Quantitative studies of science and technology represent the research field of utilization of mathematical, statistical, and data-analytical methods and techniques for gathering, handling, interpreting, and predicting a variety of features of the science and technology enterprise, such as performance, development, and dynamics. The field has both strongly developed applied research as well as basic research characteristics.
The principal purpose of this handbook is to present this wide range of topics in sufficient depth to give readers a reasonably systematic understanding of the domain of contemporary quantitative studies of science and technology, a domain which incorporates theory, methods and techniques, and applications. In addressing this domain, the handbook aims at different groups of readers: those conducting research in the field of science and technology, including (graduate) students, and those who are to use results of the work presented in this book.
Introduction (A.F.J. van Raan). Science in a Social Context. Some Contextual Problems of Science Indicators (M.J. Moravcsik). Measures of Scientific Output and the Age-Productivity Relationship (P.E. Stephan, S.G. Levin). The Structural Analysis of a Scientific Paper (N. Mullins, W. Snizek, K. Oehler). Network Analysis in the Study of Science and Technology (W. Shrum, N. Mullins). Evaluation of Research Performance and Mapping of Science. Against Absolute Methods: Relative Scientometric Indicators and Relational Charts as Evaluation Tools (A. Schubert, W. Glaenzel, T. Braun). Indicators of Research Performance: Applications in University Research Policy (H.F. Moed, A.F.J. van Raan). The Validity and Reliability of Evaluation of Scholarly Performance (A.J. Nederhof). Measuring Scientific Output by Online Techniques (O. Persson). Mapping of Science: Possibilities and Limitations (A. Rip). The Use of Co-Nomination Analysis in the Evaluation of Collaborative Research (L. Georghiou et al.). Packaging Information for Peer Review: New Co-Word Analysis Techniques (W.A. Turner et al.). Co-Citation Bibliometric Modeling as a Tool for S&T and R&D Management: Issues, Applications, and Developments (J.J. Franklin, R. Johnston). Bibliometric Indicators for Assessing Strengths and Weaknesses of West German Science (P. Weingart, R. Sehringer, M. Winterhager). Some Statistical Aspects of Co-Citation Cluster Analysis and a Judgment by Physicists (J.E.J. Oberski). Science and Technology. Technology Indicators Based on Patents and Patent Citations (F. Narin, D. Olivastro). Uses and Abuses of Patent Statistics (K. Pavitt). The Citation Gap of Applicable Science (C. Le Pair). The Measurement of Changes in Technological Output (P. Saviotti). Technological Standards for Research-Intensive Product Groups and International Competitiveness (H. Grupp, O. Hohmeyer). Advanced Data-Analytical Methods and Techniques. Using
- © North Holland 1988
- 1st November 1988
- North Holland
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