Case Study Approach

An intensive and detailed analysis of a single case, for example a particular event, an organisation, a person, a community or indeed a variety of others, is called a case study, an approach often, but by no means exclusively, linked to qualitative research (Bryman 2012, Yin 2014). According to Yin (2014) a case study is “an empirical

enquiry that investigates a contemporary phenomenon within its real life context” (p.

14). While all research operates in terms of a certain unit of analysis, in contrast to survey research, case study research focuses on the investigation of a small number of

cases in great depth. However, it differs from experimental research in that there is no direct control of any variables present in the cases under investigation, as naturally occurring rather than artificially created situations serve as the basis for the construction of cases (Hammersley and Gomm 2000). Case studies are characterised by the collection of contextually rich data, thus often favouring qualitative data sources such as interviews, observation or document analysis as form of secondary data analysis (Easterby-Smith et al. 2012, Yin 2014). This focus on rich data that derives from a particular context makes case study research a particularly promising approach for the study of complex social phenomena in which a variety of variables, some of them unknown to the researcher, shape particular responses or outcomes in a network of fuzzy interactions (Stake 2000, Flyvbjerg 2013). However, due to the exceedingly large amounts of data involved and the time and skill the collection and analysis of this data necessitate, case study research is not an efficient form of research, a disadvantage outweighed by its unrivalled ability to prevent a disconnect between research and reality (McCutcheon and Meredith 1993). This makes case study research a particularly desirable approach in the field of HL, where managerial applicability is required in an effort to not only prevent monetary loss, but also to curb human suffering (Van Wassenhove 2006).

From the 1980s onwards, case study research has been employed in the area of operations management, predominantly for exploratory studies or in descriptive ways (McCutcheon and Meredith 1993). By now it has become a very widely accepted method with some heralding the past two decades as a “renaissance” of case study research in operations management (Stuart et al. 2002, Voss et al. 2002, Ketokivi and Choi 2014). With the growing recognition of the importance of a variety of research approaches in logistics, this too has become an area in which case study research is increasingly debated (Ellram 1996, Naslund 2002). Indeed, a questionnaire of leading logistics and SC experts revealed that case studies were ranked alongside surveys as the preferred research methods (Larson and Halldórsson 2004); a preference that is not necessarily reflected in the number of publications in relevant journals (Aastrup and Halldórsson 2008).

The legitimisation of case study research in operations management (McCutcheon and Meredith 1993, Voss et al. 2002) has built primarily upon the work of Eisenhardt (1989) and Yin (1989, 1993). However, the omnipresence of their approach in operations management has recently garnered critique as the notion that case study research derives its value primarily from the identification of constructs that can then be

tested through other methods has been rejected, highlighting the value case study research has in its own right (Ketokivi and Choi 2014). Furthermore, different possible approaches have been highlighted, contradicting Eisenhardt (1989) by not setting cases based on pre-conceived notions, as well as by extolling the virtue of single cases (Spring and Santos 2015). Nevertheless, there is great value to be found in clearly structured approaches to case study research, as these serve to counter some of the criticism levelled at this approach, labelling it “ad hoc” research and questioning its usefulness beyond the mere exploration of new research areas (Ellram 1996). In particular, repeated criticism regarding the perceived lack of rigour in case study research has been countered with conventions for its application being set out building upon the previously mentioned works of Eisenhardt (1989) and Yin (1989, 1993), but focussed specifically on operations management, with guidelines for both inductive and deductive case studies (Barratt et al. 2011). Figure 20 presents the research process of case study research employing multiple case studies that are first analysed individually and then focusing on theory modification based on cross-case analysis. Conversely, Eisenhardt (1989) encouraged theory-building research, that does not seek to validate theory or to test hypotheses through the use of case studies.

Figure 20: Case Study Research (Yin 2009, p. 57)

While case study research is prevalent in both operations management and logistics research, it is usually characterised by a lack of epistemological justification (Aastrup and Halldórsson 2008), a phenomenon that is not only restrained to these areas of research, but has been observed in other disciplines as well (Meyer 2001). While it is

not constrained to this research paradigm, case study research has been highlighted as particularly suited to a critical realist perspective, as it enables the conceptualisation of the causal power of structures that are so essential in the realist view of causation (Tsoukas 1989, Aastrup and Halldórsson 2008, Easton 2010). The desire “to

understand generative mechanisms that underlie practice and performance” (Aastrup

and Halldórsson 2008, p.759) is the underlying motivation of critical realist research, thus revealing links between the Real domain of mechanisms and structures with the

Actual domain that generates particular events and outcomes. Case studies do not solely

describe empirical events, but due to the richness of the data collected, they can also be used to trace linkages and causal powers in order to uncover the actual and the real domain (Easton 2010).

Another particular strength of case study research within the critical realist paradigm lies in the ability to uncover causes and causal powers in open systems, such as SCs, without overly relying on prediction, but focussing on explanation through the abductive reasoning process that allows the constant oscillation between the Actual and the Real domain, thus unveiling potential structures and causal powers and through the process of elimination of alternatives eventually unveiling the underlying reality (Mingers 2000a, Aastrup and Halldórsson 2008). Critical realism acknowledges that social phenomena are dependent upon the context within which they occur (Sayer 1992). As case studies frequently utilise interviews as the sole or predominant method of data collection, they are well-placed in accounting for these contextual elements, as the data are gathered directly from agents within the open system under investigation and therefore include the causal powers and effects of meanings that are ascribed by said agents (Aastrup and Halldórsson 2008). It is important to note that under the critical realist paradigm, the researcher is not the producer of the identified causal laws, but merely gains access to them through the engagement with the open systems under investigation (Tsoukas 1989).

Both inductive and deductive approaches to case study research are possible and both are employed frequently (Barratt et al. 2011). Due to its solid foundation within real organisational problems and issues, case study research can be an excellent source of theory development (MacCarthy et al. 2013). However, Voss et al. (2002) insist that even an inductive approach requires a priori understanding of the general constructs under investigation and the relationships between them. As the importance of theory- driven empirical research grows in order to enable further understanding of highly complex operations management topics, so does the importance of theories

underpinning case study research (Melnyk and Handfield 1998). Regardless of the inductive or deductive nature of an enquiry, the inclusion of established theories, often from fields outside of operations management, lends validity to the conclusions drawn from the data (Barratt et al. 2011). With this focus on theory in conjunction with the highly practical approach of case study research, Spring and Santos (2015) suggest abductive reasoning as the ideal way to balance theory and practice and thus rigour and relevance of case study research. As seen in Figure 21, Ketokivi and Choi (2014) differentiate between theory testing, theory generation, and theory elaboration, aligning the latter with abductive reasoning, the iteration between general theory and the empirical data created in the case study research. As previously outlined, this is the approach taken in this thesis.

Figure 21: Three modes of conducting case research (Ketokivi and Choi 2014)