I introduce large language models (LLMs) by unpacking what they are, how they work, and why they matter for business researchers. Then, I turn to local LLMs—models you can run on your own machine—highlighting their advantages in privacy, cost, and flexibility. To encourage action, I walk through how to get started. I argue that local LLMs empower researchers to experiment, prototype, and explore ideas—without relying solely on commercial platforms.
IDeaS 2025, 2025-05-01, University of Ottawa
Jason T. Kiley is an Assistant Professor at Clemson University. His research examines the interplay of audience perceptions of firms, impression management, and their associations with outcomes, including recent publications in Journal of Management, Academy of Management Journal, and Strategic Management Journal. As part of his work, he works to advance the use of software to increase the range, efficiency, and rigor of conducting empirical research. He is a co-organizer of the annual AOM Content Analysis PDW, and his published and in-progress work often uses state-of-the-art content analysis techniques, including recent work with large language models.