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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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Maria Estela Ferreira

This chapter aims to illustrate the main outcomes and the characteristics and factors of the resilience of the footwear industry in the northern region of Portugal as performed in the last 30 years. This industry acts in a cluster located in a number of towns around Porto, within a maximum distance of 50 km from this city. Such cluster is responsible for more than 90 per cent of Portuguese footwear exports. Along the analyzed period, and among other difficulties, two main shocks are identified which the industry had to face: the full membership of China in the WTO, in 2001, which carried the delocalization of most foreign footwear companies, mainly to the Far East, and the sub-prime world crisis in 2008. The industry survived and surpassed these shocks thanks to a thorough preparedness sustained by the action of entrepreneurs, together with a strong and active association and a technological center, which provided management and technical support and strengthened links between them, stimulating coordinated actions. This chapter suggests, through a non-linear approach, that Portuguese footwear exports are about to reach the level they would have attained if China hadn’t joined the WTO.

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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.

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Patrizio Bianchi and Sandrine Labory

Chapter 6 concludes the book by summarising the main ideas and pointing to the main issues that should be further examined in this era of digital globalisation spurred by the fourth industrial revolution. One issue is the generalisation of the specific case of comprehensive industrial policy as that implemented in the Emilia-Romagna region. Another issue regards privacy and monopoly power in the new industrial system.

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Patrizio Bianchi and Sandrine Labory

Chapter 5 puts together the analysis carried out in previous chapters to discuss the industrial policy implications of the fourth industrial revolution. The main idea is that manufacturing revolutions call for comprehensive industrial policy. A focus is made on industrial policy at the regional level, and it is shown, through the experience of the Emilia-Romagna region in Italy, that regions have a role to play in designing and implementing comprehensive industrial policies effective in preparing their industries and population for the industrial revolution. It is argued that in times of important change the objective of industrial policy should be resilience, namely the capacity of the economy and the society to adapt.

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Tüzin Baycan and Berna Sezen Özen

This chapter focuses on to what extend the innovation performance of EU countries has been affected by the global economic crisis and aims to investigate the relationship between the crisis and innovation performance while addressing the changes in the indicators of the Innovation Union Scoreboard Index after 2008. Focusing on these changes over the last ten years, the chapter compares and evaluates the innovation performance of EU countries and highlights which countries were more resilient in dealing with the recession.

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Yannis Psycharis, Dimitris Kallioras and Panagiotis Pantazis

This chapter sets out to provide empirical evidence regarding the impact of economic crisis on the employment changes in the NUTS III Greek regions, during the period 2008_2012. With the application of trade-adjusted shift-share analysis, the chapter provides additional explanatory evidence on whether openness and trade have affected the resilience of regions. Results indicate that economic crisis has impacted asymmetrically on regional employment losses, leading to a widening of regional employment disparities. Construction and manufacturing have been hit severely by the crisis. Agriculture constitutes a resilient sector, while knowledge- and technology-intensive sectors are also more resilient to crisis. The less well-off regions dependent on more traditional sectors proved to be more resilient. However, trade relations and openness are offering as stabilizers to economic downturn.

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The Evaluation of Complex Infrastructure Projects

A Guide to Qualitative Comparative Analysis

Lasse Gerrits and Stefan Verweij

Infrastructure projects are notoriously hard to manage so it is important that society learns from the successes and mistakes made over time. However, most evaluation methods run into a conundrum: either they cover a large number of projects but have little to say about their details, or they focus on detailed single-case studies with little in terms of applicability elsewhere. This book presents Qualitative Comparative Analysis (QCA) as an alternative evaluation method that solves the conundrum to enhance learning.