Multiple Case Study Data Analysis for Doctoral Researchers in Management and Leadership

Multiple cases may be conducted for several reasons: they extend emergent theory, fill theoretical categories, provide examples of polar types, or replicate previously selected cases to discover new theoretical directions. However, the qualitative data analysis process for multiple case studies is a multi-step process that can be challenging for doctoral researchers. This article thus outlines the qualitative data analysis process for a doctoral-level multiple case study in management and leadership, including conducting descriptive coding and cross-case synthesis and ensuring the trustworthiness of multiple case study results. The descriptive coding strategy analyzes the raw data collected to assign meaning to the data segment, allowing Using the descriptive coding strategy allows for the emergence of words and phrases for further categorization and thematic analysis. Cross-case synthesis involves comparing and contrasting cases rather than just analyzing individual cases for content analysis. Combined with within-case analysis, it offers a more consistent platform for generating theoretical propositions and extending theory. Finally, four quality criteria of trustworthiness recommended by seminal qualitative methodologists Lincoln and Guba (1986) are reviewed, along with the preferred methods and the authors’ recommendations to strengthen the trustworthiness of a multiple case study. Case study researchers will continue to play a pivotal role in offering a voice as to how people, places, and events continually shape and reshape today’s business and technology transactions across nations’ regional and local communities