A study note on Grounded theory's ideas of qualitative data analysis: for MBA students

A study note on Grounded theory's ideas of qualitative data analysis: for MBA students (information from perplexity.ai)

My question 1: "What are the main ideas of grounded theory with reference to qualitative data analysis for MBA dissertation projects?"

The reply: "The main ideas of grounded theory in relation to qualitative data analysis for MBA dissertation projects can be summarized as follows:

1. Inductive Theory Development from Data
   Grounded theory is an inductive research approach where theories are developed directly from the data collected, rather than starting with a hypothesis to test. This contrasts with traditional deductive research, emphasizing theory emergence grounded in real-world data such as interviews, observations, and documents123.

2. Iterative Data Collection and Analysis
   Data collection and analysis occur simultaneously in a cyclical process. Researchers collect some data, analyze it, and then use insights gained to guide further data collection through theoretical sampling. This iterative loop continues until theoretical saturation is reached—when no new insights emerge from additional data134.

3. Constant Comparative Method
   A core analytical technique is the constant comparison of new data with previously collected data, codes, and categories. This ongoing comparison helps identify patterns, contradictions, and leads to the abstraction of concepts and categories that form the basis of the emerging theory24.

4. Theoretical Sampling
   Rather than predefining all participants or data sources, grounded theory uses theoretical sampling where decisions about what data to collect next are driven by the evolving theory. This allows exploration of gaps and refinement of emerging categories4.

5. Theoretical Saturation
   Data collection ends when additional data no longer provide new information or insights, indicating that the theory is well developed and grounded in the data14.

6. Memoing and Coding
   Throughout the process, researchers write memos to capture insights, reflections, and analytic thoughts. Coding is done in phases (e.g., substantive and theoretical coding) to organize data into meaningful categories that build toward theory24.

7. Empirical Grounding and Practical Relevance
   Theories generated are closely tied to empirical data, ensuring relevance and applicability to real-world contexts, which is particularly valuable for MBA dissertation projects focused on business phenomena2.

8. Flexibility and Depth
   Grounded theory allows flexibility to adapt as new insights emerge, facilitating deep understanding of participants’ perspectives and complex social processes without being constrained by preconceived frameworks245.

9. Avoidance of Confirmation Bias
   Because data collection and analysis are intertwined and the theory emerges from the data itself, grounded theory helps protect against confirmation bias and preconceived notions influencing the findings1.

For MBA dissertation projects, grounded theory offers a systematic yet flexible qualitative methodology to explore complex business phenomena, generate new theories grounded in empirical data, and provide rich, context-specific insights that can inform practice and further research.

In summary, grounded theory in qualitative data analysis involves starting with data, using iterative cycles of data collection and analysis, employing constant comparison and theoretical sampling, and developing theory grounded in empirical evidence until saturation is reached—all supported by detailed coding and memoing processes12345."

My question 2: "Could you further illustrate the ideas with reference to the dissertation topic of "to explore how the firm's work-from-home policy affect gen z employees' organizational commitment for 2 Hong Kong audit firms in 2025"?"

The reply: "To illustrate the main ideas of grounded theory with reference to your dissertation topic—"to explore how the firm's work-from-home policy affects Gen Z employees' organizational commitment for 2 Hong Kong audit firms in 2025"—here is how the grounded theory approach can be applied:

1. Inductive Theory Development from Data

Instead of starting with a fixed hypothesis about how WFH policies impact Gen Z’s organizational commitment, you would collect qualitative data (e.g., interviews or focus groups with Gen Z employees at the two audit firms) and allow themes and a theory to emerge from this data. For example, you might discover that professional isolation or work–family balance are key factors influencing commitment, as suggested by recent studies on teleworking and organizational commitment5.

2. Iterative Data Collection and Analysis

You would begin by interviewing a few Gen Z employees and analyze their responses. Based on emerging insights, you might then decide to interview more employees who have different experiences with WFH (e.g., varying levels of remote work or different team structures) to explore emerging concepts in depth. This iterative cycle continues until no new themes about WFH and commitment emerge (theoretical saturation).

3. Constant Comparative Method

As you collect data, you continuously compare new interview transcripts with previous ones to identify similarities and differences in how employees describe their commitment and experiences with WFH. For instance, you might compare how perceptions of supervisor support or social isolation vary and relate to commitment levels15.

4. Theoretical Sampling

You would purposefully select participants to fill gaps in your emerging theory. For example, if early data suggest that employees with high task interdependence experience WFH differently, you might specifically seek out employees in roles with varying task interdependence to refine your understanding3.

5. Theoretical Saturation

Data collection would end when additional interviews no longer provide new insights into how WFH affects organizational commitment among Gen Z employees in these firms.

6. Memoing and Coding

Throughout your research, you would write memos capturing your reflections on emerging categories such as "professional isolation," "work–family balance," or "perceived organizational support." Coding would be done in stages, starting with open coding to identify initial concepts, then axial coding to relate categories, and finally selective coding to integrate these into a coherent grounded theory explaining the impact of WFH on organizational commitment15.

7. Empirical Grounding and Practical Relevance

Your resulting grounded theory would provide a context-specific explanation of how WFH policies influence Gen Z employees’ commitment in Hong Kong audit firms, potentially highlighting unique cultural or industry factors. This theory could guide HR practices to improve commitment through tailored WFH policies.

Example Themes You Might Discover

• Identity and Commitment Trajectories: Gen Z employees may initially have transactional views of their job but develop relational commitment influenced by WFH experiences and supervisor support1.

• Professional and Social Isolation: WFH might increase feelings of isolation, negatively impacting organizational identification and commitment, moderated by task interdependence and communication quality35.

• Work–Family Balance: Positive WFH experiences that improve work–family balance may enhance job satisfaction and thus organizational commitment5.

• Organizational Support: Perceptions of how the firm supports employees during WFH, including communication and flexibility, could be crucial for maintaining commitment5.

In sum, using grounded theory for your dissertation means you would systematically collect and analyze qualitative data from Gen Z employees in the two audit firms, allowing a theory about the impact of WFH on organizational commitment to emerge grounded in their lived experiences. This approach provides rich, actionable insights tailored to your specific research context."

A collection of blog notes on using chatgpt for research purpose.