Request Username
Can't sign in? Forgot your username?
Enter your email address below and we will send you your username
To: INFORMS Board
Re: Annual Report for Operations Research (OPRE) Journal
From: Amy R. Ward, Editor-in-Chief (EiC)
Date: October 7, 2025
The Operations Research (OPRE) journal is a flagship journal for the INFORMS community. Its mission is to be the leading platform for innovative and impactful research in the field of Operations Research. My first priority as Editor-in-Chief (EiC) is to preserve and enhance this standing.
My term as EiC began January 1, 2024. This is the 2nd Annual Report I am writing.
One main focus has been to establish the process for data and code review (see here for procedures). The main challenge is that there is not enough manpower to do a full data and code review for every paper. There is a focus on ensuring a comprehensive review. A full and comprehensive review requires subject matter expertise, and so is hard to outsource. The solution is to prioritize papers for data and code review by having the Area Editors flag papers whose contribution is heavily on the empirical side.
The end result for papers that successfully go through data and code review is:
The results of the data and code review process for the first and second papers reviewed are available here and here. The third paper to complete the process should have a similar page available soon.
There are six more papers currently going through the process. The slow start is purposeful, while we continue to develop the best practices and procedures.
The requirement for papers that do not go through code and data review is that the code and data must be made available to readers.
To provide authors with information on how to best set up their data and code files to allow others to reproduce their results, the journal is the lead organizer for the Workshop on Replicability at INFORMS journals, in conjunction with Journal on Computing, Journal on Data Science, and Management Science.
One main struggle for establishing the process for data and code review has been limited ScholarOne functionality, and, in particular, the inability to assign 2 Area Editors to one paper. The current situation requires outside files to track the papers prioritized for data and code review, and that is not a good long-term solution.
A second focus is reviewer recognition. Timely reports from reviewers that are of strong quality are essential to the reputation and standing of the journal. In 2024, we re-established reviewer awards (see here for awardees). We further published the names of all 2024 reviewers here. The plan is to continue this every year.
Strong reviewing is a necessary condition to become an Associate Editor for the journal. This is on my mind to think more about the process for selecting Associate Editors.
The rise of LLMs -- both for doing research and for reviewing papers -- is a current challenge for the journal. The use of LLMs, on both the author side and the reviewer side, is happening, whether we like it or not. The question is what this means for the journal and how the journal should respond. One main worry is that the time to produce an LLM-generated proof is short but the time required to ensure correctness and find errors is long. The current review system may not be equipped to handle this. I am open to hearing ideas for how to handle. There is an excellent blog discussion here. I firmly believe that human intellectual energy is essential to the paper writing and review process.
The context and challenge category continues to be a struggle. We have identified three potential such papers. The current situation is that the category is only for invited papers. I would like to see how the current three papers do before deciding whether to open or close this category.
I continue to think about how to better publicize the journal, but do not have anything helpful to report in this regard.
Below are some statistics for the journal, as well as some commentary from me:
| Area / Area Editor | # of Manuscripts Handled Since 1/1/2025 |
|---|---|
| Decision Analysis | |
| David Brown | 30 |
| Ilia Tsetlin | 41 |
| Energy and Environment | |
| Golbon Zakeri | 28 |
| Financial Engineering | |
| Agostino Capponi | 31 |
| Xuedong He | 33 |
| Machine Learning and Data Science | |
| Xi Chen | 74 |
| Dennis Zhang | 48 |
| Markets, Platforms, and Revenue Management | |
| Rene Caldentey | 42 |
| Ilan Lobel | 58 |
| Defense and Security | |
| Cole Smith | 16 |
| Operations and Supply Chain | |
| Rouba Ibrahim | 59 |
| Francis de Vericourt | 51 |
| Optimization | |
| Samuel Burer | 95 |
| Dan Iancu | 55 |
| Real-World OR Innovations | |
| Turgay Ayer | 16 |
| Societal Impact | |
| Andrew Schaefer | 31 |
| Simulation | |
| Sandeep Juneja | 29 |
| Stochastic Models | |
| Raman Randhawa | 35 |
| Neil Walton | 57 |
| Transportation | |
| Jose Correa | 58 |
| Data, Software, and Computation | |
| Ted Ralphs* | 9* |
*This Area was first established in January 2024. Ted is leading the creation of the code and data review standards. We (Ted and I) are doing this slowly, and thinking carefully about best practices.
| Year | Submissions | Acceptances |
|---|---|---|
| 2018 | 596 | 86 |
| 2019 | 493 | 109 |
| 2020 | 656 | 105 |
| 2021 | 649 | 83 |
| 2022 | 515 | 126 |
| 2023 | 534 | 118 |
| 2024 | 642 | 109 |
| 2025 Q1-3 | 741 | 102 |
| Year | Acceptance Rate |
|---|---|
| 2018 | 16.0% |
| 2019 | 20.9% |
| 2020 | 15.7% |
| 2021 | 19.3% |
| 2022 | 22.2% |
| 2023 | 20.2% |
| 2024 | 19.9% |
| 2025 Q1-3 | 17.3% |
| Year | Months |
|---|---|
| 2018 | 8.60 |
| 2019 | 13.24 |
| 2020 | 10.73 |
| 2021 | 15.73 |
| 2022 | 8.91 |
| 2023 | 12.93 |
| 2024 | 7.39 |
| 2025 Q1-3 | 6.00 |
| Year | Mean (Days) | Median (Days) |
|---|---|---|
| 2018 | 139.0 | 121.0 |
| 2019 | 145.4 | 129.0 |
| 2020 | 164.6 | 139.0 |
| 2021 | 146.8 | 130.0 |
| 2022 | 154.1 | 135.5 |
| 2023 | 160.2 | 143.0 |
| 2024 | 139.9 | 125.0 |
| 2025 Q1-3 | 147.2 | 136.0 |
*All original submissions and resubmissions sent for external review with first decision dates within the reporting period.
| Year | Mean (Days) | Median (Days) |
|---|---|---|
| 2018 | 495.7 | 413.0 |
| 2019 | 527.2 | 455.0 |
| 2020 | 479.5 | 419.0 |
| 2021 | 495.1 | 441.0 |
| 2022 | 489.2 | 474.0 |
| 2023 | 561.5 | 550.5 |
| 2024 | 529.0 | 434.0 |
| 2025 Q1-3 | 545.3 | 489.0 |
*All original submissions, resubmissions, and revisions sent for external review with final decisions within the reporting period.
| Year | OPRE | Operations Research & Management Science (SCIE) | Management (SSCI) |
|---|---|---|---|
| 2017 | 2.263 | 2.472 | 2.636 |
| 2018 | 2.604 | 2.799 | 2.983 |
| 2019 | 2.430 | 3.176 | 3.291 |
| 2020 | 3.310 | 4.348 | 5.022 |
| 2021 | 3.924 | 4.971 | 5.653 |
| 2022 | 2.7 | 5.1 | 5.7 |
| 2023 | 2.2 | 4.7 | 4.2 |
| 2024 | 2.6 | 5.2 | 4.4 |
| Year | Pages |
|---|---|
| 2018 | 1788 |
| 2019 | 1812 |
| 2020 | 1962 |
| 2021 | 2025 |
| 2022 | 3676 |
| 2023 | 2398 |
| 2024 | 2816 |
| 2025 Q1-3 | 2908 |
| Year | Downloads |
|---|---|
| 2018 | 165051 |
| 2019 | 223098 |
| 2020 | 231970 |
| 2021 | 259972 |
| 2022 | 357964 |
| 2023 | 272351 |
| 2024 | 319416 |
| 2025 | 334623 |