This paper gives an overview of quantitative approaches used to study the science/technology linkage. Our discussion is informed
by a number of theoretical approaches that have emerged over the past few years in the area of innovation studies emphasizing
the exchange of actors in innovation system and a shift in the division of labour between publicly funded basic research and
industrial development of technology. We review the more quantitative literature on efforts made to study such linkage phenomena,
to which theorizing in the science policy area has attributed great importance. We then introduce a typology of three approaches
to study the science/technology linkage - patent citation, industrial science, and university patenting. For each approach,
we shall discuss merits and possible disadvantages. In another step we illustrate them using results from studies of the Finnish
innovation system. Finally, we list key limitations of the informetric methods and point to possible hybrid approaches that
could remedy some of them.
Hardly anyoee will dispute that the creation of theScience Citation Index has made an important difference to science. It is less clear, however, in what way the science system has been influenced.
This article proposes a qualitative model to better understand the mutual interactions involved. Science is pictured as an
information processing cycle. Its quality is maintained in the “peer review cycle”. The main upshot of theSCI has been the creation of a second-order cycle on top of the primary knowledge production cycle. This is the citation cycle.
The specialty of scientometrics has a key role in this citation cycle. The model enables a more profound understanding of
the various feed back processes between the two cycles. Moreover, it may give insight in the development of hybrid and heterogenous
scientific specialties like scientometrics.
Although there is considerable consensus that Finance, Management and Marketing are ‘science’, some debate remains with regard
to whether these three areas comprise autonomous, organized and settled scientific fields of research. In this paper we aim
to explore this issue by analyzing the occurrence of citations in the top-ranked journals in the areas of Finance, Management,
and Marketing. We put forward a modified version of the model of science as a network, proposed by Klamer and Van Dalen (J
Econ Methodol 9(2):289–315, <cite>2002</cite>), and conclude that Finance is a ‘Relatively autonomous, organized and settled field of research’, whereas Management and
(to a larger extent) Marketing are relatively non-autonomous and hybrid fields of research’. Complementary analysis based
on sub-discipline rankings using the recursive methodology of Liebowitz and Palmer (J Econ Lit 22:77–88, <cite>1984</cite>) confirms the results. In conclusions we briefly discuss the pertinence of Whitley’s (The intellectual and social organization
of the sciences, <cite>1984</cite>) theory for explaining cultural differences across these sub-disciplines based on its dimensions of scholarly practices,
‘mutual dependency’ and ‘task uncertainty’.
It is shown that the maximal operator of the Fejér means of a tempered distribution is bounded from thed-dimensional Hardy spaceHp(R×···×R) toLp(Rd) (1/2<p<∞) and is of weak type (H1♯i
,L1) (i=1,…,d), where the Hardy spaceH1♯i
is defined by a hybrid maximal function. As a consequence, we obtain that the Fejér means of a functionf ∈H1♯i
⊃L(logL)d−1 converge a.e. to the function in question. Moreover, we prove that the Fejér means are uniformly bounded onHp(R×···×R) whenever 1/2<p<∞. Thus, in casef ∈Hp(R×···×R) the Fejér means converge tof inHp(R×···×R) norm. The same results are proved for the conjugate Fejér means, too.
We investigate the Kronecker product of bounded Ciesielski systems, which can be obtained from the spline systems of order
(m, k) in the same way as the Walsh system from the Haar system. It is shown that the maximal operator of the Fejér means of the
d-dimensional Ciesielski-Fourier series is bounded from the Hardy space Hp([0, 1)d1×…×[0, 1)dl to Lp ([0, 1)d) if 1/2<p<∞ and mj≥0, ‖kj‖≤mj+1. By an interpolation theorem, we get that the maximal operator is also of weak type (