Oportunidades de acción para las CRA

The previous chapter identified a research gap by demonstrating a lack of systematic research on the effects of industry sectors on corporate language management. The present study aims to contribute to filling this gap by investigating corporate language management strategies in a qualitative case study with two matched pair cases across two industry sectors, underpinned by a realist ontology combined with a constructivist epistemology – i.e. critical realist assumptions (Maxwell, 2012).

Firstly, this is a study that employs qualitative data and methods of analysis. In line with Doz (2011, p. 583), the present study perceives ‘qualitative research’ as ‘qualitative analysis […] of qualitative data […]. Qualitative research is useful for gaining in-depth understanding (Patton, 2002), rich explanations (Weick, 2007) and realistic insight into a particular phenomenon (Pratt, 2008). A qualitative research design is also flexible in the way that data collection and theory building are closely interlinked, which in light of this project’s purpose is considered highly advantageous.

Case studies may be defined in numerous ways, as discussed by e.g. Gerring (2004), Platt (1992) and Ragin (1992). The present study focuses on understanding a particular phenomenon, namely the effects of industry sectors on corporate language management, which corresponds to Miles and Huberman’s (1994, p. 25) definition of ‘cases as a phenomenon of some sort occurring in a bounded context’. Case studies are seen as particularly appropriate in contemporary research areas as it does not depend on the existence of previous literature, which is scarce in the present research situation (cf.

Eisenhardt, 1989; Yin, 2009). The closeness of the case study provides a strong basis for developing holistic understanding, since a case study approach offers the possibility to examine the phenomenon – corporate language management – in its own context (Gibbert, Ruigrok, & Wicki, 2008, p. 1466). For this reason, Flyvberg (2006, p. 241) observes that case studies are very useful for ‘understanding the degree to which certain phenomena are present in a given group or how they vary across cases’.

Flyvberg’s observations are particularly relevant to the present study, as it consists of multiple case companies, i.e. two matched pair cases. Multiple cases are beneficial in the sense that they allow for cross-case comparison, which is often described as a strong basis for providing compelling evidence. In the words of Eisenhardt (1989, p. 541): ‘the idea behind […] cross-case searching tactics is to force investigators to go beyond initial impressions’ […] which will ‘improve the likelihood of accurate and reliable theory, that is, a theory with a close fit with the data’. In the context of this study, the two matched pairs will facilitate cross-sector comparison of findings across the two financial service cases and the two manufacturing cases. This is an important aspect of the case selection strategy, as the cross-sector comparison will shed light on the effects of industry cross-sectors from two different angles (financial services vs. manufacturing). Bazeley (2013, p. 255) describes the benefits of comparative analysis very accurately when stating that ‘the process of comparison, like no other, brings into sharp focus the

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distinguishing features of whatever it is you are considering’. Applied to the present study, Bazeley’s words may serve as a justification for comparing corporate language management across two very different sectors – in order to bring out the ‘the distinguishing features’ of sector effects on the case companies’ approach to language management.

The present study is a study of sector effects across two industries, yet, it comes with the following caveat: this is a study that examines the effects of sector alongside other contextual factors. The sectors must, in other words, be seen as a part of the company’s context. In a case study design, it is impossible to isolate the effects of the sector from other effects; rather the sector effects are coupled and intertwined with other company-specific factors which together influence the way the case companies manage language. For this reason, it is important to emphasise that all sector-specific effects are discussed on the basis of findings obtained from the two pairs of cases. In line with the recommendations provided by Miles and Huberman (1994, pp. 207-208), the study will put much emphasis on providing comprehensive within-case analyses before moving over to the cross-case analyses.

At this point it may be worth recalling the two research questions for this study, which are:

RQ1: How is the context reflected in the way language is managed a) in the two financial service companies?

b) in the two manufacturing companies?

RQ2: Which language management tools are implemented and why a) in the two financial service companies?

b) in the two manufacturing companies?

The first research question recognises the inter-connected relationship between a company’s context and the sector as part of this context. This question has been formulated in a relatively open manner, as the first part of the project largely focuses on gaining knowledge about the case companies’ overall situation, and in relation to that, their approach to language management. As four case companies are included in this study, the first part of this thesis will, as already mentioned, consist of four within-case analyses, according to the two industry sectors. Based on the findings presented in these within-case analyses and a brief cross-case analysis between the two pairs of cases, the ensuing discussion across the industry sectors will seek to identify sector-specific effects on the companies’ approach to language management.

The second research question is more narrowly defined and focuses explicitly on the deployment of language management tools (cf. section 2.4) in the case companies. Also these two empirical chapters (financial services; Ch. 7 and manufacturing; Ch. 8) will lay emphasis on the four within-case situations before going into a discussion on the effects of industry sectors on the use of the various tools. Still, like

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the first research question, the second research question also aims to understand how and why the two industries may affect the use of various language management tools.

This study is underpinned by the philosophy of critical realism. The distinction between ontology and epistemology is essential in critical realism: critical realists assume that a real world exists independently of the observers (i.e. a realist ontology) while at the same time acknowledging that our knowledge of the worlds is socially constructed (i.e. a constructivist epistemology) (Bhaskar, 1978;

Easton, 2010; Maxwell, 2012; Outhwaite, 1998; Sayer, 1992). My motivation for carrying out a study that examines the effects of industry sector on corporate language management lies in discovering what those effects are, how they play out in practice, and why they do so. In the language of critical realism, industry effects may therefore be described as ‘causal mechanisms’, which are defined by Morais (2011, p. 67) as ‘the process by which a structure is activated’. Causal mechanisms are central for generating causal explanations, i.e. the relationship between the cause (industry sectors) and effect (language management). Therefore, a causal explanation involves identifying the causal mechanism (industry sectors) and connecting them to the events that occur (selection of language management tools) (Easton, 2011, p. 122).

In their 2011 article ‘Theorising from case studies’, Welch et al. identify four methods of case study research, where the philosophical orientation of critical realism forms the basis for what the authors call a ‘contextualised explanation’. Seeking causal explanations involves ‘understanding the constituent nature of objects’, in the words of Welch et al. (2011, p. 748). ‘This method of theorising is based on the assertion that case studies can generate causal explanations that preserve rather than eradicate contextual richness’ (p. 750). In line with this view on critical realist case studies, the present study also emphasises the role of context when investigating the effects of industry sectors on corporate language management. However, it is also the intention of this project to examine the use of language management tools as they have been defined in the literature review – consequently, this thesis also contains elements of what Welch et al. labels ‘the natural experiment’ by referring to falsificationist positivist assumptions, commonly referred to as theory-testing studies. Without adhering to positivism as such, it is clear that parts of this project (especially regarding RQ2) are deductive in nature, which in relation to the critical realism position can be seen as an expression of post-positivism (Lapid, 1989).

Thus, in Welch et al.’s typology, the present study is placed in between the ‘contextualised explanation’

and the ‘natural experiment’.

It follows from the constructivist epistemology of critical realism that knowledge is considered

‘fallible and theory-laden’ (Sayer, 1992, p. 5), which is an important consideration also in the present study. This is not an experiment carried out in a laboratory; it consists of real-world companies and a real-world researcher who collected real-world empirical data by real-world methods. Clearly, several interpretative elements are present and may affect the findings obtained through this research process in one way or another. However, the constructivist epistemology of critical realism must be seen in close

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relation to the realist ontology; even if it is impossible to achieve a purely objective account of the world, that does not contradict the world’s existence (Maxwell, 2012, p. vii). In other words: I conduct this study while believing that it is possible to examine the effects of industry sector on corporate language management, while acknowledging that I as a researcher take an active part in constructing the observations I make when carrying out the study.

3.2 Choice of case companies