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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI and Empirical Research Methods in Operations Management

Matthias Holweg, Guangzhi Shang, Jason Bennett Thatcher, Ajay Kumar et al.
7 citations
Journal of Operations Management
Big Data and Business Intelligence
15.99
article

Generative AI and Empirical Research Methods in Operations Management

Matthias Holweg, Guangzhi Shang, Jason Bennett Thatcher, Ajay Kumar, Jan C. Fransoo, Timofey Shalpegin, Benn Lawson, Tyson R. Browning
article en
7 citations

Abstract

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.

Journal of Operations ManagementVol. 71(5)
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)
Openalex Percentile: Top 1%
Big Data and Business Intelligence
15.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.