the pubic welfare community as state and local welfare agencies interact frequently with
not-for-profit and charitable welfare service providers, welfare client advocacy groups,
state legislative sub-committees and corporate-sponsored advocates for more limited
government. We refer to these constellations of relationships as networks of inter-
organizational (IO) relations or IO networks (see Ebers, 1997).
As the governance of regionally organized political communities depends
increasingly upon the capacity of IO networks to initiate and consolidate concerted
action, the question of network steering looms ever-more present. The question of
network steering is fundamentally an epistemological question: how and in what manner
does an inter-organizational network come to know its own best interests? What capacity
does it have to monitor, envision, analyze and assess its options for the future? What
means does it have to surface hidden assumptions, uncover covert agendas and negotiate
differences of persuasion? How does it frame issues, expand or collapse the temporal and
spatial scope of issue delineation, and delineate the inclusion or exclusion of relevant
stakeholders? How does it contain the tendency to over-simplify reality to better privilege
selected interests? How does it reach beyond the grip of linear thinking to conceptualize
its domain as a domain of uncertainty, complexity, and non-linearity?
We raise these issues against the background of a specific set of circumstances. As
investigators on a National Science Foundation Biocomplexity Program grant, we are
developing a framework through which to better understand the formation and
sequestration of urban trace gas emissions in Utah’s Salt Lake Valley, the core urban
center of a metropolitan region strung linearly along major north-south valleys at the
western face of the Wasatch Mountains, a high mountain desert region of 1.2 million
urban inhabitants living in what is know locally as the Wasatch Front.
The Urban Trace-gas Emissions Study (UTES) seeks to understand the dynamics of
urban development that shape future trajectories of global greenhouse gases such as
carbon dioxide, water vapor and volatile organic compounds. We are developing a
system dynamics model of urban growth and change and tuning it to local historical
observations on indicators of urban system performance. The model is enabling us to
experiment with alternative long-term urban land use and transportation policy options to
learn how policies affect urban land consumption, traffic congestion, atmospheric
emissions and other indicators of urban system performance.
In concert with model development, we are engaging local decision makers and
opinion shapers in collaborative learning (Stahl, 2000). Our goal is to explore the degree
to which a group-mediated dynamic systems modeling activity might facilitate the
emergence of a more complex and foresighted consensus about the operation of and
future options within this policy domain.
Engaging decision makers and opinion shapers leads us to focus on the set of IO
relations organized around issues of urban growth and development. In particular, we
are interested in the subset of agencies and IO relations associated with land development
and transportation facility investments. These include departments of transportation at all
levels of government, the state transportation commission, the metropolitan planning
organization, the state quality growth commission, the regional public transit authority
commission, leaders of regional growth visioning projects, a cluster of smart growth and
balanced transportation advocacy groups, an assortment of construction and engineering
firms, a home builders association, a local board of realtors, a local organization of urban
planners and plan commission members, and several key mayoral staff members (see
Table 1).
We approach these two initiatives with specific research questions in mind. Can an
urban systems simulation model help researchers articulate a compelling storyline about
how cities work? Can the resulting narrative storyline be instrumental in engaging the
imagination of decision makers and opinion shapers? Can we collaboratively design an
iterative process for a mutual accommodation between (1) an urban narrative that will be
generally accepted by network members and (2) a system dynamics model we mutually
rely upon for policy exploration? Will a mutually accepted urban narrative serve to
effectively empower an inter-organizational network to consolidate purpose and initiate
concerted action?
This is the background to a complex research challenge that should lend insight into
the roles that collaborative learning, system dynamics modeling, and narrative
storytelling might play in answering unresolved question about how to secure a degree of
coherent regional governance through inter-organizational network steering.
Approach
UTES is not only the acronym for the research project called Urban Trace-gas Emissions
Study, it is also the name of a local Indian tribe whose native territory the State of Utah
derives its name. The study is a three-year inter-disciplinary effort that involves
researchers from seven different colleges on the University of Utah campus.
The three thrusts of the research include measurements, process studies and
community involvement. Measurements seek to distinguish anthropogenic and biogenic
sources of CO,, define the chemical composition and source of volatile organic
compounds, measure the concentration and size distribution of particulate matter, identify
the rates of vehicle and building-based fuel consumption within specific neighborhoods,
and to track thermal and gaseous fluxes emerging from neighborhood-scale observations.
Process studies include three related efforts. The first effort seeks to delineate how
trees and urban forests influence, through shade and evapo-transpiration, both urban
temperatures and urban humidity levels. The second effort seeks to simulate the self-
reinforcing feedback relationships between urban land development, urban transportation
system investments, land developmental density declines and per capita vehicular use.
Developing an understanding of these relationships enables us to explore the implications
of alternative policy choices on fuel use, atmospheric emissions, public health,
environmental remediation and basic sector job formation. Finally, the third effort seeks
to understand the dynamics of urban heat fluxes and simulate the long-term effects of
urban morphologic change on the build-up and dissipation of heat in urban areas and
subsequent effects on fuel consumption and atmospheric emissions. All three efforts are
to be merged into a single urban dynamics simulation model focusing on the interactions
between human and biophysical dimensions of an urban ecosystem.
The community involvement phase will test the social significance of scientific
measurements, process studies and simulation models. Here the basic questions are
straightforward. Does any of this research matter? Will it change opinions about what
needs to be done to better manage urban affairs? Can we develop a process that will lead
to urban policy choices that reflect observations and insights developed through research
on urban human and biophysical processes?
Multiple strands of social theory and intentions guide us with regard to this last
question. From Anthony Giddens (1984) and Patricia Healey (1997), we draw upon an
“institutionalist” conception of the simultaneous interdependence and joint determination
of both institutional practices and individual choices. This provides a window on the way
both institutionalized social and political relations as well as personal choices influence
current patterns of land use, transportation planning, fuel use and atmospheric emissions.
These authors help one to see the work of participants in local governance as part of an
ongoing process that shapes both urban planning decision practices and individual
choices and behaviors within the city.
We draw on Habermas’s Theory of Communicative Action (1984) and its intellectual
derivatives in urban planning (Forester, 1999; Innes, 1995) to better understand discourse
ethics and the normative principles for evaluating the quality of communications that
under-gird planning decisions.
State and local governments are under continual pressure to reorganize the principles
and practices of metropolitan regional planning. We rely on the insights of Sassen (1991),
Peirce (1993) and Orfield and Rusk (2000) regarding the increasing obligations of
metropolitan governance structures to secure for their regions a viable role within an
emerging global hierarchy of competing city-states. We see in this literature a way to link
the concerns of local urban policy decision makers with a variety of global-scale
processes issues including greenhouse gas emissions.
Castells (1996) draws attention to the diminishing role of semi-autonomous
bureaucratic authority in pubic governance and the increasing devolution of governing
powers to diffuse networks of individuals, agencies and organizations. Geerling (1999)
employs this trend in his discussion of planning as network steering within IO networks
focused on the management of urban affairs. We rely on both for comprehending
opportunities for the integration of research findings and collaborative deliberation
procedures into the steering function of an urban IO network.
We draw on Richmond (1992) and Ford (1999) for instruction on the design and
development of system dynamics models. We combine these skills with insights on urban
dynamics from Newman and Kenworthy (1989) among others to construct a dynamic
urban system simulation model. The model’s dynamic organizing principle is grounded
in the observation that most cities, when faced with traffic congestion, build more
roadways that induce more urban land development at increasingly lower densities thus
generating increasingly more traffic for which increasingly more roads need to be built.
This self-reinforcing process causes urban land consumption, traffic generation and urban
road building to greatly outpace underlying population and employment dynamics
(Emmi, 2003). If not successfully dampened, the feedback mechanism leads to fiscal,
human health and environmental effects that undercut the region’s continued capacity for
basic job formation. After a slow overshoot-and-collapse, lowered rates of basic job
formation drop the region to a new equilibrium at a lower standard than could have been
otherwise obtained.
Donald Michael (1973) provides inspiration regarding the possibilities of
organizational learning. Checkland (1990) and Peter Senge (1990) tie systems thinking
and the construction of mental models to the organization’s learning process. Daniels and
Walker (2001) show how collaborative learning can be used to resolve conflicts within
and among organizations. Vennix (1996), Stave (2002) and Peterson et al. (2004)
combine these and proceeding ideas together for instruction on group mediated dynamic
simulation modeling as an approach to environmental consensus building.
Finally, our thinking is informed by the work of Throgmorton (1996) and Beauregard
(2003) on the importance of persuasive, locally grounded, urban narratives. These authors
suggest that persuasive urban narratives might be transformative devices for helping
protagonists in a planning process re-envision the systems they seek to manage and the
broader effects of their management preferences on both the welfare of others as well as
their collective futures. Yet, because of the contributions of Scott (1998) and Flyvbjerg
(1998), we remain alert to the way power seeks a self-serving simplification of urban
narratives. In defense of this possibility, we recognize the need to frame urban narratives,
as Lakoff (1997) instructs, in a language that is not automatically off-putting to those
whose most invested in simplified narratives.
Computer-Aided Story Telling and its Role in Consensus Building
We are implementing the approach outlined above as a central effort within the UTES
community involvement initiative. First, we develop and tune a systems dynamic model
of the Salt Lake Valley to capture the essential dynamics governing urban sprawl and
congestion. We ensure that it replicates accurately historic observations. We explore
alternative urban policy options. We define baseline and alternative policy scenarios as
well as their effect on the management of congestion and sprawl as outlined by Emmi
and Forster (2003) and Emmi (2003). We attach to the basic model the extensions needed
to capture urban fiscal management, fuel use and atmospheric emissions that are
associated with different transportation regimes and land developmental densities. We
infer the implications these have on fiscal capacity, public health and environmental
remediation and indirectly on basic job formation within the region.
Second, we rely on our urban systems modeling experience to draft an urban narrative
about the region’s recent history and possible future. At first the narrative is impenetrably
mechanistic and heavily burdened with statistics. The sequential progression of the story
is driven by a disembodied logic and fails to frame the essential issues in terms and
metaphors that correspond to local values.
Third, the narrative is re-cast to be more effectively transformative. Main objectives
are to preclude the over-simplification of urban realities, project the vision of a
manageable future, identify the existence of a mutually beneficial solution set, and point
out the benfits of consensus around workable strategies for addressing pressing problems.
This is done with conscious awareness of the need to evoke both a rational and an
emotional response. The sequential progression of the story is advanced so that it begins
with the end, that is, with a threat to the continued economic vitality of the region. The
language of the story is reframed in metaphorical terms to represent the city as a difficult
and dangerous place that must be made good through the application of discipline and
moral authority or else be cut free to face the discipline of a callously competitive world
(Powell, 2003). This “strict father” metaphor accurately reflects the model’s dynamic
organizing principle and thus the narrative’s underlying message while framing that
message in terms acceptable to most members of the local IO network. The resulting
urban narrative is reproduced in Appendix I.
Fourth, we confront the likelihood that, while we may have a message, we are not the
right messengers. So we intend to organize a group of five to seven local opinion leaders
with whom we can work collaboratively to re-draft an urban narrative that will be
accessible to a broad range of decision makers and policy shapers. We expect that this
may require group exploration of our urban system dynamics model, and we are prepared
to engage in that if needed. We hope this will produce an even more transparent version
of the narrative supported by more extensive visual and graphical representations of the
basic argument. Since the region has produced a core of opinion leaders who are forward
thinking on these matters, we are confident that a suitable panel can be assembled.
Fifth, we will identify roughly twenty decision makers and opinion leaders to
participate in workshops focused on learning about the future of our local region. These
people will be drawn from larger lists of individuals, agencies and organizations
influential locally in urban land use and transportation planning (see Table 1).
Engaging Opinion Leaders and Decision-Makers in Collaborative Learning
The UTES team is in the process of engaging local opinion leaders and decision-
makers through a series of five, one-half day workshops intended to develop an improved
understanding of how their planning/management decisions might affect urban
atmospheric emissions. We will be using a collaborative learning/mediated modeling
process that helps opinion leaders and decision-makers appreciate more fully the roles
they play in urban processes. In doing so, we trust they will tend increasingly to endorse
actions that respond to a deepened view of urban dynamics and will lead to a series of
beneficial results.
The first workshop will be held in Salt Lake City on July 18, 2004. We will report
preliminary results from this workshop in our oral presentation.
One of the main purposes for the workshops is to create an environment that
facilitates joint learning among all participants (including the research team), and that
builds political capital by laying the foundation for additional collaborative learning (on
any topic) among local opinion leaders and decision makers. The workshops are designed
to accomplish the following objectives:
1. Inform participants about the reasons why atmospheric trace gas emissions
reductions should be considered,
2. Relate trace gas emissions to the co-produced criteria pollutants that are more
central to the planning/management issues of concern to the participants,
3. Involve participants in joint discovery of cost-saving advantages of emissions
reduction, and
4. Integrate the diverse perspectives of the participants who all play a role in
making decisions that impact emissions reduction in the region.
The 5-workshop series begins with an assessment of the knowledge base of the
participants. Assessment results will be used to develop subsequent workshop
learning/modeling activities. The workshops will incorporate the diverse perspectives of
participants and present balanced information that illustrates the importance of emissions
reduction in both technical and practical terms. In addition, the difficulties and benefits
of implementing emissions reduction strategies will be outlined and the need to develop
interactive relationships between participants will be surfaced.
Our workshop strategy focuses on collaborative learning between the UTES team and
workshop participants (Daniels and Walker, 2001). UTES team members will be
involved as presenters and observers who exchange ideas with the community
participants. This approach provides opportunities for participants to discover common
ground and negotiate mutual benefits. By working within a learning format, participants
with varied values, interests, and insights can establish a common understanding with
diminished fear of practical, political impacts. This encourages participants to integrate
individual perspectives with systemic views to everyone’s mutual benefit.
Participants in the workshops will include decision-maker and opinion leaders
recruited from the businesses, agencies and organizations given in Table 1. The first
workshop will serve five primary functions: participants will (1) identify and discuss the
interests and concerns; (2) discuss the value of taking a systemic perspective toward
complex problems and how collaborative learning helps all to do so; (3) receive training
to facilitate collaborative discussion skills; (4) collaboratively decide what further
information will be needed, who might provide that information, and at which future
workshop it would be presented and (5) self-select for participation in subsequent
workshops.
An urban narrative outlining urban human/biophysical proce: and alternative
urban development strategies will be distributed to inform prospective workshop
participants during the recruiting process and will play a key role in the collaborative
learning process. We expect to some degree during every session that an evolving urban
narrative will serve as a vehicle for integrating systems theoretic concepts with the
adoption of shared labels, language and meanings and the comprehension of urban and
biophysical processes.
These three narrative-based processes will help achieve ongoing objectives with
respect to participants developing a common knowledge base on major issues, gaining
conceptual sophistication about urban processes, and collectively deepening the urban
narrative itself. These functions will also help participants instruct research team
members on how to enrich both the urban narrative’s constructs as well as the urban
simulation model’s treatment of narrative constructs.
In the 2 workshop we will draw upon the urban narrative to create conceptual
system maps of how the urban region works and how the parts interact to create an urban
dynamic that is not easily known without a systems view. In the 3“ workshop we will
refine the conceptual model maps created during the second workshop. Decision makers
will send the research team away with requests for the assimilation of their ideas into a
quantitative model. The team members will bring the requested model to workshop # 4.
Workshop # 4 will require access to computer workstations and will be a modeling
workshop. This session will include learning to work with the system model’s user
interface to explore the outcomes of various developmental alternatives. Participants will
suggest revisions of all sorts including new alternatives they might see as important. If
they ask for things the modelers know are not possible to produce, the modelers will say
so, and will explain why. Workshop # 5 also will require the workstations for the
continued collaborative design of experiments in urban development and emission
reduction strategies.
During the final workshop, participants will work with the modelers to design and
simulate experiments that will answer questions about the consequences of various urban
planning/management strategies. Participants will present the results of their
explorations to each other and UTES team members. We hope that growing competency
will enable the participants to learn how to use the systems model independently from
UTES team modelers. This, in turn, should enable them to simulate scenarios associated
with planning/management alternatives that are of particular interest to their parent
organizations and their constituencies.
Throughout, workshop participants will continue developing their communication
skills and their knowledge base while contributing to successive revisions of the
narrative. In addition, they will work with modelers from the research team to develop
and test a simulation model for urban activity levels and trace gas emissions.
Participants will work together to refine a succession of narratives and systems maps,
developing them as guides for systems modeling. This will involve translating narratives
and maps represented linguistically and diagrammatically into iconographic
representations that collectively form the quantitative systems model. This translation, or
quantification, will be grounded in theoretical concepts, data, empirical correlations and
expert opinion. Modelers from the research team will lead participants through this
translation and make participant-induced adjustments between successive workshops
(Fig. 1).
The revisions need not capture a collective perspective; probably they won’t; instead
revisions will reflect the participant’s diverse perspectives. Also, because the model they
are building will have multiple alternatives, and the continual possibility to develop new
alternatives, it should serve well to mediate between differences among participants with
substantially diverse interests and perspectives regarding urban processes and
atmospheric emissions.
The systems-modeling process and the urban narrative revision process complement
one another. Both facilitate collaborative learning among participants and UTES team
members enabling all to share their learning with others (Vennix, 1996).
These complementary processes should deepen participants’ understanding of the
impacts that various urban policies have on the region’s future trajectory. This should be
beneficial for participants as they interact with their agency staff and their constituents
and lead, in turn, to a sense of ownership over the process. Should these things occur, it
would make the modeling process and the political capital it builds substantially more
important than the model itself (Peterson, Kenimer, and Grant, 2004).
After the workshops are done, the resulting urban narrative will be distributed
throughout the IO network. A description of how it evolved will accompany the
narrative. Comments and critiques will be invited and responded to. The narrative,
comments and responses thereto will be both re-distributed and forwarded to the relevant
governmental agencies for assimilation into their plans and project designs. These will
specifically include the region’s metropolitan planning organization, its regional transit
authority, the state transportation commission, the state department of transportation, the
state quality growth commission and concerned county and municipal leaders.
Discussion
The approach taken here represents a variation on emerging practice in mutual
learning through group-mediated model building. It seeks to deploy the proposed
variation as a way to engage in collaborative inter-organizational network steering. The
variation emphasizes the importance of both collaborative learning and narrative story
telling. Drafting an initial urban narrative is closely linked to the power of systems
thinking and system dynamics model building. Successive revision of a persuasive, in-
depth and broadly reviewed urban narrative represents good practice in collaborative
learning and is advanced as a means for creating participant ownership over the
deliberative process. Ownership is assumed to be necessary for the adoption of deeper
understandings by opinion leaders and acceptance by IO network members. (Participant
ownership over the evolving urban simulation model is indirect. Participants will
understand that the model and the narrative tell the same story yet they will not be asked
to nor should they prepared to “own” the model.)
On the critical side, the process takes lots of time. We expect that the use of an urban
narrative will shorten the time it typically takes, since the narrative will serve both
workshop participants and IO members as a vehicle for integrating systems theoretic
concepts with both the comprehension of urban human and biophysical processes as well
as the adoption of shared terms, language and meanings.
The ongoing UTES project admittedly deals with powerful actors and is embedded in
a deeply political context. We are not dealing with technocrats, mid-level bureaucrats nor
under-funded representatives of public interest advocacy groups. Our corroborators are
instead senior-level policy decision makers and well-regarded public opinion leaders.
These are “people of substance” whose time and patience is limited, people who are
accustomed to defining agendas and not having them set a priori. These are not people
who should be expected to follow a detailed line of reasoning into the interstices of a
system dynamics model. In their world, analysis and reason are weak tools. To an
important degree, we will need to de-politicize the workshop environment by
emphasizing its focus on collaborative learning. But most will both expect and
understand that important political issues are just beneath the surface. Correspondingly,
the urban narrative will need to be de-politicized by representing it as a statement in
advancement of the public interest.
In this regard, our project is clearly hazardous and should not be tried at home. To the
degree that our chances of some su are better here, it can be attributed, in large part,
to regional contextual variables. The issues we are addressing have been under discussion
regionally for over eight years. Proponents of extreme positions have been largely
isolated. There is a strong sense of community and a genuine desire to address the issues.
There is a strong tradition of political cooperation so long as alternative resolutions
remain within pre-established bounds and existing authorities remain intact. We have yet
to learn whether our project will explore solutions within these bounds or be thought of
as disregarding them. To an important degree, sensitivity to boundary issues is more
important than sophisticated collaboration techniques.
Conclusions
We have outlined a complex project of research and community involvement that
envisions the collaborative development of urban narratives and dynamic urban
simulation models as an approach to meeting two goals — deepening insights into human
and biophysical processes in urban environments and securing a degree of coherent
metropolitan regional governance through inter-organizational network steering. We rely
on collaborative learning workshops with opinion leaders and decision makers from the
inter-organizational network to better mediate among divergent perspectives on how
urban regions should be planned and managed. We rely on narrative story telling because
narration is the approach humans use to explain and rationalize action in complex social
and political contexts. We observe the frequent use of over-simplified narratives often
leads to ill effect. We think more complete and dynamically complex stories will improve
both process understanding and regional governance. We think reliance upon narratives
will be more efficient than otherwise and that they will serve to integrate systems
theoretic concepts with both the comprehension of urban human and biophysical
processes as well as the adoption of shared terms, language and meanings.
Initially, we employ system dynamics modeling to assist in the collaborative
exposition of a dynamically complex narrative. Later, we iterate between system
dynamics modeling and narrative exposition to explore and enrich the internal structures
of both story and model. Upon completing the workshop series, we circulate the urban
narrative among IO members together with a description of how it was derived, invite
comments, and respond to each. The narrative with comments and responses is
redistributed with a directive that its elements be incorporated into public plans and
project designs — a procedure that resembles an environmental impact review process as
specified by regulations pursuant to the National Environmental Policy Act of 1969.
Our research team brings a history of practical public involvement, mediation
experience, modeling competency, scientific measurement capacity and planning
theoretical insight to the project’s design. The project itself must be regarded as an
experiment. Its outcomes will be known, in part, by the quality of its product and the
ownership participants take in the process. These can and will be assessed. But the
ultimate impacts on our goals for deepened process insights and improved regional
governance will be discerned only slowly through time by the unreliable means of
anecdotal evidence and individual assessment.
Acknowledgement
The authors wish to acknowledge the National Science Foundation Biocomplexity in the
Environment Program (award number ATM 02157658) and the Southwest Center for
Environmental Research and Policy (Border + 20 Project) for its support of this research.
Appendix I —- Urban Narrative
Development Strategies for Utah’s Wasatch Front:
Toward a ‘Win-Win’ Urban Future!
National recessions reveal strengths and weaknesses in regional economies. During
the previous three recessions, the economy of Utah’s Wasatch Front showed remarkable
resilience. Yet during the most recent recession, a new pattern emerged that shows the
area’s recession-based job losses to be concentrated among higher-paying industries. As
a possible precursor, the National Science Board notes that between 1995 and 1999, Utah
lost science and engineering jobs, dropped in patents production and experienced a 26%
decline in the proportion of U.S. patents filed locally.’
We are a people demonstrably concerned about quality growth. Do these changes
suggest that the Wasatch Front may be loosing its ability to create, attract and maintain
quality jobs and quality industries?
Trends in urban system performance suggest that, if this is not now so, it may soon be
so. Consider changes in the urbanized parts of the Salt Lake-Ogden metropolitan area
across the most recent two decades. For every 2 urban dwellers, there are now three — an
increase by one-half. Urban land use and urban roads miles have increased by two-thirds.
Vehicle trips have nearly doubled, and the road gap — the difference between actual and
desire road capacity —is up by a factor of five.*
Breaking the Cycle of Sprawl and Congestion. We have modeled these changes
mathematically with a high degree of accuracy and verified the existence of a self-
reinforcing feedback mechanism that slowly but inexorably impels this region toward
declining developmental densities, increasing road densities, and growing traffic
congestion. These trends portend more extensive atmospheric emission control
technologies, growing public service costs and increasing local taxes.
Yet these same models show that it is possible to avoid this consequences with
policies that constrain sprawl and defeat congestion. Four things must be done in close
concert to succeed. (1) Reduce by one-fifth the proportion of daily trips made alone in
private cars. To meet this objective, use car pools, reliable transit services, light rail,
commuter trains, taxies, road tolls, bike paths, usable walkways and real parking fees. (2)
Increase by one-tenth the traffic capacity of existing roads. Synchronize traffic lights,
control on-street parking, limit left-hand turns and control the timing of freeway on-ramp
entry. Link up local streets,
collector and arterial roads
where’ interrupted by
geography, land use or
jurisdictional boundary. Make
the existing grid street system
truly functional. (3) Increase
developmental densities by 20
percent. On the land where
five new buildings would
Population otherwise be built, build six.
To do this, substitute within
ooae 4990 2000 each square mile one 80-unit
Year garden court project for one
10-acre low-density
subdivision. For greater
proximities, vary densities and mix up land uses. For greater connectivity, articulate
nodal points and corridors where related urban activities are concentrated and easily
linked. For greater efficiency, mix in housing and jobs nearby one another. For greater
equity, intermix single homes, condominiums and garden apartments. This will also
lower trip frequencies, shorten trip lengths and save on municipal infrastructure costs. (4)
Having reduced the sprawl-related propensity to increase trip making, respond more
quickly to the need that remains. Meet the now reduced need for new roads by building in
100
Trips per Year
Urban Land Area
50 :
Road Lane Miles
% Change from 1980
three years what would normally take five. This will reduce traffic congestion due to
road-building response lags.
Our simulations show that implementing these measures over a six-to-eight year
period will slow urban density declines by half and return congestion delays to levels last
seen in the mid-1990s. Our simulations demonstrate that imposing this discipline breaks
the cycle of urban sprawl and traffic congestion.
The Structure of Self-Reinforcement. The needed discipline in urban policy
implementation is increased by an awareness of what the alternative entails. A
continuation of current trajectories portents a baseline urban future where sprawl and
congestion that:
* undercuts the region’s economic and fiscal vi
* exerts an effective drag on the regio ability to attract and retain footloose industries, skilled
professionals and amenity-oriented residents; and
* draws its community and corporate interests along increasingly divergent paths.
lity;
Sprawl and congestion relate to one another as a self-reinforcing feedback loop
articulated through the processes of urban land development and urban road construction.
As is well know, new urban land development generates new trips. New trips congest
existing roads and add to the demand for more roads. New roads induce declines in urban
land developmental densities so that the next round of urban land development generates
even more new trips and adds to the demand for even more roads.* The dynamic is more
readily understood when the individual steps of the process are unpacked.
The population of the Salt Lake -Ogden SMA has been growing at a rate of 1.9% per
year compounded annually over the period 1980 - 2000. This population required an
average of 2.6% more land per
year compounded annually for
homes and workplaces. These
places generated traffic at a rate of
3.3% per year compounded
annually. To ease congestion, we
built roads at the rate of 2.7% per
year compounded annually. Part
of the reason trips grew faster than
roads is because the new roads
facilitated further land
development, always, slowly, at
lower densities than before
resulting in an overall density
decline of 0.7% per year
compounded annually. This is consistent with national empirical studies that suggest a
0.25% decline in developmental densities for every 1% increase in urban road lane
miles.° Model simulations suggest that had developmental densities not declined, traffic
would have grown at the less rapid rate of 2.6% per years compounded annually and
would not have outpaced the rate of road building.
So with every new road lane mile, households and jobs are located a bit further away
from one another. The density of opportunities declines in both city and suburb. People
have drive a bit further to get things done. They use the car a bit more often to make
Total Acres of
Urban Land
Number of Trips per Year
New Acres of Urban Land
Developed per Year
Road Lane Miles Needed
for Uncongested Traffic
Acres of Urban Land
per Building
New Road Lane Miles Needed
vs
Existing Total Road Lane M
Total
Road Lane Miles
needed trips. They need more roads to handle the added traffic along side of which they
build more buildings at still lower densities and travel still further to get to and fro.
A one percent growth in road lane miles encourages a quarter percent decline in
developmental densities and a quarter percent increase in traffic. With the effect of
declining densities added to underlying increases in people and jobs, traffic grows faster
than does overall roadway capacity. Drivers need more travel time to deal with
congestion, more money for proximate housing and reliable transportation, more workers
per household to meet the costs, and for each worker at least one car. So the conclusion
begins to dawn: it makes little sense to build more roads and develop more land without
plans to keep each from requiring more of the other.’
Baseline Scenario. Since Utah County established the state’s first Planning and Zoning
Commission in 1941, the counties and cities of Utah have committed substantial
resources to urban planning. This has helped considerably at the neighborhood and
municipal scales. But the state’s largest urban region has no coordinated land use and
transportation plan that functions at the metropolitan regional scale. It has no plans for
land use that do not presume more roads, none for urban roads that does not presume
more ever-lower density urban land development, none that seeks to limit both sprawl
and congestion, none that creates closely coordinated transportation and land use choices
and promise an end to increasing transportation, housing and environmental costs. As a
result, current trajectories will likely continue into the future.
Here in brief is what our model says current trajectories will be. From 1980 to 2020,
urban population in the Salt Lake-Ogden area increases by 110% - more than doubling in
forty years. Urban land increases by nearly 200%. Urban roads — everything from
highways to local streets - increase by more than 250%. Vehicle-trips increase by more
that 300%. With local traffic circulation made difficult by the design and layout of
residential subdivisions, a growing proportion of vehicular traffic shifts toward highways
and arterials. Sometimes the highways are fast, but they also become increasingly
unreliable as weather, accidents and congestion render then inoperable. Traffic
congestion will get to be five times as bad as in 1980. These trends give raise to thoughts
on related issues of energy consumption and atmospheric emissions.
A Poorly Hedged Bet. Big lots, big cars and big roads play roulette with air quality,
federal highway dollars and urban economic futures. The assimilative capacity of the
region’s urban air shed is nearly used up. The air shed edges on non-compliance with
several federal ambient air quality standards.*
With rapid growth in vehicular traffic, following the current trajectory places a poorly
hedged bet on continued technologic progress in reducing vehicle emissions. Given an
urban air shed at the margin of non-attainment, continued development along current
trends implies a bet that emission rates will decline faster than vehicle use increases.
Continuing along the current path bets that air quality standards will not become more
stringent even as scientists learn more about the health and environmental effects of
atmospheric emissions. And it does so while indirectly encouraging, through ever lower-
density development patterns, the continued growth in vehicular traffic. Any gambler will
tell you that this is a poorly hedged bet.
A poorly hedged bet limits future options. This one entails an expensive commitment
to an air emissions technology fix. Without one, growing vehicular traffic will
overwhelm the region’s air shed.
Unconstrained sprawl and congestion portend other consequences of concern to both
public and private actors. Davis County expects to use up all available land for
development by 2030. In Salt Lake and Weber Counties, little land will be left to develop
that is not remote from employment centers. Those who can only afford residing in
remote locations will see their household transportation costs go up. Others will find
more proximate housing bid up substantially. The less wealthy will be most affected.
Under the current path, the proportion of income needed for housing and transportation
will grow even more rapidly and affect an ever-larger majority of Wasatch Front
families.’
School districts will close more central-city schools, open more suburban schools,
and charge more taxes to get the job done." Suburban municipalities will find it evermore
costly to provide infrastructure and services to increasingly lower-density neighborhoods,
while inner city municipalities will endure the premature obsolescence of existing
infrastructure.
Hoping to capture more revenues and to put off an inevitable property tax rate
increase, municipalities will compete more vigorously with one another to encourage
business relocations to sites near newly built highway interchanges. They'll do so without
acknowledging that both the highway interchange and the relocated businesses will
attract additional residential development which, with low densities and high service
requirements, will fail further to pay their own way. ''
Competition among municipalities will create additional inequities between newer
and older urban areas. Inter-jurisdictional competition will exacerbate municipal fiscal
problems. For most municipalities, it will result in higher local taxes and fees, inefficient
municipal service expenditures and lower public services. The local success of a few
municipalities will undercut the region’s overall ability to maintain quality service and
development throughout.”
Congestion, pollution, health concerns, housing costs, transportation costs, and taxes
— after some time lag, the region’s reputation for providing a high quality of living may
diminish. Skilled professionals, footloose entrepreneurs and amenity-oriented residents
may be reluctant to come. Some of those already here may consider moving elsewhere.
The high quality of the region’s labor pool and its employment opportunities may be
harder to maintain. Business may regard this place as offering an increasingly less
favorable business climate. Households may grow concerned about issues of community
livability. A region that now enjoys an excellent reputation may no longer compare so
well with competing urban regions.
Those concerned about such matters may find themselves in 10 to 15 years cut free
from the good regard of fellow Americans to face the discipline of the outside world.
Jobs would grow more slowly. Unemployment, long below national averages, might
move up to and then above national averages. Out-migration would increase. Population
growth would slow. If so, employment in the construction industry would decline. Real
estate sales would do likewise but even more rapidly. Hard limits would prevail. Budget
discipline would unravel under the pressures of short-term concerns. The region would
establish a new economic equilibrium but at a lower quality of life than otherwise could
have been attained. And no one in particular could be held responsible.
A Harmonization of Interests. These untoward events need not be endured. The
recommended urban policy measures will move this region along a happier path. The
recommended measures are not new. Many organizations have been advocating them for
years. What’s new is the recognition that they must be implemented comprehensively, in
concert and with discipline.
Historically, Americans have sought unsuccessfully through an evermore-fervent
schedule of road building to attain the ever-receding goal of congestion relief. We now
understand and can mathematically demonstrate the futility of this approach. We also
understand and can demonstrate that doing concertedly and unrelentingly what others
have advocated piecemeal will work to contain sprawl and congestion to the benefit of all
with sacrifice from none.
All win-win strategies entail a degree of mutual discipline. We must work within a
framework designed to solicit local cooperation where unconstructive competition has
historically prevailed. This requires a reform of municipal finance and a strengthening of
county and municipal collaboration at the metropolitan regional scale. It requires a
politics of mutuality that mobilizes the will to act regionally. It requires an opening up of
the political agendas and a broadening of the constituencies participating in land use
plans and infrastructure investments. It requires a deepening of ongoing regional
visioning processes. It requires an enduring commitment to plain, honest speaking,
trustworthy behavior, transparent intentions and comprehensible actions. Securing these
objectives will bring not only a better quality of life to the region but also a greater
harmonization of interests across diverse sectors of our urban society.
"This document is under preparation by a committee of academics and community leaders coordinated by
Prof. Philip C. Emmi, Director, Urban Planning Program, College of Architecture and Planning, University
of Utah, Salt Lake City, UT 84112.
? Wood, J. A. 2004. The Utah economy: A review and outlook, Utah Economic and Business Review, 64.
3 National Science Board (2004) Science and Engineering Indicators, 2004. Arlington: National Science
Foundation, National Science Board.
+ Emmi, P. C. and C. B. Forster (2003) Modeling the reciprocal relationship between metropolitan roadway
expansion and urban land development with elementary extensions to environmental consequences. In
Subhro Guhathakurta (ed.) Land Use and Environmental Modeling. Berlin: Springer-Verlag.
* Emmi, P. C. (2003) Coupled human-biologic systems in urban areas: Towards an analytical framework
using dynamic simulation. Proceedings of the 21st International System Dynamics Conference. New York
City, July 20 -24, 2003.
© See James G. Strathman, Kenneth J. Dueker, Thomas Sanchez, Jihong Zhang, and Anne-Elizabeth Riis
(2000) Analysis of Induced Travel in the 1995 NPTS, Portland State University. Center for Urban Studies,
Catalog Number PR113, online at: http://www.upa.pdx.edu/CUS/publications/projectreports.html/
’ William Fulton explores how growth patterns differ across the U.S. from 1982 to 1997. A growing
metropolitan region like Atlanta had its expansion of urban land exceed growth in population by 134%
while its density declined by 11%. Yet Pittsburgh with regional population declines of 8% still grew in
urban land consumption by 43% while declining in densities by 36%. This demonstrates a clear disconnect
between population growth and growth in urban land consumption. Fulton, W. et al. 2001. Who Sprawls
Most? How Growth Patterns Differ Across the U.S. Washington D. C.: Brookings Institute.
* See http://www.airquality.utah.gov/GRAPHICS/MAPS/non_attn.pdf accessed on 07 Oct 2004 for maps
of non-attainment and maintenance areas for several criteria pollutants.
° Between 1980 and 2000, the proportion of household income spent on housing plus transportation has
grown from 3 to 10 percent higher for the three lowest-earning population quintiles: on average, the less
wealthy the household the greater the increase. (Authors’ analysis of consumer expenditure data online at
http://data. bls. gov/labjava/outside. jsp ?surve'
‘0 “With recent increases in property value assessments, one would think that our local jurisdictions would
be awash in property tax revenues. Indeed, revenue growth has been rapid but not sufficient to outpace the
demand for local services. Utah school districts owe $1.16 billion, more than double their debt of 6 years
ago. Nineteen school districts, 16 special districts, 5 water districts, 13 cities and 4 counties sought tax
increases in 1999.” Emmi, P.C. 2000. The fiscal burden of growth: Memo to Salt Lake City Mayor and
City Council Members.
"' For recent reviews on this issue, see Chapter 3 “From Red to Green: Fiscal Impacts of Sprawl” in
Benfield, F. K., Chen, D. D. T. and Raimi, M. D. 1999. Once There Were Greenfields: How Urban Sprawl
is Undermining America’s Environment, Economy and Social Fabric. Washington, D. C.: Natural
Resources Defense Council.
2 See Paul G. Lewis (1996) Shaping Suburbia: How Political Institutions Organize Urban Development
(Pittsburgh: University of Pittsburgh Press) for a discussion of the effects jurisdictional fragmentation and
inter-jurisdictional competition have on urban form and development.
Table 1. Selected Agencies, Organizations and Associations Influencing Decisions
that Affect Atmospheric Emissions, Salt Lake Metropolitan Area, Utah.
Federal Government
¢ EPA Region VIII
* U.S. Army Corps of Engineers
¢ US. Dept. of Transportation
Utah State Government
¢ Department of Environmental Quality:
Division of Air Quality
* Governor’s Science Advisor
* Utah Air Quality Board
* Utah Department of Transport
* Utah Energy Office
¢ Fleet and Physical Plant Operations
* Utah’s Quality Growth Commi:
* Utah Transportation Commission
Salt Lake County Government
¢ Fleet and Physical Plant Operations
¢ Salt Lake County Council
¢ Salt Lake County Council of
Governments
¢ Salt Lake Valley Health Department
Municipal Government
¢ Salt Lake City
co Airport Operations
o City Council
o Environmental Affairs
co Fleet and Physical Plant
Operations
o Planning Department
¢ 14 Other Cities/Towns
* >6 Unincorporated Towns &
Townships
Metropolitan Planning Organizations
* Wasatch Front Regional Council
¢ Utah Transit Authority
Other
* Opinion Leaders (prominent business,
religious, and other community leaders)
¢ County Residents
Key Businesses With Emissions
¢ 2 Oil Refineries
* Kennecott Corporation (Copper Mine)
* Questar Gas
¢ Pacificorp (Electricity Production)
Real Estate Development Services
* Church of Jesus Christ of Latter Day
Saints
* Cowboy Partners
* Kennecott Land Development
Corporation
* Sorenson Development
Public Interest Advocacy organizations
¢ Envision Utah
¢ Friends of Great Salt Lake
¢ National Energy Foundation
* Nature Conservancy, Great Basin
¢ Salt Lake Clean Cities
¢ — Sierra Club, Utah Chapter
¢ Tree Utah
* Utah Clean Energy Association
* Utahns for Better Transportation
* Utahns for Clean Water, Clean Air and
Quality Growth
¢ Utah Industry Environmental Coalition
¢ Wasatch Clean Air Coalition
Industry and Professional Associations
* Utah Association of Realtors
* Utah Home Builders Association
¢ Ski Utah
¢ Utah Trucking Association
* Utah Mining Association
* Utah Manufacturer’s Association
* Utah City Engineers Association
* Utah Petroleum Association
¢ Structural Engineering Assoc of Utah
¢ — Intermountain Utility Contractors
¢ Intermountain Contractor
e ATA/APA, Utah Chapters
UO
NARRATIVE 2 NARRATIVE 3
This is the This is
|story about the st pou
[co, emissions
from an urban
‘ecosystem. ecosystem. ‘ecosystem.
MODEL 1 MODEL 2 MODEL 3 MODEL 4
0° | |\o°%O
Ooo 00
(e)
OL] Model Revisi
Figure 1. Flowchart for narrative/model revision during workshops.
References
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Guhathakurta S (ed). Springer-Verlag: Amsterdam:.
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' This draft document is under preparation by a committee of academics and community leaders
coordinated by Prof. Philip C. Emmi, Director, Urban Planning Program, College of Architecture and
Planning, University of Utah, Salt Lake City, UT 84112. This draft was last updated on 08 OCT 2004.
? Wood, J. A. 2004, The Utah economy: A review and outlook, Utah Economic and Business Review, 64.
3 National Science Board (2004) Science and Engineering Indicators, 2004. Arlington: National Science
Foundation, National Science Board.
* Emmi, P. C. and C. B. Forster (2003) Modeling the reciprocal relationship between metropolitan roadway
expansion and urban land development with elementary extensions to environmental consequences. In
Subhro Guhathakurta (ed.) Land Use and Environmental Modeling. Berlin: Springer-Verlag.
* Emmi, P. C. (2003) Coupled human-biologic systems in urban areas: Towards an analytical framework
using dynamic simulation. Proceedings of the 21st International System Dynamics Conference. New York
City, July 20 -24, 2003.
© See James G. Strathman, Kenneth J. Dueker, Thomas Sanchez, Jihong Zhang, and Anne-Elizabeth Riis
(2000) Analysis of Induced Travel in the 1995 NPTS, Portland State University. Center for Urban Studies,
Catalog Number PR113, online at: http://www.upa.pdx.edu/CUS/publications/projectreports.html/
’ William Fulton explores how growth patterns differ across the U.S. from 1982 to 1997. A growing
metropolitan region like Atlanta had its expansion of urban land exceed growth in population by 134%
while its density declined by 11%. Yet Pittsburgh with regional population declines of 8% still grew in
urban land consumption by 43% while declining in densities by 36%. This demonstrates a clear disconnect
between population growth and growth in urban land consumption. Fulton, W. et al. 2001. Who Sprawls
Most? How Growth Patterns Differ Across the U.S. Washington D. C.: Brookings Institute.
® See http://www.airquality.utah.gov/GRAPHICS/MAPS/non_attn.pdf accessed on 07 Oct 2004 for maps
of non-attainment and maintenance a1 for several criteria pollutants.
° Between 1980 and 2000, the proportion of household income spent on housing plus transportation has
grown from 3 to 10 percent higher for the three lowest-earning population quintiles: on average, the less
wealthy the household the greater the increase. (Authors’ analysis of consumer expenditure data online at
http://data.bls. gov/labjava/outside. jsp?survey=cx).
'° “With recent increases in property value assessments, one would think that our local jurisdictions would
be awash in property tax revenues. Indeed, revenue growth has been rapid but not sufficient to outpace the
demand for local services. Utah school districts owe $1.16 billion, more than double their debt of 6 years
ago. Nineteen school districts, 16 special districts, 5 water districts, 13 cities and 4 counties sought tax
increases in 1999.” Emmi, P.C. 2000. The fiscal burden of growth: Memo to Salt Lake City Mayor and
City Council Members.
"' For recent reviews on this issue, see Chapter 3 “From Red to Green: Fiscal Impacts of Sprawl” in
Benfield, F. K., Chen, D. D. T. and Raimi, M. D. 1999. Once There Were Greenfields: How Urban Sprawl
is Undermining America’s Environment, Economy and Social Fabric. Washington, D. C.: Natural
Resources Defense Council.
2 See Paul G. Lewis (1996) Shaping Suburbia: How Political Institutions Organize Urban Development
(Pittsburgh: University of Pittsburgh Press) for a discussion of the effects jurisdictional fragmentation and
inter-jurisdictional competition have on urban form and development.
to tl
