Doing comparative case study research in urban and regional studies: what can be learnt from practice?

Figures & data

Table 1. Different epistemological starting points to theorizing in comparative case study research.

‘Traditionally’	‘Recently’
• Conceptualizing the constitution and development of a place as subject to universalized laws	• Space-specific emergence and reproduction of a place; non-linear development trajectories
• Rather fixed theorization of space and scale	• Place is theorized as interconnected; attention to constitutive processes and practices
• ‘Measuring’ of findings against a-priori defined variables; the case as a variation	• A commitment to seeing difference; working with repetition • Including diverse urban experiences across the global North-South divide
• Expectation to draw generalizable findings	• Not necessarily generalizing from the cases/different degrees of generalization
• Affinity to variable-centred comparative case study research	• Affinity to (constitutive) process-centred comparative case study research

Source: own elaboration.

Table 2. Final set of documents used to find answers how to do good comparative research.

Project acronym (time span) funding project ID (‘grant number’)	Topic/research interest of the project	Analysed number of documents pr. source (date of document extraction: MM/DD/YY)
		Web of Science (11/26/18)	Scopus (11/21/18)	Google Scholar (11/21/18)	OpenAIRE (11/26/18)	Further sources
PROFIT (2004–2007) EU FP6^a 506245	Overcoming the inter­generational transmission of inequalities	0	0	11	0	1
ACRE (2006–2010) EU FP6 028270	Creating or stimulating ‘creative knowledge regions’ in the EU	0	0	9	0	0
SHRINK SMART (2009–2012) EU FP7^b 225193	Social cohesion and the governance of urban shrinkage	0	5	24	0	2
COPE (2012–2015) EU FP7 290488	Minimum income pro­tection policies that help to alleviate the risk of poverty	1	6	14	4	0
IMPROVE (2012–2016) EU FP7 290613	Social cohesion, social policy and social innovation	9	3	34	35	3
CITISPYCE (2013–2015) EU FP7 320359	Combating inequalities through innovative social practices of and for young people in cities	0	0	7	0	1
DIVERCITIES (2013–2017) EU FP7 319970	Increasing the (perception of) positive effects of urban diversity	5	2	11	16	3

Source: own, based on the data sources as provided in the table.

^aEU FP6 – European Commission – Research: The Sixth Framework Programme (2002–2006).

^bEU FP7 – European Commission – Research: The Seventh Framework Programme (2007–2013).

Table 3. The theoretical framework for comparing.

Project	Positioning towards comparative methodology and generalization aspirations
PROFIT	• Statement on project’s methodology and its aspirations to generalize: explicitly excluding a claim to generalize on the basis of cases (Warzywoda-Kruszyńska et al., 2007, p. 12) • Affinity towards a theory-testing/hypothesis-testing approach (Warzywoda-Kruszyńska et al., 2007, p. 22)
ACRE	• Hypotheses-building and empirical testing (Kovács, Murie, Musterd, Gritsai, & Pethe, 2007, p. 14; Musterd & Gritsai, 2010, Section 2) • No explicit statement on comparative case study approach, but encompassing description, e.g. in Musterd and Gritsai (2010, Section 5)
SHRINK SMART	• Developing working models and empirical testing (model provided in Haase et al., 2016) • Shift over the course of the project towards process-orientated, context-sensitive research (Bernt et al., 2014; Haase et al., 2016, p. 99) • Explicit statement on comparative case study approach utilizing the model developed in Haase et al. (2016) (Cortese, Haase, Grossmann, & Ticha, 2014, p. 2054; Haase, Rink, Grossmann, Bernt, & Mykhnenko 2014, p. 1521)
COPE	• Research questions guided by theory (Jessoula, Sabato, Agostini, & Madama, 2014, p. 34) • Causal Process Tracing (Jessoula et al., 2014, p. 61) • Information on means of comparison, associated challenges and guidelines for field work (e.g. Angelin, Johansson, & Koch, 2014; Jessoula, 2015, p. 497; Kozek & Kubisa, 2014, pp. 78–79)
IMPROVE	• Explicit reference to variation-finding, hypothesis-testing in the beginning, changing to ‘individualising comparing strategy’ (Oosterlynck et al., 2016, pp. 4–5) • Contextualized, ‘contingent’ insights within the case study research (Sabato & Verschraegen, 2016, p. 9) • Extensive discussion of the project’s positioning and comparative approach (Oosterlynck et al., 2016)
CITISPYCE	• Contextualized insights; ‘triangulation approach’ (Jubany & Güell, n.d. (2016), p. 49) • Finding commonalities and differences based on qualitative analysis of case study reports (Hussain & Higson, 2014) • Comparing along analytical categories and research dimensions • Explicit reference to action-research approach and qualitative framework of analysis (Jubany & Güell, n.d. (2016))
DIVERCITIES	• Contextualized, ‘contingent’ and not necessarily generalizable insights (Tasan-Kok et al., 2013, pp. 21, 63) • Research questions guided by theory (Tasan-Kok et al., 2013, p. 61ff.) • Explicit reference to relational perspective on cities and neighbourhoods (Bolt, 2017, p. 6; Tasan-Kok et al., 2013, p. 61ff.) • No explicit statement on comparative case study approach found

Table 4. The practice of choosing cases.

Project	Cases	Case study selection
PROFIT	8 medium-sized towns	• ‘deliberately selected towns’, as data basis too limited for controlled choice • Mix of similarity (basic city characteristics, disadvantaged cities) and difference (social welfare systems; social policies; East-West) (all information based on Warzywoda-Kruszyńska et al., 2007, pp. 5, 12)
ACRE	13 city regions	• Thematically chosen (creative knowledge regions) for hypotheses testing • Familiarity seems to play a role (cases are often equivalent to the location of academic project partners) (Musterd & Gritsai, 2010) • Mix of similarity (second range global cities or below) and difference (geographical and structural variety across Europe) (Musterd & Gritsai, 2010, p. 23)
SHRINK SMART	7 urban regions	• Thematically chosen (shrinking/shrunk cities), although acknowledgement of some pragmatism in the choice of cases • Mix of similarity (shrinking/shrunk cities) and difference (geographical variety across Europe; both cities having experienced long-term shrinkage and rapidly shrinking cities) (all information based on Bernt et al., 2014, p. 1753; Haase et al., 2016, p. 91)
COPE	5 post-industrialist cities	• Thematic choice (precisely, cities which implement or adopt national active inclusion policy) • Establishing common criteria and let national partners make the actual choice of the case study • Selection criteria to also ensure variation in terms of (welfare) policy regimes and relationship to Europe (Jessoula, 2015, p. 492; Johansson et al., 2013, p. 17)
IMPROVE	31 social initiatives in 8 countries	• Choosing thematically ‘interesting’ cases in accordance with a clear-cut theoretical background (Kazepov et al., 2013; Sabato & Verschraegen, 2016) • Cases partly selected from a call that the researchers sent to many different civil society actors • Ensuring variation in terms of geographical and structural context
CITISPYCE	2 neighbourhoods in each of 10 selected cities	• Two-stage process for city selection, in which familiarity and active engagement of cities played a role (some of these cities are consortium partners themselves) (‘Citispyce Repository of Case Studies’, n.d.; Robinson, n.d. (2016), p. 2) • Mix of similarity (focus on young people in disadvantaged neighbourhoods) and difference (geographical and structural context)
DIVERCITIES	13 European cities, including 10 policy initiatives in each city	• Familiarity seems to play a role (cases are often equivalent to the location of project partners) (Maloutas & Souliotis, 2015) • Selection of policy initiatives within selected case study area following comparable criteria (see e.g. Barberis, Grossmann, Kullmann, Skovgaard Nielsen, & Hedegaard Winther, 2019, pp. 965, 969 for details) • Mix of similarity (larger cities, deprived, diverse and dynamic research areas) and difference (geographical/structural context of research areas; themes and nature of policy initiatives) (Barberis et al., 2019)

Table 5. Dealing with empirical challenges.

Project	Reflective statements on/discussion of empirical challenges and other issues
PROFIT	• Problems in comparability of data • Preferring depth to scope
ACRE	• Limits in the generalisability of findings (Musterd & Gritsai, 2010, p. 32) • Admission that interview-based quantified indicators may be subjective (Musterd & Gritsai, 2010, p. 42)
SHRINK SMART	• Learning processes in the project’s conceptual approach to comparing (Bernt et al., 2014, p. 1753)
COPE	• Data collection challenges regarding their comparability and functional equivalence, respectively (Johansson et al., 2013, p. 19) • Statements on terminology, terminological and conceptual differences across disciplines to establish a common ground for the project (Hvinden & Halvorsen, 2012)
IMPROVE	• Challenges linked to a mixed-method approach: issue of timing and synchronization of different work (Kazepov et al., 2013, p. 43) • Learning processes in the project's conceptual approach to comparing and justification on the adaptation of the project’s strategy (Oosterlynck et al., 2016, p. 5)
CITISPYCE	• Adaptations in guidelines for empirical work (Hussain & Higson, 2014, p. 4)
DIVERCITIES	• No explicit statements found

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