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A practical guide to implementing ChatGPT as a secondary coder in qualitative research

Eva Blondeel (UGent) , Patricia Everaert (UGent) and Evelien Opdecam (UGent)
(2025) INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS. 56.
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Abstract
Analyzing interview data provides in-depth insights into qualitative research topics, but is often a time-consuming and costly process. This research aims to enhance this process by leveraging transformative technologies influencing the accounting field, like ChatGPT. ChatGPT is capable of generating human-like text and performing text-based analyses by using a pre-trained model. Specifically, this research illustrates ChatGPT's role as a secondary coder in deductive qualitative accounting research, analyzing interview transcripts using content analysis with a predefined coding scheme. Data was collected through semi-structured interviews with 36 business economics students. First, the primary researcher manually analyzed the data using a deductive approach. Next, a second human researcher and ChatGPT (ChatGPT-4o Plus) were appointed as secondary coders to independently verify and validate the coding. The paper demonstrates ChatGPT's potential to assist in coding interview transcripts, emphasizing its role as a supplementary tool in qualitative research. The coding results from both secondary coders were compared with those of the primary human coder, revealing over 99% agreement for both secondary coders. In addition, a step-by-step illustration, best practices, prompts, and critical reflections are shared. This study serves as a foundational step in understanding and leveraging ChatGPT's use in the analysis of interview transcripts.
Keywords
ChatGPT, Qualitative research, Interview analysis, Accounting

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MLA
Blondeel, Eva, et al. “A Practical Guide to Implementing ChatGPT as a Secondary Coder in Qualitative Research.” INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, vol. 56, Elsevier BV, 2025, doi:10.1016/j.accinf.2025.100754.
APA
Blondeel, E., Everaert, P., & Opdecam, E. (2025). A practical guide to implementing ChatGPT as a secondary coder in qualitative research. INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, 56. https://doi.org/10.1016/j.accinf.2025.100754
Chicago author-date
Blondeel, Eva, Patricia Everaert, and Evelien Opdecam. 2025. “A Practical Guide to Implementing ChatGPT as a Secondary Coder in Qualitative Research.” INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS 56. https://doi.org/10.1016/j.accinf.2025.100754.
Chicago author-date (all authors)
Blondeel, Eva, Patricia Everaert, and Evelien Opdecam. 2025. “A Practical Guide to Implementing ChatGPT as a Secondary Coder in Qualitative Research.” INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS 56. doi:10.1016/j.accinf.2025.100754.
Vancouver
1.
Blondeel E, Everaert P, Opdecam E. A practical guide to implementing ChatGPT as a secondary coder in qualitative research. INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS. 2025;56.
IEEE
[1]
E. Blondeel, P. Everaert, and E. Opdecam, “A practical guide to implementing ChatGPT as a secondary coder in qualitative research,” INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, vol. 56, 2025.
@article{01KEGTKFVYWS608430VYRPBMNQ,
  abstract     = {{Analyzing interview data provides in-depth insights into qualitative research topics, but is often a time-consuming and costly process. This research aims to enhance this process by leveraging transformative technologies influencing the accounting field, like ChatGPT. ChatGPT is capable of generating human-like text and performing text-based analyses by using a pre-trained model. Specifically, this research illustrates ChatGPT's role as a secondary coder in deductive qualitative accounting research, analyzing interview transcripts using content analysis with a predefined coding scheme. Data was collected through semi-structured interviews with 36 business economics students. First, the primary researcher manually analyzed the data using a deductive approach. Next, a second human researcher and ChatGPT (ChatGPT-4o Plus) were appointed as secondary coders to independently verify and validate the coding. The paper demonstrates ChatGPT's potential to assist in coding interview transcripts, emphasizing its role as a supplementary tool in qualitative research. The coding results from both secondary coders were compared with those of the primary human coder, revealing over 99% agreement for both secondary coders. In addition, a step-by-step illustration, best practices, prompts, and critical reflections are shared. This study serves as a foundational step in understanding and leveraging ChatGPT's use in the analysis of interview transcripts.}},
  articleno    = {{100754}},
  author       = {{Blondeel, Eva and Everaert, Patricia and Opdecam, Evelien}},
  issn         = {{1467-0895}},
  journal      = {{INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS}},
  keywords     = {{ChatGPT,Qualitative research,Interview analysis,Accounting}},
  language     = {{eng}},
  pages        = {{21}},
  publisher    = {{Elsevier BV}},
  title        = {{A practical guide to implementing ChatGPT as a secondary coder in qualitative research}},
  url          = {{http://doi.org/10.1016/j.accinf.2025.100754}},
  volume       = {{56}},
  year         = {{2025}},
}
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