3. METODOLOGÍA
3.1 PROBLEMÁTICA DEL AGUA SITUACIÓN ACTUAL DE LA
This research adopts critical realism as a research paradigm (Bygstad and Henfridsson, 2013; McGrath, 2013; Mingers et al., 2013; Smith, 2010), which constitutes an alternative to the interpretative and positive paradigms, historically dominating the field of Information Systems (Easton, 2010; Wyn and Williams, 2012). Due to its stronger explanatory apparatus, critical realism can overcome the ‘theory-practice inconsistency’, which characterizes both positivism and interpretivism (Smith, 2006, p. 191). In particular, it can strengthen the understanding of non-deterministic causality, which is largely unaddressed in the other two dominant perspectives in IS (Smith, 2006).
The main principle of critical realism is that there is a world, which exists independently from our knowledge of it (Mingers et al., 2013). Although rooted in the research paradigm of realism, critical realisms advances our understanding of reality and advocates for the adoption of transcendental realist ontology (Mingers, 2004). As a result, it perceives the world as reality, divided in three distinct levels; real, actual and empirical (see Figure 5) (Bhaskar, 1993). Underlying objects forming structures and their causal powers characterize the real world, but tend to be unobservable (Sayer, 1992). Generative mechanisms operating in the real world produce patterns of events in the actual world, some of which we can experience in the empirical world (Bhaskar, 1993; Mingers, 2004; Smith, 2006). Reality, thus, consists not only of the events we observe, but also of the events that we could not observe and the mechanisms, which produce them.
41 Figure 5. Layered Ontology of Critical Realism (Sayer, 1992)
Understanding causality under the form of a generative mechanism is a central topic in critical realism (Bygstad et al., 2016; Henfridsson and Bygstad, 2013; Sayer, 2000; Smith, 2010). Zachariadis et al. (2013) argue that “observable events that are being causally generated from the complex interactions of mechanisms can give some information on the existence of these unobservable entities” (p. xxx). Critical realists reject the view on causality as a pattern of events based on a number of regularities (see Figure 6) (Sayer, 2000). Rather they advocate for identifying the generative mechanisms, which explain what caused (trigger) a particular phenomenon (outcome) and how the latter came into being (mechanism) (Henfridsson and Bygstad, 2013; Mingers et al., 2013; Sayer, 2000). In particular, the existing structures in the real domain enable certain generative mechanisms, which operate in specific context, to lead to events observable in the empirical domain (Smith, 2006; 2010). Due to the contingent nature of causality, there is no regularity between triggering events, the generative mechanisms and the various outcomes (Sayer, 2002). Instead, different triggers set in motion various generative mechanisms, which can account for different outcomes (Henfridsson and Bygstad, 2013; Sayer, 2000).
42 Figure 6. Critical Realism’s View on Causality (Sayer, 2000)
Critical realism advocates for “epistemic relativity” (Mingers et al., 2013, p. 797). Thus, critical realists recognize that knowledge is context dependent, socially constructed (Henfridsson and Bygstad, 2013) and incomplete (Smith, 2006). Wyn and Williams (2012) further argue that our knowledge is not isolated, but rather mediated by the values, beliefs and perceptions of the researchers.
Critical realists tell apart between transitive (our knowledge of the world) and intransitive (independent of our knowledge) knowledge (Bhaskar, 1977). Thus, while our knowledge of the reality is transitive, the world itself is intransitive (Smith, 2006). In particular, although researchers observe events in the empirical layer, they, in fact, operate in the actual layers and may be unobservable or different researchers can observe them in different ways (Easton, 2010). Thus, no knowledge is certain and most of the observations are erroneous, as they cannot guarantee complete consistency between reality and theory (Easton, 2010; Sayer, 1992; Wyn and Williams, 2012).
For critical realists, the goal of a theory is to generate as accurate as feasible explanations about the intransitive world rather than putting forward predictions about it (Hunt, 2005; Wyn and Williams, 2012). To ensure that the acquired knowledge about the real world is valid, researchers need to assess it critically by adopting different theoretical perspectives and methods to investigate the same data (Easton, 2010; Sayer, 2000). Thus, researchers often put forward multiple possible explanations of a particular phenomenon (Wyn and Williams, 2012).
As critical realism initially emphasized on ontology and later on epistemology, the guidelines on methodology remained largely absent in early work (Bhaskar, 1975; Sayer, 2000). In later contributions, critical realists recommend that to derive explanations of the observed events and the generative mechanisms producing them, researchers should rely on retroduction (Sayer, 2000), which is a specific form of abductive reasoning. When engaging in retroduction, researchers begin by concentrating on a particular phenomenon they wish to explain and trace back the mechanisms and events, which shape it (Easton, 2010; Sayer, 2000; Volkoff and Strong, 2013). Extending further this view, Mingers et al. (2013) summarize this approach as consisting of several
43 phases, namely describing the phenomenon, deriving possible generative mechanisms, evaluating the explanatory power of the proposed mechanisms and selecting the correct ones.
Due to the non-deterministic (contingent) causality, critical realism advocates for the adoption of multiple methods (Mingers, 2004; Mingers et al., 2013; Sayer, 2000). Sayer (2000) distinguishes between extensive (largely quantitative) and intensive (qualitative) methods of inquiry, where the former have less explanatory power than the latter (see Easton, 2010). Aiming to overcome the historical separation between quantitative and qualitative research, Zachariadis et al., (2013) further apply the ontological and epistemological principles of critical realism to advocate for mixed-methods research.
Despite these attempts, however, most IS scholars, when engaging in critical realism research, consider case studies as one of the most appropriate methods due to their ability to provide in-depth explanations (Easton, 2010; Mingers, 2004; Wyn and Williams, 2012). Initially, scholars have focused on providing detailed guidance how to conduct case study research from critical realism perspective in order to identify the relevant generative mechanisms (Bygstad and Munkvold, 2011; Easton, 2010; Henfridsson and Bygstad, 2013; Wyn and Williams, 2012). Wyn and Williams (2012), for example, outline five different principles – explication of events, explication of structure and context, retroduction, empirical corroboration, triangulation. Later, researchers also sought to extend these principles by proposing to identify generative mechanisms through affordances (Bygstad et al., 2016; Tan et al., 2015) or grounded theory (Vintzce, 2013).