Sampling in Qualitative research

In qualitative research, there are three types of sampling strategies, theoretical in grounded theory, purposeful and purposive sampling (Emmel, 2013). These three, he argues, may often be used interchangeably and may even seem to have contradictory meanings.

3.13.1 Theoretical Sampling

Theoretical sampling is intrinsically part of grounded theory where theory is generated from the study or investigation of the empirical social world (Glaser and Strauss, 1967; Emmel, 2013). According to Emmel (2013) however, since central to grounded theory is emerging theory where the researcher is constantly asking what groups or sub-groups does one turn to next in data collection, and for what theoretical purpose; then, theoretical sampling in grounded theory can neither be identified ahead of the research, nor can it be allotted to a thing, person, organisation, document or a research instrument. He states:

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“Instead, the researcher is continuously guided by emerging theory as to where to go next in search of their sample. Structural (or practical) concerns are not the guide to identifying the sample; rather it is the impersonal criteria of emerging theory.” The researcher must

be completely open and receptive to emergent theory without letting any preconceptions impede the flow of the research as theories emerge. Charmaz (2014) states: “theoretical sampling means seeking pertinent data to develop your emerging theory. The main purpose of theoretical sampling is to elaborate and refine the categories constituting your theory. You conduct theoretical sampling by sampling to develop the properties of your categories until no new properties emerge”.

3.13.2 Purposeful Sampling

This has been looked at in nonprobability Sampling but here, a little more in detail. Purposeful sampling strategy is very different from theoretical sampling. Much of the sampling here is influenced by the researcher’s judgement and skill in the field of study, and what is learnt before, during and after the research. According to Emmel (2013), “the purpose of purposeful sampling is to select information rich cases that best provide insight into the research questions and will convince the audience of the research.” Purposeful

sampling also called ‘pragmatic sampling’ (Patton, 2002), is also an aspect of grounded theory, but, unlike theoretical sampling, purposeful sampling makes a judgement about who or what to sample with respect to the purpose of the study, its context, and the specific audience for the research (Emmel, 2013). This judgement or purposive sampling is not driven by theoretical categories, but practical and pragmatic considerations, with the sole aim of doing what makes sense, reporting fully on what was done, why it was done, and what the implications are for the findings (Patton, 2002). Emmel (2013) states:

“The logic and power of purposeful sampling rest on the in-depth study of information rich cases, towards learning a great deal about the research question and the issues considered by the researchers to be of central importance.”

The selection and in-depth study of cases deemed to be information rich is the sampling strategy adopted by this research. The successful and unsuccessful turnaround companies were chosen because they fit the purpose of the study and were seen to have the right information to satisfy the questions being asked by the study. Emmel continues:

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“These cases are worthy of in-depth study because they provide detailed insight.”

It is also important to note that even though purposeful sampling is very different from probabilistic sampling; the use of strategies of randomisation, stratification, or quotas to select cases may be used. This is not for the purpose of generalizability but for the purpose of seeking out cases that give the findings credibility with its audience (Emmel, 2013). Furthermore on strategy of purposeful sampling, Emmel shrinks Patton’s 14+1 strategies for purposeful sampling into six strategies for purposeful sampling. They are:

Table 3.1: Purposeful sampling

S/N Strategies

1 First, researchers make judgements before, during, and after sampling about what to sample and

how to use the sample in making claims from their research.

2 Secondly, there judgements are made with reference to what is known about the phenomena under

study. This includes recognising that much can be learnt from exploring the ways in which phenomena are described through variables, categories, and insight from both quantitative and qualitative research.

3 Thirdly, based on what is learnt before the research starts and as the research proceeds, researchers are strategic in selecting a limited number of cases toward producing the most information that is usable.

4 Fourthly, researchers are aware of who the audience for their research will be and choose

sampling strategies that will produce the most credible results for these audiences.

5 Fifthly, these decisions are always constrained by resources, an important consideration but one

that should be addressed only after the first four themes are considered. Qualitative researchers would always like to sample more, but have to make choices with reference to time to do fieldwork, budget, and their capacity to analyse the data they collect.

6 And finally, there are quite different logics to qualitative and quantitative sampling strategies.

These differences are exemplified in the purpose of the purposeful sample.

Source: Emmel (2013)

With regards to sample size, Emmel (2013) states that the school of thought here is divided. There are authors who advocate that the sample size must be a specific or proportionate number and others who argue that the sample size is not the issue, but how the researcher is able to convince his or her audience with the cases they are able to collect given the resources available to them. This research adopts the latter.

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3.14

Theoretical or purposive sampling

This sampling strategy on the other hand embraces theory in such a way that the researcher’s intellectual work is pivotal in the progress of the research. According to Emmel (2013),“theoretical or purposive sampling strategies assume that to explain real phenomena requires more than a faithful abstracted rendering of events and experiences. It requires direct engagement between theory and empirical accounts in interpretative and inductive strategy of sampling.” According to Tongco (2007), in purposeful/purposive

sampling technique, the researcher must know about the field of study before he/she samples the population in order to find knowledgeable and reliable informants most efficiently. The next thing is for the researcher to decide what needs to be known and set out to find people who can and are willing to provide the information by virtue of knowledge or experience (Bernard 2002). The informant must also be as near as possible to the theoretical norm of the sampled population (Tongco, 2007). In order to choose the right informants, Guest et al (2006), and Allen (1971) states that a set of specific criteria needs to be drawn out on what would make a good informant. The selection criteria for this study will be discussed in a later section.

In summary, given the research question of this study – “How can a failing small and medium-sized construction company turnaround?” – it is quite clear that in order to answer

the question, we will need to select information rich cases (good informants) that best provide insight into the research questions, in this case, companies with experience of successful turnaround or companies who have attempted a turnaround but failed. An in- depth study of these cases will definitely go a long way in answering the research question. Therefore, the best strategy of sampling for this study is deemed to be the ‘Purposeful sampling’ strategy. Since the intricate logic and power of purposeful sampling rest in the in-depth study of information rich cases that help the researcher answer his or her research questions. In succinct terms – it fits the direction of the study.