When new publishing ventures are launched, there is a journalistic tendency to depict them as “disruptive,” “innovative,” or “game changers.” In reality, very few new ventures are. Two years in, most new ventures can hope to be alive, let alone prove to be disruptive. Most of these companies just fade from our memories. There is very little incentive to go back and revisit them.
In 2012, I published two posts on PeerJ. The first, arguing that this new publication represented a clear cultural shift, from the staid publishing houses of Europe and the Eastern United States, to a West Coast Silicon Valley startup mentality. The second post took a more critical look at their publication business model and and argued that this venture capital-backed company had an exit strategy built right in and we could predict when they would sell by the shape of their author membership curve.
Rather than taking the easy route of more idle speculation, I decided to take a data-driven approach and look at what PeerJ was publishing and whether it leads to any insight on the success (or failure) of this new venture.
Based on publication data that I parsed from PubMed, between May 3, 2013 and October 8, 2014, PeerJ published 600 articles and one correction. PubMed does not index PeerJ PrePrints. Their publication rate has been pretty steady (Figure 1 below), and appears to be rising somewhat in 2014.
PubMed lists the online publication date for each article, but strangely provides just the PubMed batch load date in their data extract. The periodic spikes in new papers and authors in the figures below reveal those weekly PubMed loads.
From the PubMed metadata, I was able to count the number of authors per paper, and with a little work, calculate whether the author was new or returning. Remember that PeerJ works on a lifetime membership model where you “pay once, publish for life.” Returning authors, therefore, do not bring additional revenue to the company although they do incur expenses.
Figure 2 plots the number of new authors (blue bar) by date, as well as the cumulative number of new authors (red line). Like Figure 1, the number of new PeerJ authors is rising steadily and may be increasing in 2014.
The 600 published PeerJ papers included 2557 authors, 2290 (about 90%) of whom were unique. The median number of authors per paper was 4, with one paper listing 18 authors. The vast majority of unique authors (92%) were listed on just one PeerJ paper. The remaining 8% (193) were repeat authors: 143 (6.2%) authors were listed on two papers, 34 (1.5%) were listed on three papers, 10 (0.4%) authors were listed on four papers, 4 (0.2%) authors were listed on five papers, and 2 (0.1%) authors were listed on six PeerJ papers.
While these two graphs look almost identical, they convey two very different things toward measuring the success of PeerJ. The first graph shows that the company is able to attract and publish new papers. Yet, compared to multidisciplinary open access journals with similar scope (viz. PLOS ONE), PeerJ is still very small. Submissions to PeerJ PrePrints may have been eclipsed by Cold Spring Harbor Laboratory’s bioRxiv and it appears that PeerJ may be fighting to attract new preprint authors by dropping all publication fees if their authors use their preprint service.
Even thought the number of publications is increasing, we can’t simply convert them into reliable estimate of a revenue stream. Like most open access startup journals, PeerJ has had several periods where author fees were waived, so not all authors and not all papers paid for memberships. As a private company, the financial details of PeerJ are locked tightly in a black box; however, news of a new round of funding by venture capitalist, Tim O’Reilly and SAGE Publishing may give hints on the financial self-sustainability of PeerJ.
Since last writing about PeerJ, the company has introduced two new pricing models. First, it is now easier for a single author to pay for co-authors or for the entire author group. This makes PeerJ operate like most other open access (and hybrid) journals in which a single author is responsible for all financial details. Second, PeerJ introduced an institutional “pre-pay” model in which libraries can purchase memberships for their institutional authors. If I remember correctly, this institution-pays model was first introduced by BioMed Central nearly ten years ago. These two price model introductions may indicate that the individual membership model is not working, or at least not as well as PeerJ‘s founders predicted.
To me, the more important graph to watch is the number of new authors (Figure 2). The commercial success of this company is predicated on an increasing stream of new authors willing to pay lifetime membership fees. This is not a bad assumption to make for a young journal in which the vast majority of members are first-time authors. It does start to break down if the number of new (paying) authors is unable to support the growing expenses of returning authors.
Within a few weeks, PeerJ content will be indexed in the Web of Science and BIOSIS Previews, according to Joelle Masciulli, Editorial Director of the Web of Science at Thomson Reuters. At this point, PeerJ has not been assigned an Impact Factor. As most scientists consider journal prestige and Impact Factor important in their submission decisions, receiving an Impact Factor next year could lead to a rapid influx of new PeerJ submissions, as we saw with PLOS ONE. Alternatively, a low Impact Factor could lead to a steep drop-off.
In sum, PeerJ introduced a new publication model that was “innovative” in the true sense of the word; however, changes in its pricing models are making this journal look much more like other open access and hybrid journals. Competition from bioRxiv may have eclipsed PeerJ‘s prospects of a business built on preprints. PeerJ is growing, publishing more papers and attracting more authors, although it is not clear whether the company is moving toward financial sustainability. In a crowded market of multidisciplinary open access journals, the success/failure of PeerJ may be determined when it receives its first Impact Factor.