PURPOSIVE SAMPLING

Purposive sampling

Purposive sampling (also known as  judgment, selective or subjective sampling) is a sampling technique in which researcher relies on his or her own judgment when choosing members of population to participate in the study.

Purposive sampling is a non-probability sampling method and it occurs when “elements selected for the sample are chosen by the judgment of the researcher. Researchers often believe that they can obtain a representative sample by using a sound judgment, which will result in saving time and money”.[1]

TV reporters stopping certain individuals on the street in order to ask their opinions about certain political changes constitutes the most popular example of this sampling method. However, it is important to specify that the TV reporter has to apply certain judgment when deciding who to stop on the street to ask questions; otherwise it would be the case of random sampling technique.

Alternatively, purposive sampling method may prove to be effective when only limited numbers of people can serve as primary data sources due to the nature of research design and aims and objectives. For example, for a research analysing affects of personal tragedy such as family bereavement on performance of senior level managers the researcher may use his/her own judgment in order to choose senior level managers who could particulate in in-depth interviews.

Purposive sampling

In purposive sampling personal judgment needs to be used to choose cases that help answer research questions or achieve research objectives.

According to the type of cases, purposive sampling can be divided into the following six categories[1]:

    Typical case. Explains cases that are average and normal.

    Extreme or deviant case. Deriving samples from cases that are perceived as unusual or rare such as exploring the reasons for corporate failure by interviewing executives that have been fired by shareholders.

    Critical case sampling focuses on specific cases that are dramatic or very important.

    Heterogeneous or maximum variation sampling relies on researcher’s judgment to select participants with diverse characteristics. This is done to ensure the presence of maximum variability within the primary data.

    Homogeneous sampling focuses on “focuses on one particular subgroup in which all the sample members are similar, such as a particular occupation or level in an organization’s hierarchy”[2]

    Theoretical sampling is a special case of purposive sampling that is based on an inductive method of Grounded Theory.

Application of Purposive Sampling (Judgment Sampling): an Example

Suppose, your dissertation topic has been approved as the following:

A study into the impact of tax scandal on the brand image of Starbucks Coffee in the UK

If you decide to apply questionnaire primary data collection method with use of purposive sampling, you can go out to Oxford Street and stop what seems like a reasonable cross-section of people in the street to survey.

Another example. Your research objective is to determine the patterns of use of social media by global IT consulting companies based in the US. Rather than applying random sampling and choosing subjects who may not be available, you can use purposive sampling to choose IT companies whose availability and attitude are compatible with the study.

Advantages of Purposive Sampling (Judgment Sampling)

    Purposive sampling is one of the most cost-effective and time-effective sampling methods available

    Purposive sampling may be the only appropriate method available if there are only limited number of primary data sources who can contribute to the study

    This sampling technique can be effective in exploring anthropological situations where the discovery of meaning can benefit from an intuitive approach

Disadvantages of Purposive Sampling (Judgment Sampling)

    Vulnerability to errors in judgment by researcher

    Low level of reliability and high levels of bias.

    Inability to generalize research findings

REFERENCES  

https://research-methodology.net/sampling-in-primary-data-collection/purposive-sampling/