9. Qualitative Method Design and Data Analysis

This chapter delves into the world of qualitative data analysis, exploring various instruments and methods used to understand human experiences and social phenomena. It begins by introducing the philosophy of interpretivism, which underpins qualitative research, and highlights the importance of contextuality in understanding individuals' experiences. The chapter then discusses key characteristics of the qualitative approach, including its subjective nature, emphasis on reflexivity, and inductive approach. It also explores different types of data collection methods, such as interviews and focus groups, and presents examples relevant to management research. The chapter further discusses the process of qualitative data analysis, including data organisation, familiarisation, coding, and interpretation. It also highlights the advantages and disadvantages of qualitative approaches, such as their ability to capture the intricate nature of human experiences and their susceptibility to researcher bias. The chapter concludes by discussing the art and evolving science of qualitative interpretation, highlighting the role of AI in enhancing qualitative research. Additionally, the chapter explores various qualitative methods, such as thematic analysis, grounded theory, narrative analysis, and phenomenological analysis, and their applications in management research. It also discusses the process of each method, including data collection, coding, and interpretation. The chapter concludes by highlighting the importance of qualitative research in understanding complex phenomena and its applications in academic and practical settings.