CODIFICACIÓN

The research adopts a critical realist epistemology, as developed in the works of Bhaskar (1978), Archer and Bhaskar (1998); Sayer (1992), Easton (2000, 2010), Danermark et al. (2002), Archer (2010) and Tsoukas and Chia (2011)8_{. The reason for considering a critical} realist stance is threefold: First, a critical realist epistemology provides superior congruence between the thesis’ research objective of explanatory theory development from a qualitative data set and the adopted network ontology. Moreover, this combination of epistemological, ontological and methodological approaches has been continuously advanced in the field of business network research, which allowed the researcher to learn from existing work by reading published research (for instance, Harrison & Easton, 2002) and from personal conversations with Geoff Easton in 2011 and 2012, who offered invaluable advice on critical realism informed qualitative case study research. Second, critical realism offers a set of conceptual tools to make sense of empirical observations and guide explanatory theory development. These conceptualisations include the critical realist understanding of dynamics in polyvalent open social systems, the morphogenetic cycle in structure-agency settings (Archer, 2010) and the development of causal mechanism explanations (Hedstrom, 2005; Mason, Easton & Lenney, 2013; Pawson & Tilley, 2013). Third, critical realist assumptions about knowledge generation support the methodological choice of case study research method (Easton, 2000; 2010).

The following briefly examines key assumptions of critical realism, including the concepts of a stratified reality and the operation of causal mechanisms as an approach to explanatory theory development. An abbreviated version of core assumptions underpinning the critical realist epistemology include (Sayer, 1992; Archer, 2010):

a) The existence of a mind-independent reality.

8_{This research does not consider the meaning of ‘critical’ in the Marxist context of identifying and} changing suboptimal social structures. Instead, the term ‘critical’ is used to refer to the researcher’s awareness for the need for critical reflection throughout the research process, which is partly an implication of a stratified understanding of reality and the understanding of inevitable limitations of any research process in capturing ‘reality’.

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b) The understanding that perception and knowledge of this reality is fallible and theory laden. Evaluating the accuracy and truth value of research findings rests in its practical adequacy.

c) Analytical dualism, which captures the interdependence of structure-agency duality in a ‘morphogenetic cycle’ (Archer, 2010, p.276).

d) A differentiated and stratified reality, where natural and social objects possess “powers and liabilities capable of generating events” (Sayer, 1992, p.5). These structures exist regardless of whether they generate regular patterns of (perceivable) events or not9_.

Critical realism assumes a stratified reality, comprising the ‘empirical’, ‘actual’ and ‘real’ domains:

Table 3.1. Stratified reality. Adapted from Bhaskar, 1978, p.13.

Empirical Domain Actual Domain Real Domain

Experiences ✓ ✓ ✓

Events ✓ ✓

Mechanisms ✓

The ‘empirical domain’comprises the layer of reality imperfectly perceivable by the researcher through experience and senses. The empirical domain includes all that is possibly perceivable, including “the external and visible behaviours of people, systems and things as they occur… [or] are reported” (Easton, 2010, p.120). The ‘actual domain’comprises events and actions that a researcher may be partially aware or unaware of, due to limited cognitive capacity that prevents accurate capturing of all empirical events and activities. The ‘real domain’comprises “structures, mechanisms, powers and relations” (Ackroyd & Fleetwood, 2000, p.13, emphases added) that are generally not directly apprehensible by the researcher, but can be approximated through scientific inference – specifically the process of retroduction - and analysis. Across the three layers of reality, there are ‘objects’ and ‘entities’ connected through necessary and/or contingent relations, which together form the “basic theoretical building blocks for critical realist explanation” (Easton, 2010, p.120). The aim of critical realist inquiry is to penetrate the surface level of the empirical and actual domains in order to uncover generative causal mechanisms.

9 _{For a comprehensive discussion of critical realist assumptions, please consult Sayer, 1992,} particularly from p. 5 onwards.

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Identifying ‘causal mechanisms’ is key to meeting the explanatory aim of critical realist research, which seeks to answer the question of what caused the events observed in the empirical domain to happen (Easton, 2010)? In other words, “to ask for the cause of something is to ask what ‘makes it happen’, what ‘produces’, ‘generates’, ‘creates’ or ‘determines’ it or, … what ‘enables’ or ‘leads to’ it” (Sayer, 1992, p.104). Easton defines ‘mechanisms’ as “ways in which structured entities by means of their powers and liabilities act and cause particular events” (2010, p.122). Consequently, a causal explanation“is one that identifies entities and the mechanisms that connect them and combine to cause events to occur” (ibid., emphasis added). Figure 3.1 illustrates conceptually the operation of causal mechanisms:

Figure 3.1. Causal mechanism. Adapted from Sayer, 1992, p. 109.

‘Mechanisms’ in critical realist literature are also referred to as ‘deep structures or processes’ (considering their emergence in the ‘deep/real’ domain) or ‘generative mechanisms’ (considering their power to ‘generate’ events in the actual and empirical domain). Figure 3.1 illustrates that the relation between objects (or social entities) and causal powers is necessary. However, the relation between causal powers and their conditions (also referred to as ‘context’, which has the potential to activate the mechanisms) is contingent (Sayer, 1992). Because the activation of mechanisms is context-contingent, critical realist research considers context - the structural embeddedness of (social) entities and the relationships between entities - seriously. The present research translates this consideration into practical research terms by:

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b) Using a layered unit of network analysis (Section 3.5) to examine the relationships between entities;

c) Presenting it in a defined industry context (see Chapter Four).

Since causal powers do not inhere “simply in single objects or individuals but the social relations and structures which they form” (Sayer, 1992, p. 104, emphasis added) it is important that the research ontology and unit-of analysis informing this research enable the examination of relationships between entities. Identifying potential causal mechanisms relies on applying retroductive logic to scientific inference, proceeding backwards from the empirically observable events of the ‘empirical domain’ to the patterns of activities in the ‘actual domain’ to the abstract mechanisms in the ‘real domain’ (Danermark et al., 2002). Retroductive logic assumes that “events are causally explained by retroducing and confirming the existence of mechanisms …in turn the existence of mechanisms is explained by reference to the structure … of the objects” (Sayer, 192, p.235). While deductive and inductive logic allow movements within the ‘empirical layer’ from the general to the particular and vice versa (Easton, 2010), retroduction implies movement across the three layers of reality from one, empirically observable phenomenon to an abstract mechanism.