Informes, Libro Blanco y otros documentos

A case study is defined by the choice of the research object used—an individual case, which may be a person, location, event, organization, or other boundable instance (Stake, 2005).69 _{Many scholars}

68 _{In fact I would argue that agency and structure are two ends of a continuum, rather than separate concepts.} However the use of the two terms aids in analysis and interpretation. Flyvbjerg (2001) makes this argument as well.

69 _{Please note that multiple (comparative) and nested case studies are possible and common. Nested case} studies will be discussed later in this section.

106 argue that rather than being a method, as it is sometimes described, case study is an approach or analysis process (Patton, 2002; Stake, 2005; Stark & Torrance, 2005). Various methods are then applied in the use of the case study approach. Interviews, participant observation, document analysis, and field studies are particularly common (Patton, 2002; Stark & Torrance, 2005), though case studies are by no means limited to qualitative analysis methods.

After choosing the research questions and determining that a case study best suits the research objectives, the researcher must then select the case. This decision is based on several considerations that are discussed in the Sampling Methods section below. Next, data are collected. These data are then assembled and processed to the extent necessary. In more complex cases, an intermediate step of creating a case record can be carried out. In this step the case data are further organized, condensed, and classified. During and after this phase, the data are analyzed.70 _{Finally, the case study}

narrative is written. This can be organized in various ways, for example chronologically or thematically. The goal is “a holistic portrayal, presented with any context necessary for understanding the case” (Patton, 2002, p.450).

Purpose & Approach

The purpose of a case study is to focus in-depth on a particular case; to systematically collect comprehensive, rich data on a particular subject and then carefully analyze meanings within the context of the case (Mukhija, 2010; Patton, 2002; Stake, 2005). Stake stresses “the case researcher digs into meanings, working to relate them to contexts and experience. In each instance, the work is reflective” (2005, p.450). Researchers also stress that “depth, detail, and richness” of data (also referred to as thick description, among other names) is the key to strong case study research and provides a mechanism for internal validity (Mukhija, 2010, p.419).

The case study approach “assumes that ‘social reality’ is created through social interaction, albeit situated in particular contexts and histories, and seeks to identify and describe before trying to analyse and theorize. It assumes that things may not be as they seem” (Stark & Torrance, 2005, p.33). Thus the case study approach fits clearly into the interpretivist theoretical perspective and constructionist epistemology within which this research is situated. Stark and Torrance go on to state that case study is “particular, descriptive, inductive, and ultimately heuristic—it seeks to ‘illuminate’ the readers’ understanding of an issue” (p.33). Case study researchers teach both by sharing what they have learned, as well as by presenting material to readers, thus facilitating the construction of knowledge by the reader (Stake, 2005).

Data Collection

Given that case studies focus on a particular instance in-depth, it is unsurprising that many types of data need to be collected in the case study process. Stake lists six categories of data, pertaining to: the nature of the case; the case’s historical background; the physical setting; economic, legal, political, and other contexts; other cases with similarities to the case of interest; and informants (2005). Patton lists method-linked data categories: interview data, observations, documents, and statistical information, among others (2002). These data can be used to reconstruct the case, illuminate different

70 _{The nature of the analysis depends on the methods employed. The specific methods used in this research are} discussed in Section 3.3.

107 understandings of the phenomena at hand, and identify changes in values and objectives of individuals or programs over time.

A particularly difficult aspect of data collection is determining the boundaries of the case. Given that various contexts and their interplay are key to quality case research, it is easy to see the difficulty in bounding the case—too small and important connections are lost; too large and the case’s larger environs subsume the case. Stark and Torrance (2005) caution against the automatic use of physical boundaries of the case location, giving the example of investigating schooling and excluding the role of parents, were the school itself used to bound the case. They also provide an example of an alternative bounding, taking a vertical ‘core’ from the central policy-maker, down to the ground-level implementation in the example of a policy case study (Stark & Torrance, 2005, p.35).

Sampling Methods

Case studies often use purposive (also known as purposeful or theoretical) sampling, often associated with qualitative methods, in contrast to random sampling, which is often used with quantitative methods. The strength of analysis based on purposive sampling is not linked to the number of samples, as it is in random sampling, where a sufficiently high number of samples is required to show statistical significance. To the contrary, the strength of purposive sampling comes from the selection of an information-rich case appropriate to answering the research questions (Patton, 2002). While the strength of random sampling comes from the researcher not influencing the cases selected, in purposive sampling the researcher’s choice of appropriate case(s) can determine the strength of the study before any data collection or analysis is carried out. That is, if a researcher selects individuals or groups who have deeper experience or understanding of the problem of interest, the research will be stronger than had he or she attempted to randomly sample individuals (who may or may not have the necessary knowledge and experience).

Purposive sampling does of course have shortcomings: the voices and perspectives of individuals and groups that are underrepresented, intentionally or not, may be left out of the research. In the case of exploratory research, such as this, important parties may be excluded due to the inherent ambiguity of an exploratory approach.

Stake (2005) divides case studies into three types: intrinsic, instrumental, and multiple or collective case studies. Intrinsic case studies are those undertaken to better understand the case itself. This is in contrast to instrumental cases, which are studied in order to investigate the concerns of researchers—that is, to develop or test theory. Multiple or collective case studies are instrumental case studies extended to multiple cases. In my opinion, intrinsic case studies are an ideal, but non- existent, type, since all researchers select their cases for some reason, in order to investigate some understanding or lack of understanding of the world.

Both Stake (2005) and Patton (2002) advocate case selection on the basis of the opportunity to learn and develop knowledge. Patton (2002) details sixteen purposive sampling strategies, each with its own purpose. The rationales vary: extreme or deviant case sampling examines unusual cases of a phenomenon; typical case sampling investigates the ‘normal’ instance of a phenomenon.71

Opportunistic sampling makes use of flexibility and emergent circumstances, while political

108 importance-based sampling is used to attract attention to the study. Clearly, the scientific credibility of sampling methods varies.

Both Patton (2002) and Flyvbjerg (2006) draw attention to the possibility of a case fulfilling multiple sampling selection strategies. In these cases the researcher may be able to analyze the case from multiple perspectives (Flyvbjerg, 2006)).

Cases generally include smaller units within them: people, places, events, and policies, for example. These are referred to as layered, nested, embedded, or mini cases (Patton, 2002; Stake, 2005). Some authors advise collecting data on the lowest reasonable level, as aggregation is always possible but disaggregation is not (Patton, 2002). Nested cases can take interesting forms; for example, Mukhija (2010) suggests creating subcases based on different perspectives; in his example, those of for-profit housing developers, non-profit housing developers, and community cooperatives.

Generalizability

The inability to generalize statistically from a case study to a population is considered the major weakness of case study research (Stark & Torrance, 2005). Some argue that case study research efforts can be small steps toward generalization (Stake, 2005), while a more traditional view considers case study research to be appropriate only for hypothesis generation, and thus appropriate for under- researched and weakly developed areas of research.

Others argue for the generalizability of case studies. These arguments fall into two groups. The first is based around Popper’s falsification test, in which a scientific statement can be falsified through one counter example. A falsification of a theory would certainly be generalizable. The selection of critical cases, those in which it can be said “if it happens there, it will happen anywhere” or “if it doesn’t happen there, it won’t happen anywhere” (Patton, 2002, p.236), is ideal in case study research designs investigating theory falsification (Ruddin, 2006).

The second argument for the generalizability of case studies is referred to as “naturalistic generalization” (Stake & Trumbull, 1982). Here generalization is considered transferability, meaning that the researcher provides detail rich description that facilitates each reader making an individual judgment on whether a case is generalizable or not (Lincoln & Guba, 1985; Ruddin, 2006; Stark & Torrance, 2005). This is the argument I make for this research. My intention is to provide sufficient detail and depth of description so that, in addition to my conclusions, readers can judge for themselves in which ways the work is generalizable. I provide some direction, such as restricting the discussion to weak market regions, but leave the task of making generalizability decisions to the reader on a case- by-case basis. Of course, I intend for this research to generate hypotheses that can be tested in later research as well.