Applied Evolutionary Economics and Economic Geography

Applied Evolutionary Economics and Economic Geography

Edited by Koen Frenken

Applied Evolutionary Economics and Economic Geography aims to further advance empirical methodologies in evolutionary economics, with a special emphasis on geography and firm location. It does so by bringing together a select group of leading scholars including economists, geographers and sociologists, all of whom share an interest in explaining the uneven distribution of economic activities in space and the historical processes that have produced these patterns.

Chapter 13: Evolutionary Urban Transportation Planning? An Exploration

Luca Bertolini

Subjects: economics and finance, economics of innovation, evolutionary economics, geography, economic geography, innovation and technology, economics of innovation


Luca Bertolini 1. INTRODUCTION For urban transportation planners these are challenging times. On the one hand, and in spite of all the hype about dematerialization of society, physical mobility systems appear ever more crucial in granting individuals and organizations the access to the spatially and temporally disjointed resources they need to thrive or even just to survive. On the other, because of a heterogeneous mix of mounting financial and fiscal constraints to infrastructure expansion, and growing awareness of and social resistance to the negative impacts of mobility, the traditional ‘predict and provide’ approach to planning is no longer an option. Practical concerns are echoed by more fundamental critiques (see, for instance, Dimitriou, 1992; Gifford, 2003). Central to this more fundamental criticism is the contention that conventional planning methods do not adequately account for the irreducible uncertainty of developments affecting transport and its relationship with the broader context. Uncertainty is, of course, inherent to any future-oriented activity. There are, however, different forms of uncertainty. As discussed by Van der Heijden (1996), a first form of uncertainty is risk, where there is enough historical precedent in terms of similar events to allow the estimation of probabilities for various outcomes (this is the core realm of forecasting); structural uncertainties are a second form, where the event, while still conceivable in terms of chains of cause and effect, is unique enough not to provide any indication of likelihood (think of the complex interplay of rising wealth, social emancipation, mass motorization...

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