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  • Author or Editor: Koenraad Debackere x
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In this paper, we describe the development of a methodology and an instrument to support a major research funding allocation decision by the Flemish government. Over the last decade, and in parallel with the decentralization and the devolution of the Belgian federal policy authority towards the various regions and communities in the country, science and technology policy have become a major component of regional policy making. In the Flemish region, there has been an increasing focus on basing the funding allocation decisions that originate from this policy decentralization on “objective, quantifiable and repeatable” decision parameters. One of the data sources and indicator bases that have received ample attention in this evolution is the use of bibliometric data and indicators. This has now led to the creation of a dedicated research and policy support staff, called “Steunpunt O&O Statistieken,” and the first time application of bibliometric data and methods to support a major inter-university funding allocation decision. In this paper, we analyze this evolution. We show how bibliometric data have for the first time been used to allocate 93 million Euro of public research money between 6 Flemish universities for the fiscal year 2003, based on Web-of-Science SCI data provided to “Steunpunt O&O Statistieken” via a license agreement with Thomson-ISI. We also discuss the limitations of the current approach that was based on inter-university publication and citation counts. We provide insights into future adaptations that might make it more representative of the total research activity at the universities involved (e.g., by including data for the humanities) and of its visibility (e.g., by including impact measures). Finally, based on our current experience and interactions with the universities involved, we speculate on the future of the specific bibliometric approach that has now been adopted. More specifically, we hypothesize that the allocation method now developed and under further improvement will become more criticized if it turns out that it (1) also starts influencing intra-university research allocation decisions and, as a consequence (2) introduces adverse publication and citation behaviors at the universities involved.

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Scientometrics
Authors: Arnold Verbeek and Koenraad Debackere

Summary  

In this paper we analyze the (historical) co-evolution of technological development and economic progress (by relating public and private R&D investment, patenting, and corporate profitability). We relate to the work ofSchmookler(1966),Griliches(1990),Pakes&Griliches(1980) andPakes(1986) who all have studied the techno-economic interplay by considering patents as in indicator of technological performance. We use United States industry and government data over the period 1953-1998 (45 years). Co-evolution analysis over this period reveals a strong interdependency among the variables. Patent evolution is strongly related to the development of private R&D and corporate profitability; the levels of public and private R&D expenditure in combination with the level of technological output (i.e. patents) have a strong predictive and explanatory power towards corporate profitability (R2 value of 94.9%). Causality tests reveal a joint determination between R&D investment and corporate profitability (L=2; p<0.01).

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The US-EU race for world leadership in science and technology has become the favourite subject of recent studies. Studies issued by the European Commission reported the increase of the European share in the world’s scientific production and announced world leadership of the EU in scientific output at the end of the last century. In order to be able to monitor those types of global changes, the present study is based on the 15-year period 1991–2005. A set of bibliometric and technometric indicators is used to analyse activity and impact patterns in science and technology output. This set comprises publication output indicators such as (1) the share in the world total, (2) subject-based publication profiles, (3) citation-based indicators like journal-and subject-normalised mean citation rates, (4) international co-publications and their impact as well as (5) patent indicators and publication-patent citation links (both directions). The evolution of national bibliometric profiles, ‘scientific weight’ and science-technology linkage patterns are discussed as well. The authors show, using the mirror of science and technology indicators, that the triad model does no longer hold in the 21st century. China is challenging the leading sciento-economic powers and the time is approaching when this country will represent the world’s second largest potential in science and technology. China and other emerging scientific nations like South Korea, Taiwan, Brazil and Turkey are already changing the balance of power as measured by scientific production, as they are at least in part responsible for the relative decline of the former triad.

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In this paper we investigate — at a country level — the relationship between the science intensity of patents and technological productivity, taking into account differences in terms of scientific productivity. The number of non patent references in patents is considered as an approximation of the science intensity of technology whereas a country’s technological and scientific performance is measured in terms of productivity (i.e., number of patents and publications per capita). We use USPTO patent-data pertaining to biotechnology for 20 countries covering the time period 1992–1999. Our findings reveal mutual positive relationships between scientific and technological productivity for the respective countries involved. At the same time technological productivity is associated positively with the science intensity of patients. These results are confirmed when introducing time effects. These observations corroborate the construct validity of science intensity as a distinctive indicator and suggest its usefulness for assessing science and technology dynamics.

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The interplay and cross-fertilization between science and technology, but also the specific role of science for technological development, have received ample attention in both the research and the policy communities. It is in this context that the concepts of absorptive capacity and knowledge spillovers play an important role. We operationalize the science-technology link by quantifying and modeling bibliographic references to the scientific literature as they occur in patents. This approach allows exploring the associative patterns between science creation (as emerging from the scientific literature) and technology development (as emerging from the patent literature). In the current paper, we focus on an analysis of the geographic distribution of the science citation patterns in patents, singling out two fields of (different) technological development, namely biotechnology and information technology. In both fields, the science citation flows from the European, Japanese and US science bases into USPTO and EPO-patents are explored and modeled. Intensive geographic citation flows between the regions are identified, pointing (amongst others) to the strength of both the US and the European science bases as sources for technological activity and creativity around the world.

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Abstract  

This paper explores issues related to the impact of Science-Industry relationships on the knowledge production of academic research groups, in particular on the alleged shift to the more applied research end under the influence of business partners' needs. Our findings from a case study of the Belgian Katholieke Universiteit Leuven ((K.U. Leuven) show a significant steady growth over time of publications produced by academic research groups involved in University-Industry linkages, closely related to factors both internal and external to the university that have stimulated academic entrepreneurial behaviour. On an aggregated level for 1985-2000, basic research publications appear to be more present than applied ones, both in total numbers and in growth rates. Our findings show that applied and basic research publications generally rose together in the same year. No clear and generalised evidence of a shift towards the applied research end determined by the involvement in U-I linkages was found, the weak indications of such a shift within groups coming only for groups that have already high applied versus basic orientation. These results suggest that the academic research groups examined have developed a record of applied publications without affecting their basic research publications and, rather than differentiating between applied and basic research publications, it is the combination of basic and applied publications that consolidate the group's R&D potential. Accordingly, critical assessments of the University side of the emerging 'Triple Helix' need to take into account the dynamic nature of the research dimension.

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The objective of the present study is twofold: (1) to show the aims and means of quantitative interpretation of bibliographic features in bibliometrics and their re-interpretation in research policy, and (2) to summarise the state-of-art in self-citation research. The authors describe three approaches to the role of author self-citations and possible conflicts arising from the different perspectives. From the bibliometric viewpoint we can conclude that that there is no reason for condemning self-citations in general or for removing them from macro or meso statistics; supplementary indicators based on self-citations are, nonetheless, useful to understand communication patterns.

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Abstract  

A common problem in comparative bibliometric studies at the meso and micro level is the differentiation and specialisation of research profiles of the objects of analysis at lower levels of aggregation. Already the institutional level requires the application of more sophisticated techniques than customary in evaluation of national research performance. In this study institutional profile clusters are used to examine which level of the hierarchical subject-classification should preferably be used to build subject-normalised citation indicators. It is shown that a set of properly normalised indicators can serve as a basis of comparative assessment within and even among different clusters, provided that their profiles still overlap and such comparison is thus meaningful. On the basis of 24 selected European universities, a new version of relational charts is presented for the comparative assessment of citation impact.

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In this paper we examine whether and to what extent material transfer agreements influence research agenda setting in biotechnology. Research agendas are mapped through patents, articles, letters, reviews, and notes. Three groups are sampled: (1) documents published by government and industry which used research materials received through those agreements, (2) documents published by government and industry which used in-house materials, (3) documents published by academia. Methodologically, a co-word analysis is performed to detect if there is a difference in underlying scientific structure between the first two groups of documents. Secondly, interviews with practitioners of industry and government are intended to capture their opinion regarding the impact of the signed agreements on their own research agenda choices. The existence of synchronic and diachronic common terms between co-word clusters, stemming from the first two groups of publications, suggests cognitive linkage. Moreover, interviewees generally do not consider themselves constrained in research agenda setting when signing agreements for receiving research materials. Finally, after applying a co-word analysis to detect if the first group of documents overlaps with the third group we cannot conclude that agreements signed by industry and government affect research agenda setting in academia.

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Abstract

Two paradigmatic approaches to the normalisation of citation-impact measures are discussed. The results of the mathematical manipulation of standard indicators such as citation means, notably journal Impact Factors, (called a posteriori normalisation) are compared with citation measures obtained from fractional citation counting (called a priori normalisation). The distributions of two subfields of the life sciences and mathematics are chosen for the analysis. It is shown that both methods provide indicators that are useful tools for the comparative assessment of journal citation impact.

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