When universities or university departments produce research outputs?such as published papers?they sometimes experience increasing returns to scale, sometimes constant returns to scale, and sometimes decreasing returns to scale. At the level of nations however, R&D tends to see increasing returns to scale. These results are preliminary.
Background
“Returns to scale” refers to the responsiveness of a process’ outputs when all inputs (e.g. researcher hours, equipment) are increased by a certain proportion. If all outputs (e.g. published papers, citations, patents) increase by that same proportion, the process is said to exhibit constant returns to scale. Increasing returns to scale and decreasing returns to scale refer to situations where outputs still increase, but by a higher or lower proportion, respectively.
Assessing returns to scale in research may be useful in predicting certain aspects of the development of artificial intelligence, in particular the dynamics of an intelligence explosion.
Results
The conclusions in this article are drawn from an incomplete review of academic literature assessing research efficiency, presented in Table 1. These papers assess research in terms of its direct outputs such as published papers, citations, and patents. The broader effects of the research are not considered.
Most of the papers listed below use the Data Envelopment Analysis (DEA) technique, which is a quantitative technique commonly used to assess the efficiency of universities and research activities. It is capable of isolating the scale efficiency of the individual departments, universities or countries being studied.
