There are two types of sampling techniques: probability and non-probability. The selection of the study sample is very important for any research. According to Cohen, Manion, and Morrison (2007), the probability sampling method gives all members in the population the chance to be included in the sample. However, this type of sampling requires a sampling frame that includes all members of the population. The second type of sampling technique is the non-probability sample, which does not require any sort of sampling frame. The choice of sample type depends on the nature of the research problem, availability, cost, time, level of accuracy, and data collection methods (Cohen et al., 2007).
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6.8.1 Qualitative sampling techniques
This study does not seek results that are generally or universally true, because the nature of the study is evaluative, depends upon key leaders from both public and private sectors, and draws much of its empirical material form the Emirates, and from a limited sample. This study used interviews to explore the issue of Emiratisation, and address the problems related to the implementation of the policy. Therefore, the sampling technique that was used was the purposive sampling method, also known as the expert sampling method that depends on the researcher‟s judgement, focuses on certain issues, and targets certain people. This type of sampling, which derives its questions from prior interviews or focus group discussions, enables researchers to answer research questions about what larger numbers or categories of persons think or say (Patton, 2002).
When implementing qualitative research methods, there is no exact sample size, and results depend only on the data collected from participants (Rubinstein, 1994). According to Baum (2008), there is no rule for sample size in qualitative methods, because sampling usually relies on a small number of participants and aims to elicit rich and detailed information about the subject being studied, not universally true generalisations (Miles & Huberman, 1994). In this study, the aim is to seek a richness of data about Emiratisation and how people in higher positions and decision making think about the policy and its success and/or failures. This study targeted 20 key informants/leaders (in high ranking positions) from both the public and private sectors. The sample, therefore, was purposefully selected from different public and private organisations, rather than randomly. The public and private sectors, which are the main employers in the UAE, whether Emirati nationals or expatriates, have the main responsibility for designing and/or implementing policies and strategies related to the labour market and employing people. For these reasons, this study targeted key people from these sectors.
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6.8.2 Quantitative sampling techniques
Sample size:
This study used a questionnaire to explore the views of Emirati nationals about Emiratisation and its advantages and disadvantages. According to Baines and Chansarkar (2002), the sample size has a critical impact on the statistical significance of the study, as well as the confidence of the results. According to Cohen et al. (2007), there are no clear answers to the question what is correct sample size, but a questionnaire sample should reflect the views of a larger population; that is, it should be large enough to estimate the population mean (Kumar, 2005). About 700 questionnaires were distributed by hand to young Emiratis who visited the National Human Resources Development and Employment Authority (Tanmia) in a two month period. These people came to Tanmia for the purpose of finding jobs and/or enquiring about training courses and personal development. Furthermore, Tanmia conducts open days every Sunday for Emirati nationals. These focus on the training courses that offered by Tanmia. Additionally, Tanmia‟s employment advisors discuss various topics with young Emiratis, such as employment and unemployment and other issues. Those young nationals may already work for different types of organisations (public sector, private sector, and others), or they may be self-employed and unemployed. More than half of the distributed questionnaires were completed by those to whom they were offered.
Sampling technique:
Sampling does not requireincluding the whole target population, and in this study the number of interviewees was in any case limited by time, resources and access constraints, and it was therefore essential to target a small portion of the population. As Leedy and Ormrod (2012) say, that is the point of sampling. According to Neuman (2009), to study an entire population, it is necessary to isolate a specific number of variables (causal factors) and generalise the findings in relation to the larger population. Sampling of this quantitative type, according to Gall, Gall, and Borg (2006), is a way of selecting a number of people or organisations from a population to
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represent the entire population. As indicated above, there are two sorts of sampling techniques: probability sampling and non-probability sampling. In probability sampling, every member or element of the population has the chance to be selected in the sample. By contrast, in non-probability sampling the researcher makes a judgement in the selection of the sample.
The stratified random sampling technique, used in this study, is claimed to increase the precision of the results. Stratified sampling depends upon dividing the target population into a number of strata (for example age or gender). Stratification also depends on „randomisation‟, which gives equal chance to all individuals to be included in the sample (Cochran, 1977, p. 90). In this study, the strata (sections) represent age, gender, and employment status. The sample design covers the method of selection and the sample structure. In this study, the design of the sample utilised the characteristics of graduate, skilled and unskilled workers. The Statistical Package for the Social Sciences (SPSS)12, version 19, was used for selecting the sample, which covered three strata: age, gender, and education level.