Problem areas of determining the sample size in qualitative research: a model proposal

Abstract

Purpose

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Design/methodology/approach

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

Findings

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

Originality/value

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

Citation

Tutar, H., Şahin, M. and Sarkhanov, T. (2023), "Problem areas of determining the sample size in qualitative research: a model proposal", Qualitative Research Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/QRJ-06-2023-0099