R (research) and D (development) have very different objectives and outputs (science versus technology; discovery versus innovation) and they are performed by different people in different places (academia, federal government funded research centres versus business and industry) and funded with money of very different origins (government versus industry). And their motivations are also different (intellectual passions versus economic added value).
Canadian Benoit Godin, from INRS University (Quebec) is the most important source about the critical history of science & technology statistics and innovation statistics. His sociological approach shows these devolopments as outcomes of “social battlefields” related with games of power and politics at the international level and betwen powerful actors and institutions (like OECD, UNESCO, European Community, World Bank, …). His web page is a mandatory reference for all interested in the issues of innovation (“the idea of innovation”) and statistics of science and technology (“the culture of numbers”).
In a recent paper (Godin and Lane, “Research or development? A short history of research and development as categories”, 2012) he emphasizes that the real issue it is not applied versus basic research, but research versus development, and that Research OR Development is an appropriate way to formulate the issue, nor R&D.
D is much more important than R, in money terms. R&D is the result of the appropriation of D (industry) by R (academy), profiting of the much larger dimension of D in order to claim a large R&D, of course leaded by academy - not a D&R leaded by industry and business, who really pay around ⅔ of the R&D bill in USA. These has “helped the case of candidates looking for symbolic and popular support for public funding if research activity”:
co-mingling of research and development expenditures, activities and
results had the effect of giving priority to research over development
in policies. While research, which corresponds to one third of R&D
expenditures, has specific categories to discuss it (basic and applied),
the bulk of the R&D expenditures – two thirds is devoted to
development – has no category at all. The difference in emphasis may be
that governments’ funding of research has a large, articulate and
influential interest group in university scholars, while there is no
equivalent interest group for development."
- "Why do measurements fail to differentiate R methods from D methods? Why do indicators exclude the methods and imperfectly measure the outputs of industry (surveys of innovation)? Historically, the pervasive emphasis on scientific research by its champions has completely overshadowed the equally important contributions of engineering development. Furthermore, the “free market” bias often prevents public policies from even considering industrial production as being eligible to share in the stream of public revenues allocated to technological innovation. The supreme irony is that industry – private sector corporations and their employees – generate the majority of revenues collected through taxation and dispensed to the public and non-profit sectors through government programs. Nations that establish policies accounting for the mechanisms and indicators of all three, research, engineering development and industrial production, would be best positioned to lead innovation in the Twentieth-First Century".
R&D formula is a direct consequence of the "linear model" that wrongly assumes that technology (D) is a consequence of research (R), a second step of a cycle that begins and works upon the results of science activities. So the driver of development would be found in science and research - the offer side. That is wrong: technology is driven by the demand side, and often even science (aplied R) is driven by the demands of technology (D). (Genuine pure or basic R is said to be driven by intellectual passions of the researcher).
This suggests me a different possible formulation: DandR. Or may be DorR.
(Italics, our responsability).