Generative AI and Empirical Research Methods in Operations Management
Generative Artificial Intelligence (Gen-AI) is arguably the fastest-adopted technology in history (Mariani and Dwivedi 2024). Like past transformative technologies—such as computers and the Internet—Gen-AI brings new opportunities and challenges to research. However, its distinctive features may result in an adoption pattern and impact that differ from those of earlier technologies. Anthony et al. (2023) offered a novel perspective on studying AI. Traditionally, technologies are viewed either as tools to improve performance or as mediums to enhance collaboration; however, AI can be seen as a counterpart or an agent interacting with human agents (c.f. Bendoly et al. 2024; Angelopoulos et al. 2023). Along these lines, the popular press has already labeled Gen-AI models as a “superhuman research assistant” in the research process (The Economist 2023). With the formation of such hybrid teams in research, it is more critical than ever to define the roles of team members.
Authors
- Matthias Holweg (ORCID: https://orcid.org/0000-0001-9403-1681)
- Guangzhi Shang (ORCID: https://orcid.org/0000-0002-3287-6520)
- Jason Bennett Thatcher (ORCID: https://orcid.org/0000-0002-7136-8836)
- Ajay Kumar (ORCID: https://orcid.org/0000-0002-8187-4169)
- Jan C. Fransoo (ORCID: https://orcid.org/0000-0001-7220-0851)
- Timofey Shalpegin (ORCID: https://orcid.org/0000-0003-2368-8541)
- Benn Lawson (ORCID: https://orcid.org/0000-0002-8489-1984)
- Tyson R. Browning (ORCID: https://orcid.org/0000-0002-9089-1403)
Institutions
- Florida State University (US)
- Texas Christian University (US)
- University of Colorado Boulder (US)
- Tilburg University (NL)
- University of Oxford (GB)
- Prince Mohammad Bin Salman College of Business and Entrepreneurship (SA)
- Science Oxford (GB)
- École de management de Lyon (FR)
- Arizona State University (US)
Publication Details
- Journal
- Journal of Operations Management
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1002/joom.1371
- Citations
- 7
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 15.99