[Logprofs] Journal of Business Logistics AI-Integrated Research STF

[Rodney Thomas]

Journal of Business Logistics Special Topic Forum

AI-Integrated Research: A Field Experiment in SCM Knowledge Production
The Journal of Business Logistics invites submissions to a Special Topic Forum (STF) on AI-integrated supply chain management research.
Artificial intelligence is rapidly transforming supply chain management practice. As scholars increasingly examine how AI alters operational decision making, far less attention has been devoted to how these tools may reshape the production of supply chain knowledge itself. It is both natural and necessary to examine AI’s influence on how supply chain research is conducted, developed, and evaluated. Scholars and journals now play a central role in determining how AI will shape the future of academic research.
Authors submitting to this STF are explicitly allowed to use AI in the development of their empirical research. Authors may use AI for ideation, theorizing, literature synthesis, writing, coding, simulation, data analysis support, and methodological design. The only non-negotiable boundary is that the unchecked fabrication or falsification of empirical data is strictly prohibited. Beyond that constraint, authors have broad discretion in how they integrate AI into the research process. Authors do, of course, remain fully responsible for the integrity, originality, and accuracy of their work.
This STF differs from regular submissions in two important ways. First, it explicitly allows AI use across the research process, making visible what is often implicit or unevenly disclosed. Second, it invites reflectivity. Authors are required to explain how AI was used. Thus, the research process itself becomes partially examinable as an object of scholarly inquiry.
The EIC Team will treat this STF as a subject of disciplined experimentation. We seek to observe AI-integrated research, and thereby provide systematic insight into how generative technologies reshape theorizing and empirical research in supply chain management. This initiative positions JBL as a laboratory for responsible, transparent, and rigorous AI-integrated supply chain scholarship.
Submission Scope
Any topic within the domain of supply chain management is welcome. However, submissions must meet JBL’s high standards for substantive insight, relevance to supply chain management, theoretical contribution, and methodological rigor. Polish and execution alone will not substitute for meaningful intellectual insights.
Comprehensive AI Disclosure Requirement
For this STF, AI Use Statements are not merely compliance disclosures. They are an integral component of the scholarly initiative. Authors will be required to document their use of AI and their associated evaluations by completing a structured survey that captures:

  *   The nature and intensity of AI usage
  *   Tools and prompting approaches employed
  *   Stages of the research process affected
  *   Instances where AI outputs were rejected or substantially modified
  *   Points at which human judgment overruled AI-generated suggestions
  *   Authors’ reflections on benefits, limitations, and unexpected behaviors

These survey responses will not influence editorial decisions. The data will be anonymized for editorial research and will be stored separately from the manuscript file.
This documentation will enable systematic analysis of AI integration patterns and their relationship to review outcomes. As part of an accompanying editorial study, we will examine patterns in AI usage, reviewer responses, and manuscript development trajectories. Longer-term citation and impact patterns will be evaluated as data become available.
What We Hope to Learn
Through this STF, JBL seeks to better understand:

  *   Where AI meaningfully enhances theoretical clarity and rigor
  *   Where it risks superficiality or intellectual homogenization
  *   How AI affects hypothesis generation and model specification
  *   Whether AI-integrated research differs in novelty, coherence, or impact
  *   How reviewers evaluate AI-integrated work

The lessons learned will inform future editorial policy and contribute to broader conversations about responsible AI use in scholarly research.
Submission and Review Process
The STF will follow a two-step submission and review process:

  1.
Proposal submission:
Authors must submit a research proposal. The proposal should clearly state the research question(s), summarize the (expected) theoretical contributions and managerial interest, and outline the proposed methodological approach(es) and data source(s). In addition, the proposal will require a completed survey detailing in what way(s) the authors anticipate using AI tools.

Proposals will be reviewed by the Editors-in-Chief with a focus on evaluating each proposal’s fit with JBL’s mission of publishing high-quality empirical supply chain management research that meaningfully contributes to theory, literature, and practice. Authors of proposals that are deemed to potentially meet these expectations will be invited to submit full-length manuscripts. Such invitations do not present guarantees that the papers will ultimately be published—each full-length paper will undergo a full, double-blind peer review.


  1.  Manuscript submission and review:

All papers will undergo full peer review consistent with JBL standards. Reviewers will be informed that the manuscript is part of the STF and that AI use is permitted within the stated guidelines. But they will not have access to the authors’ AI disclosures. Reviewers will be instructed to evaluate submissions independent of the extent of any perceived AI integration.

Timeline

  *   Initial proposal submission window: July 1st – July 31st (2026).
  *   Proposal decisions: September 1, 2026
  *   Full paper submissions due prior to: February 1, 2027
  *   Standard review process initiated after paper submission




Rodney Thomas, Ph.D.

Co-Editor-In-Chief, Journal of Business Logistics

Department of Supply Chain Management

Walton College of Business

University of Arkansas


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.mit.edu/pipermail/logprofs/attachments/20260316/a57b3398/attachment-0001.htm>