The analysis uses the idea of “efficiency” as an (the?) aim of research. e.g., lines 23-24 Assuming that the natural tendency will be to use a strategy that will lead to maximisation of individual efficiency”

Lines 46-47 “The efficiency of the scientific system is of key importance to ensure the competitiveness of a group, university, nation or region”

Lines 270-271 “the efficiency gain in producing a high quality paper”

This makes sense from the perspective of a top down driven change in science policy, but I would argue that it does not reflect the actual drivers of science.
Most scientists publish papers, because they wish to communicate the implications of their measurements (or simulations, modelling, and so on) of a natural phenomenon or of a laboratory synthesis. Put simply, I have a thesis that the world is not flat and my data are consistent with this interpretation. If I have access to the data of others and these are also consistent with my “non-flat world” hypothesis (though these data have in the past been interpreted as = flat world), my thesis is stronger. The community will at this point get into an argument (or at least it should!) about the interpretation of these datasets. This will lead in due course to better measurements and the establishment that the world is a spheroid, with an equatorial diameter slightly longer than the polar one, due to spin. In terms of the quality of a paper, a perhaps old-fashioned term, but very relevant is “a paper that is well received”, that is lots of people in a field have read it, because of its significance. We began to lose this idea when the journal became a false proxy for the paper, but we are now returning to the paper and I suspect in the longer term, to the data. At a personal level, I have never even considered “scooping” to be a problem, because there is so much blank space on the map, it is easy to go to places where you gain huge insights, but are miles away from your neighbours. Scooping is a problem of the herd mentality, for example, a huge number of people work on a small number of proteins out of the products of 20,000 human structural genes, in the face of systems analyses demonstrating that there are at least 10x more that are equally important from a regulatory perspective.
So if you split your authors into “explorers” and “herds”, and data sharing is embraced by the pioneers, but not the herd, then do you get the same gain for the explorers? If so, the herd will follow.