What are some general strategies for sample selection? Why the right selection of sampling method is so important for any research?

There are two broad classifications of sampling procedures: random and non random sampling. Both of these methods have several techniques and researcher select a technique that is most pertinent to their accounting research ideas. Sometimes there are more than one sampling techniques that seem like suitable for the research. How can one reach to the conclusion that this particular technique is most suitable for their research. The researchers utilize their knowledge of principles of sampling to decide about the strategy for sample selection.

Sample selection strategies
Kemper and colleagues (2003) identify seven such principles:

Logically appropriate
The sampling strategy should stem logically from the conceptual framework as well as the research questions being addressed by the study. It needs to support and answer the research questions and align with the conceptual framework.

The sampling technique should be appropriate for the aims and goals of the research. In case, one sampling strategy cannot fulfill the aims of the research you can combine two strategies to get an appropriate sample.

Thorough database
The sample should be able to generate a thorough database on the type of phenomenon under study. The sample size should be enough so that it can represent the sampling frame or the population from which the sample is taken. Too small sample may not represent the population while too large can become difficult to handle. Therefore, the right size of the sample is very important.

Clear inferences
The sample should at least allow the possibility of drawing clear inferences and credible explanations from the data. Again the sample size should justify the population size. The sampling technique should yield unbiased and precise inferences. And this is only possible when you have selected the right sampling technique and used the right procedures. As we increase the sample size we get more precise inferences. Of course, populations are large and one has to reach a limit where further growing the sample size may make it impossible to collect data and make inferences.

Ethical
The sampling strategy must be ethical. Data protection and confidentiality issues may arise if the researcher did not keep the personal information hidden. Also in non probability research the choice and selection of sample should be based on theoretical reasons not on some personal reasons.

Feasible
The sampling plan should be feasible. The researcher should make sure that the sampling technique is feasible for the available resources.

Generalizable
The sampling plan should allow the researcher to transfer/generalize the conclusions of the study to other settings or populations. Generalizability is an important aspect of research guides and your sampling technique can highly effect it. The right selection of the sample can highly improve the generalizability of research.

Practical
The sampling scheme should be as efficient as practical. Practicality should be considered because otherwise you can get stuck in the midst of research with too much stress.