Phenomenological Approach in the Qualitative Study: Data Collection and Saturation

Abstract

The study aims to explore the phenomenological study method, data collection procedures and analysis, followed by how and in which position the saturation is achieved. Phenomenological approach has been employed to explore the perceptions of stakeholders through sharing their experiences. Using snowball sampling procedures, data have been collected from 10 respondents through face-to-face semi-structured interviews. For the data analysis, this study has adopted the inductive thematic approach. In the interview process, the researcher focused on the respondents’ understanding of the commercial banks' money lending activity. The findings of the study show that different stakeholders have a different perception on commercial banks' money lending activity. Respondents have a common understanding but explained it differently as they experienced it. The common academic background of the respondents plays a role in the common understanding and thus, it helps to achieve the data saturation point for each research question separately. Money creation through the commercial banks' money lending activity has a potential threat of financial crisis but the strong role of Bank Negara Malaysia (BNM) can ease this tension. This perception comes from the data saturation point on the basis of the respondents understanding on the research phenomenon. The study has potential implications on the qualitative research method, and phenomenological study method, data collection procedures and analysis followed by how and on which position the saturation is achieved. The current study may have several contributions to the existing literature in qualitative research. This study may assist researchers on how to reach the saturation point for heterogeneous data. Step by step process on data selection and interview approach can guide to achieving the data saturation point. Future research can take this study as an input to develop the qualitative research model for the heterogeneous data. In addition, a follow-up interview approach may help to get comprehensive data collection that can also assist to achieve data saturation point.