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David Kaufmann

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Varieties of Capital Cities

The Competitiveness Challenge for Secondary Capitals

David Kaufmann

The political and symbolic centrality of capital cities has been challenged by increasing economic globalization. This is especially true of secondary capital cities; capital cities which, while being the seat of national political power, are not the primary economic city of their nation state. David Kaufmann examines the unique challenges that these cities face entering globalised, inter-urban competition while not possessing a competitive political economy.
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Sander Faber and Marina van Geenhuizen

This chapter investigates adoption of medical technology in the form of eHealth solutions in hospitals. A model of organizational eHealth adoption is developed and empirically explored using a survey among hospitals in cities in the Netherlands and structural equation modelling (SEM). Technology adoption is seen as a process in different stages, revealing a high level of interest (about 60 per cent of hospitals) but very limited actual adoption (ranging from 6 per cent to 23 per cent). Furthermore, adoption levels tend to be higher in larger cities, and this is confirmed by significant direct influence of urban size on eHealth adoption. Other important factors tend to be organizational readiness and top management of hospitals, but these are not affected by urban size. The results leave the question open as to what makes hospitals in large cities more often adopt new technology if this is not mediated by hospital size and other organizational characteristics.

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Lasse Gerrits and Stefan Verweij

We explain and demonstrate how the selected cases have to be prepared for the actual comparison. This involves a serious effort with regard to the interpretation of the case materials. In QCA, this process of interpreting data is guided by calibration, where raw (qualitative) case data are transformed into quantitative values. Calibration is important because it systematizes interpretation and makes it transparent. There are three principle types of calibration in QCA: crisp-set QCA, fuzzy-set QCA, and multi-value QCA. We explain and demonstrate the different types of calibration using real examples. We also discuss good practices that will help the researcher in making sound decisions when calibrating. The calibration results in a calibrated data matrix, which forms the input for the formal comparison in QCA. Having completed this chapter, the researcher will be able to start the comparison.

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Lasse Gerrits and Stefan Verweij

We explain why it is important to research specific cases and how exactly cases are to be understood and studied using QCA. Cases allow the researcher to account for the heterogeneity, uniqueness, and contextuality of projects. Whereas the term ‘case’ is often used indiscriminately, in QCA it is a clearly defined and important building block. In QCA, cases are conceptualized as configurations of conditions. This configurational nature highlights the complexity of the case. Cases can be researched in two principal ways: case-driven and theory-driven. The case-driven route is decidedly grounded in empirical material, with the boundaries and aspects of cases being constructed during the empirical research process. In the more theory-driven route, the boundaries and aspects of cases are defined by prior theories. Both routes constitute dialogues between data and theory. The chapter explains the concrete research steps involved in both routes.

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Hans Jeekel

This chapter investigates innovation in urban passenger transport and clarifies how cities play a leading role. By focusing on liveability, intelligent systems management and new mobility, single innovations are discussed and the results summarized in a matrix. The most important ‘initiators’ are city governments, citizen groups, public transport authorities and universities, with the enterprise world somewhat lagging until recently. On the physical side, larger cities create more inventions and high density plays a role in feasibility of public transport. Universities are important, as is a historical city centre. On the social side, a well-educated population wishing to continue living in the city enhances innovation, but in some developing countries the electorate which does not own cars appears to be important. Also helpful are city governments acting on openness and trust and active political leaders. Furthermore, the early adopting cities often faced a crisis in mobility or failure of projects.

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Pieter E. Stek

This chapter presents a bibliometric study identifying clusters (cities) that are ‘champions’ in acceleration of invention in solar photovoltaics (PV), using patent analysis. The number of inventions has increased rapidly in the past decades, particularly since 2003. In this process, leading clusters change, in part, over time. Some have held their position since 2000 – Tokyo, Osaka, Seoul and Taipei in East Asia, and San Jose in the US – whereas most high-performing clusters in the US have somewhat lost their position, for example Los Angeles. Over time, there is an increased spread of inventive performance in PV technology across the world. To improve understanding of these patterns, a regression model has been estimated. Using data from 110 clusters, it appears that agglomeration factors and relational factors are equally influential, and they also tend to reinforce each other. Leadership tends to follow from a delicate balance between the size of the cluster and size/diversity of its networks.

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Cities and Sustainable Technology Transitions

Leadership, Innovation and Adoption

Edited by Marina van Geenhuizen, J. Adam Holbrook and Mozhdeh Taheri

This enlightening book elucidates the leadership challenges of various cities in emerging transitions towards higher levels of sustainability. It examines elements of three socio-technical systems, energy, transport and healthcare, while addressing technology invention, commercialization, mass-production and adoption. The book breaks new ground in the analysis of topical issues such as local ‘cradle’ conditions, incentive schemes, niche-development, living labs, impact bonds, grass-roots intermediation and adaptive policy making. It offers a broad coverage of global systems of cities, with a particular focus on Scandinavia, Germany, the Netherlands, China, Korea, Japan, the US and Canada.
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Lasse Gerrits and Stefan Verweij

We explain and demonstrate how the researcher can identify recurring patterns across cases on the basis of the calibrated data matrix, in a systematic and transparent way. The comparative process in QCA consists of three main steps. First, the calibrated data matrix needs to be transformed into a truth table. In the truth table, the cases are sorted across the logically possible configurations of conditions. Second, the truth table has to be minimized. This is done through the pairwise comparison of truth table rows that are considered to agree on the outcome and differ in their score in but one of the conditions. The result of the minimization is a solution formula. Third, the solution formula needs to be interpreted. Two common issues in the truth table minimization are limited diversity and logical contradictions. We present various strategies for dealing with these issues.

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Lasse Gerrits and Stefan Verweij

In this concluding chapter, some of the main issues concerning the evaluation of complex infrastructure projects with QCA are revisited. First, QCA’s capacity to truly capture and study the complexity of the development of infrastructure projects is discussed. QCA’s take on complex causality is relatively static because it does not explicitly integrate the time dimension. Various strategies to integrate time in QCA are discussed, including Temporal QCA (TQCA) and Time-Series QCA (TS/QCA). The different strategies have their strengths and weaknesses and they relate to different research steps (i.e., the case, the calibration, and the comparison) involved in QCA. Second, the deployment of QCA in real-world evaluations and various issues evaluators may run into are discussed. These issues include learning and political accountability, the presentation and visualization of results, and the transfer of lessons learned.