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Edited by John R. Bryson, Lauren Andres and Rachel Mulhall
Marina van Geenhuizen, J. Adam Holbrook and Mozhdeh Taheri
This chapter presents the theme, theoretical approaches and overview of the chapters in the book. The theme is the contribution of cities (their actors) to increased sustainability in social-technical systems, eventually by accelerating sustainability improvements. The selected systems are energy, transport and healthcare. Cities may act as the cradle of key inventions, as places of up-scaling and commercialization and as places of quick adoption, though few individual cities take up all these roles. Next, several urban innovation theories are introduced, including agglomeration and cluster theories, and the relational (collaboration) approach, with the aim to ‘position’ the chapters. Specific attention is given to the entrepreneurial ecosystem approach. Complementary approaches are institutional and governance perspectives, in particular with respect to cities acting as institutional innovators. A final approach is the evolutionary approach, as invention, up-scaling, commercialization and adoption of new technology are concerned with long time-lines and manifold uncertainties.
Architecture and Urban Competitiveness
Peter K. Kresl and Daniele Ietri
Evaluating Public–Private Partnerships and Other Procurement Options
Darrin Grimsey and Mervyn K. Lewis
This introductory chapter begins by considering the infrastructure challenge posed by what former US Treasury Secretary Larry Summers calls the ‘Age of Secular Stagnation’ and International Monetary Fund managing director Christine Lagarde terms the ‘new mediocre of growth’. Both advocate increased infrastructure spending as the solution, but there are considerable differences between infrastructure policies in three of the largest economies. After decades of neglect, the United States and even Germany are saddled with once advanced, but increasingly outmoded infrastructure assets, while China keeps on building and has become an exemplar of modern urban transit, with ports, expressways, railways, subways, airports, and by far the world’s largest high-speed rail network. Nevertheless, a 2016 Oxford study challenges the efficacy of China’s infrastructure-led growth strategy. Upon examination, however, their study has serious defects and, contrary to their arguments, China’s infrastructure megaprojects appear less wasteful than those authors claim, and they have laid the foundations for Chinese growth, supported by a later case study.
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.