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New University Presses (NUPs) and Academic-led Publishers (ALPs) are very much the hot topics on the agenda of scholarly publishing conferences. With as many as 19 NUPs becoming operational in the UK in recent years (including the likes of White Rose University Press, UCL, and Cardiff University Press), there is a perceptible shift taking place in academic publishing, one which aims to put academics and institutions at the centre, prioritising their needs above all else. Many believe that this trend will be the most disruptive development the industry has seen since Open Access, once again transforming the role of publishers. But how real is the threat they actually pose? And what role will technology play in this story?
Technology is very much at the heart of everything these new outfits do. They predominantly champion digital-first business models, with the production of print products across monographs, books, and journals, usually via Print on Demand, only as secondary propositions. They are Open Access advocates through and through, driven by a need to disseminate research on the largest possible scale to meet the demands of scholars. They are increasingly investing in affordable technology and service options, which can help them establish a strong infrastructure and better manage their workflows on a day-to-day basis. And they do all this at a relatively low operational cost — their goal is not to generate revenue and they tend not to have article or book processing charges.
While many technological innovations have dramatically reduced NUP set-up and running costs, a lack of human resource has always been, and still is, the main stumbling block barring their growth, with most NUPs operating with just one full time member of staff. As they establish themselves, many NUPs are set up out of scholarly libraries, and the running of the Press becomes one in a long list of tasks the stretched, modern-day librarian must undertake. Even when an NUP is established as a separate entity with its own dedicated resources, they typically lack adequate resources to compete with more established publishers, limiting how much research can realistically be processed, disseminated, and marketed effectively.
This resourcing issue means that while some academics will indubitably choose to publish their research via their institution’s Press, it is unlikely that an NUP in the early stages of its trajectory will be able to publish the vast majority of the work of their home universities’ academics. So, while by nature NUPs may be perceived as radically disruptive to the hegemony of traditional publishers, when you look at the metrics of volume, scale, and resources, it is unlikely that they pose a real threat to their business, at least at present.
One of the main challenges NUP employees face is the need to constantly juggle tasks. Staff spend far too long on editorial procedures such as indexing and inputting metadata manually to make sure research is discoverable, and end up spending very little time promoting and marketing the work so that researchers can find it. The systems most publishers have entrenched make these processes slow and arduous, not to mention susceptible to human error.
This is what makes developments in machine learning technology, and their introduction into the publishing process, so exciting, particularly for resource starved NUPs. By introducing machine learning into the workflow, we estimate that publishers can free up around 40 per cent of the time spent on manual editorial tasks. By automating these processes, NUP staff can focus instead on adding real value where human attention is needed most — on higher level work such as promoting journals and books to ensure that they reach more eyes around the globe, and actually become the disruptive threat traditional publishing fears.
