The Communication, Digital Technology, and Organization (CTO) Division of the Academy of Management (AOM) is to invite you to a series of online workshops on computational methods, with a particular focus on large language models (LLM). These sessions introduce emerging computational approaches and practical tools for analyzing large-scale textual data and generating theory-relevant insights across a range of organizational contexts.
Each workshop session will last approximately 150 minutes and combine conceptual introductions with hands-on demonstrations designed to help participants understand how these methods can be implemented in their own research. The sessions will also include interactive discussions and Q&A, providing opportunities for participants to engage with instructors on methodological challenges, best practices, and emerging applications of LLM-based approaches in management and organizational scholarship. Capacity is limited. Registration is open to all, but priority will be given to AOM members if the limit is reached.
Date: 28 April 2026
Format: Online on Zoom (Register to receive the link)
Prerequisites: Basic familiarity with Python is expected.
Workshop 1: Applying Large Language Models to Management Research: Methods and Practice
Time: 01:00 PM - 03:30 PM BST (08:00 AM - 10:30 AM EDT)
Instructor: Wen Zhang, Lecturer in Business Analytics, University of Bristol Business School
Description: This session introduces how Large Language Models (LLMs) can be applied to management research. It begins with a conceptual overview of how LLMs have evolved from traditional NLP methods and what key tasks they can perform for researchers, including text classification, information extraction, text embedding, and qualitative coding. The session then showcases recent publications from top journals to illustrate how LLMs have been applied across management domains such as finance, operations, information systems, and social science research. Attendees will also participate in a hands-on Python demonstration covering practical examples using LLM APIs, designed to be accessible for those with limited programming experience. The session concludes with a discussion of limitations and boundaries, including reproducibility, validity, bias, and ethical considerations.
Workshop 2: Dissecting Corporate Culture with Large Language Models
Time: 04:00 PM - 06:30 PM BST (11:00 AM - 01:30 PM EDT)
Instructor: Feng Mai, Henry B. Tippie Research Fellow and Associate Professor in Business Analytics, University of Iowa
Description: This session offers a deep dive into computational approaches for extracting structured, theory-informed knowledge about corporate culture and organizational values from large-scale text. It introduces two methodological advances: (1) Semantic Projection with Active Retrieval (SPAR), a framework for computationally intensive theory construction that bridges theoretical concepts and unstructured text; and (2) the use of generative AI as reasoning agents for structured information extraction and knowledge graph construction. Participants will gain hands-on experience with Python code applied to real data and structured LLM prompts.
We look forward to welcoming you!
The Organizers:
Hamid Khobzi
Bei Yan
Romilla Syed
Roberta Bernardi
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Roberta Bernardi
CTO Division Chair-Elect
roberta.bernardi@bristol.ac.uk------------------------------