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2017 | OriginalPaper | Buchkapitel

17. Transportation Planning and the Urban Economy

verfasst von : John R. Miron

Erschienen in: The Organization of Cities

Verlag: Springer International Publishing

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Abstract

In this chapter, I introduce transportation costs into the model from Chap. 15. My purpose here is to lay out a way of thinking about municipal land use planning that allows us to understand how it might organize a city. The model in this chapter then shows us how a planner might alternatively address the organization of a city to take into account issues of sprawl. The model introduces transportation costs formulated as quadratic programming problem wherein the benefits of land use complementarity can be directly assessed and shadow prices (Lagrangeans) can be interpreted. I draw an important conclusion from this analysis. The planned organization of a city under this model can look quite different from the planned organization under the design standards of Chap. 16. Put differently, if planners expect design standards to get at issues of sprawl and congestion, they will be disappointed. The significance of this argument is that it refocuses urban development policy away from land use and toward the notion of prices and marginal cost.

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Fußnoten
1
Mitchell and Rapkin (1954) is an early reference to the idea traffic is “generated” by land use. In their view, “land use” simply describes a spatial cluster of similar establishments (e.g., firms, other organizations, and households) and these establishments have predictable interactions with other establishments that generate traffic.
 
2
At the time, Kenneth K. Schlager was Chief Systems Engineer for the Southeastern Wisconsin Regional Planning Commission and taught at Marquette University and the University of Wisconsin in management science and systems analysis. He had Master's degrees from the University of Wisconsin in electrical engineering and from M.I.T. in industrial management. Of the Faves listed in Chap. 2, he is perhaps closest intellectually to Jay Wright Forrester.
 
3
See, for example, Francis and White (1974), Kusiak and Heragu (1987), Meller and Gau (1996), and Loiola et al. (2007).
 
4
Repeated application of a mathematical or computational procedure (algorithm) to obtain successively better approximations to the solution of a problem.
 
5
Computing that solves by trial and error or by rules that are only loosely defined.
 
6
In most cases, transportation involves a vehicle and guideway. Here, I ignore how people and goods get assigned to vehicles.
 
7
Suppose instead that transportation flows were sensitive to price. As a result, the flow between two land uses would drop as it became more costly to ship. As a logical extreme here, imagine two zones so far apart as to make any shipment prohibitive. Were all shipments to be prohibitively expensive, there would be no transportation flows and the problem would revert to Chap. 15. What is missing here is an accounting of the state of well being of firms and/or households in this city.
 
8
Notably, I implicitly assume here that trip cost does not depend on speed. Usually, transportation markets include some competitors who supply transportation services that are faster but more costly. Customers then choose among providers based on the importance of trip time as opposed to trip cost. Of course, there may also be other considerations in the mind of the customers: e.g., safety, convenience, and comfort. In the model in this chapter, I ignore such considerations.
 
9
Near-vertical demand curve; demand varies only weakly with price.
 
Metadaten
Titel
Transportation Planning and the Urban Economy
verfasst von
John R. Miron
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-50100-0_17