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Can ChatGPT perform a  grounded theory approach to do risk analysis? An empirical study
Can ChatGPT perform a  grounded theory approach to do risk analysis? An empirical study
Can ChatGPT perform a  grounded theory approach to do risk analysis? An empirical study
Can ChatGPT perform a  grounded theory approach to do risk analysis? An empirical study
20Dec
Seminar Calendar, Information and Innovation Management

Can ChatGPT perform a grounded theory approach to do risk analysis? An empirical study

20 Dec 2024 | 10:30 a.m. — 12:00 noon
KK 1121, K. K. Leung Building, HKU
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SPEAKER

Prof. Yufei Yuan
Professor of Information Systems
DeGroote School of Business
McMaster University

ABSTRACT

Grounded theory is a widely used scientific method for generating theories from qualitative data analysis. However, it is often time-consuming and requires professional training. Generative artificial intelligence, such as ChatGPT, excels in understanding and analyzing text, making it a valuable tool for qualitative research. This research proposes a novel approach to guide ChatGPT using the grounded theory method for qualitative data analysis and to design rigorous metrics for evaluating its performance. Using risk analysis as a case study, we compare ChatGPT’s results with those obtained through manual methods. Our findings show that, with expert guidance, ChatGPT can effectively perform the grounded theory method, achieving results comparable to those of human analysts. To maximize its potential, researchers should properly guide ChatGPT in performing required tasks, rigorously evaluate its outputs, and ensure high-quality results. This approach can significantly enhance the efficiency and quality of qualitative data analysis.

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Can ChatGPT perform a  grounded theory approach to do risk analysis? An empirical study
About Speaker
Prof. Yufei Yuan

Professor of Information Systems | DeGroote School of Business | McMaster University

Can ChatGPT perform a grounded theory approach to do risk analysis? An empirical study
20 Dec 202410:30 a.m. — 12:00 noon
KK 1121, K. K. Leung Building, HKU
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