The urban networks discussed in this volume, and that appear in the literature more broadly, are characterized by significant diversity. This is perhaps not a surprise as the study of urban networks is necessarily interdisciplinary, drawing on theoretical foundations from geography, economics, psychology and sociology, and on methodological tools including ethnographic and qualitative methods from sociology, and quantitative methods from mathematics and physics. However, although the flexibility of network models to capture a wide range of urban phenomena is a key strength of the approach and a source of intellectual diversity, it can also be a source of confusion. Different fields and different research questions require studying different types of urban networks, often defined in very different ways, which obscures their commonalities. In this introductory chapter, we sketch a framework for integrating the diversity of urban networks by situating them along the dimensions of level and scale. These two dimensions define, respectively, the aggregation and spatial scope of the nodes, and therefore provide critical parameters for defining an urban network. In some instances, a network’s level and scale are defined implicitly by the research question, but we contend there is still value in being explicit about level and scale. Similarly, although a great deal of past research on urban networks has explored only specific intersections of level and scale (for example, networks of people at the local scale, or networks of cities at the global scale), we contend that exploring urban networks with different combinations of levels and scales offers opportunities for new insights that the reader will find in this volume. We begin by describing the level/scale framework in general, then discuss the case of economic urban networks as an extended example, and use the framework to explore commonalities among the diverse urban networks in this volume. We conclude by discussing ways that levels and scales can be made more explicit in urban networks, and the potential benefits for studying urban networks at multiple levels and scales.
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Roberta Capello and Peter Nijkamp
The space-economy has never been static, but has always shown a state of flux. Regions are normally in transition; they are work in progress. As a consequence, we observe a complex evolution of regional systems that varies between growth and decline. Static location and allocation theories may be helpful in understanding underlying structures in regional economies, but do not offer a full-scale picture of the development of multi-actor processes and of the perpetual or temporal impediments for regional growth and prosperity. The conceptualization and solid explanation of regional growth, and differences therein, is still largely a mystery for the research community in many countries. There is no uniform panacea for enhancing or accelerating the development trajectory of regions in a national or supranational economy. Therefore, regional policy is still in many cases a black box; the outcomes of intensified regional growth strategies are often largely unpredictable. Best guesses are more common than testable and operational estimates of policy impacts. Against the above-mentioned backgrounds, the editors of the Handbook of Regional Growth and Development Theories published a decade ago a comprehensive volume with a rich collection of advanced contributions on the above challenges in regional economics and regional science. In the ten years since then the world, both the empirical regional world and the theoretical and empirical reflection on growth and development issues, has not come to a standstill. We have become sadder and wiser after economic crises, regional fragmentation trends, the introduction of radical technological innovation, and the awareness of failures of regional policy. However, we have also enriched our knowledge horizon, with new insights and new methods and theories of regional analysis. The time has now come to take a refreshing and new look at the achievements of regional growth and development theories.
Edited by John R. Bryson, Lauren Andres and Rachel Mulhall
Lasse Gerrits and Stefan Verweij
We argue that infrastructure projects are complex and that evaluations of such projects need to do justice to that complexity. The three principal aspects discussed here are heterogeneity, uniqueness, and context. Evaluations that are serious about incorporating the complexity of projects need to address these aspects. Often, evaluations rely on single case studies. Such studies are useful because they allow researchers to focus on the heterogeneous, unique, and contextual nature of projects. However, their relevance for explaining other (future) projects is limited. Larger-n studies allow for the comparison of cases, but they come with the important downside that their relevance for explaining single projects is limited because they cannot incorporate heterogeneity, uniqueness, and context sufficiently. The method Qualitative Comparative Analysis (QCA) presents a promising solution to this conundrum. This book offers a guide to using QCA when evaluating infrastructure projects.
Åke E. Andersson and David Emanuel Andersson
Åke E. Andersson and David Emanuel Andersson
The games of markets including entrepreneur-driven economic development have always taken place on an arena of the combined material and non-material infrastructure. The infrastructure thus constitutes the arena; it is public capital that facilitates and constrains the rapid “games” of buying and selling that economic agents play. Agents perceive the arena as stable because its evolution is so much slower than that of markets for goods and services. Synergetic theory is well equipped to handle such multiple timescales. Its application to economic phenomena enables us to show that competitive equilibrium theory requires prior specification of the infrastructural arena, which consists of public knowledge, space-bridging networks and institutions. Synergetic theory can also help us avoid the pitfalls of conventional macroeconomic theory. In this chapter, we demonstrate how macroeconomic equilibrium depends on the infrastructure. We claim that all goods are durable and are thus instances of capital. This means that historical trajectories, current outcomes, uncertain expectations and changes in spatial accessibility all influence the growth and fluctuations in the value of capital goods. Dynamic non-linear interactions between scientists, inventors and entrepreneurs affect investments. New technological or design ideas spread most easily among spatially proximate firms within communication and transport networks. Such network effects shape processes of spatial clustering, agglomeration and urbanization. Based on causal and various econometric considerations, it has been common for economists to resort to difference equation in their modeling strategies. But if we include dynamic interactions within a system of difference equations—so as to accommodate realistic causal assumptions—it will often result in complex models with chaotic outcomes. However, there are ways out of chaos in economic modeling. The first is to focus on continuous dynamic synergetic models, which implies a careful separation of variables and dynamic processes according to their relevant timescales as well as the collectiveness of their impacts.