At Taylor & Francis, we work hard to develop our electronic peer review systems. We want to improve and enhance the quality of peer review. And we want to make it easier for you to find new reviewers.
Recruiting suitable new peer reviewers for your journal can sometimes be a difficult and time-consuming task. Our guide to finding reviewers has a range of tried-and-tested tips to help. These include, for example, getting leads from the article’s references list and using the networks of your Editorial Board members.
To supplement these more traditional methods, we’re supporting the introduction of digital solutions that will make it simpler to widen your pool of reviewers and help you find the right experts for every paper. These tools use Artificial Intelligence (AI) to match submissions with suitable reviewers, saving you time and improving the peer review experience for authors.
Journals which use the ScholarOne Manuscripts submission system have the Web of Science™ Reviewer Locator enabled.
Here’s how it works:
Please remember that the tool uses AI and that no human has checked the results you receive. There will therefore sometimes be suggestions that aren’t appropriate.
Screening the results
The search results should be available by the time an editor has been assigned to the paper. All you have to do is go to the Select Reviewers page. Here you’ll find the reviewers’ details, including the article(s) that flagged them as a potential reviewer for this manuscript.
This will give you a range of information about the potential reviewers, including their publication, peer review, and editorial history, flags for potential conflicts of interest, biographic information, keywords, institutional affiliations, and links to external sources.