Social enterprises in the EU (IVOR nr. 111) 2018/3.6.2:3.6.2 Methodology

Social enterprises in the EU (IVOR nr. 111) 2018/3.6.2

3.6.2 Methodology

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In the meta-synthesis, the case study findings were collected, analysed, compared, and synthesised. In principle, the meta-synthesis sought to generate cross- case comparisons, causal explanations, and holistic conclusions.1 It was designed and developed following specific methodological steps:2

(i)

Collecting, summarising, and coding the findings of the case studies

The case study findings were the basis, i.e. the input to be analysed and investigated. However, due to the gross limitations in the developed research and results of Case Study 9, this case study was only partially considered in the cross-case analysis, whereas it was not considered at all in the synthesis of results.

The replication logic in the development of the case studies provided a high level of heterogeneity in the data under investigation in the meta-synthesis, e.g. all cases examined the implementation of participatory governance by means of a replicated method and under the same theoretical and conceptual framework. Accordingly, the sections ‘Case study results’ and ‘Discussion’ in the case studies comprised the findings, i.e. ‘the data’ used for the comparison and cross-case analysis in the meta-synthesis. These data were collected, summarised, and coded with codes relating to the roles of participation of stakeholders, e.g. ‘stakeholders as owners and members’, ‘stakeholders as decision-makers’, ‘stakeholders as controllers and supervisors’, ‘stakeholders as recipients of information’, or ‘stakeholders as consultants’.

The case study findings were also coded in relation to the identified stakeholder participatory mechanisms, with codes such as ‘formal participation’ and/or ‘formal stakeholder mechanisms’, or ‘informal participation’ and/or ‘informal stakeholder mechanisms’. The coding regarding the identified stakeholder participatory mechanisms was also supported by an analysis of the (x) data matrices provided in each case study. On an aggregate level, all the (x) data matrices were analysed by means of quasi-statistics, i.e. qualitative results translated into simple numerical results and counts with the objective of supporting the cross-case and cross-country analysis.

(ii)

Cross-case comparison of the findings identified in the preliminary case studies

The cross-case comparison comprised an analysis on a cross-case level, but also on a cross-country (cross-national) level. In principle, an analysis was used based on visual displays of all the case studies’ ‘data’-findings using the technique of the partially ordered meta-matrix (see Tables 3.16 and 3.19) as provided by Miles and Huberman.3 The partially ordered meta-matrix allowed for the juxtaposition of the coded findings from the different case studies that were initially placed into a mega-table, i.e. a meta-matrix. The meta-matrix was then divided into smaller tables, i.e. the partially ordered meta-matrix tables (I and II), which enabled the sorting and partition of the findings into comparable units. The comparable units demonstrated similarities and differences with respect to certain categories-variables, such as the ‘roles of stakeholders in the governance’, the ‘outcome of in practice implementation’, ‘formal participation’, ‘the causes of the formal outcome’, and the ‘effects of the formal outcome’ (see Tables 3.16 and 3.19). The sorting and clustering of data was conducted within each category, i.e. based on findings per-country but also on a cross-case level.

(iii)

A synthetic causal explanation of the findings in relation to patterns and core themes The synthetic process entailed the use and development of causal networks. A causal network generally allows for the development of inferences from a case level causal analysis to a cross-case causal analysis.4 Miles and Huberman indicate that a ‘cross-case causal network is a comparative [case study] analysis of all cases in a sample, using variables estimated to be the most influential in accounting for the outcome criterion’.5 A causal network was developed which concerned the examined cases on a per-country level, i.e. a causal network for the cases in Belgium, Greece, and the UK (see Figures 3.6 – 3.9 and Figure 3.11). In this way, all the cases except for Case Study 9 were mapped in a specific causal network. The partially developed causal networks in Figures 3.6 – 3.9 were then combined and assembled into one aggregate meta-causal network (see Figure 3.10). The development of the meta-causal network demonstrated and visualised the most influential case-specific variables and their causes, but also the effects of the implementation of participatory governance in the examined cases. Consequently, the isolation of causal streams that were identified in the meta-causal network led to the analysis concerning the effectiveness and the effects of participatory governance in the examined cases. The causal analysis provided a schematic visualisation of patterns identified in the sequence and relationship of certain case-specific variables as well as their effects in a way that is meaningful across the cases.6

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