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Books > Science & Mathematics > Mathematics > Applied mathematics > Non-linear science
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Science Dynamics and Research Production - Indicators, Indexes, Statistical Laws and Mathematical Models (Hardcover, 1st ed. 2016)
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Science Dynamics and Research Production - Indicators, Indexes, Statistical Laws and Mathematical Models (Hardcover, 1st ed. 2016)
Series: Qualitative and Quantitative Analysis of Scientific and Scholarly Communication
Expected to ship within 12 - 17 working days
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Total price: R2,077
Discovery Miles: 20 770
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This book deals with methods to evaluate scientific productivity.
In the book statistical methods, deterministic and stochastic
models and numerous indexes are discussed that will help the reader
to understand the nonlinear science dynamics and to be able to
develop or construct systems for appropriate evaluation of research
productivity and management of research groups and organizations.
The dynamics of science structures and systems is complex, and the
evaluation of research productivity requires a combination of
qualitative and quantitative methods and measures. The book has
three parts. The first part is devoted to mathematical models
describing the importance of science for economic growth and
systems for the evaluation of research organizations of different
size. The second part contains descriptions and discussions of
numerous indexes for the evaluation of the productivity of
researchers and groups of researchers of different size (up to the
comparison of research productivities of research communities of
nations). Part three contains discussions of non-Gaussian laws
connected to scientific productivity and presents various
deterministic and stochastic models of science dynamics and
research productivity. The book shows that many famous fat tail
distributions as well as many deterministic and stochastic models
and processes, which are well known from physics, theory of extreme
events or population dynamics, occur also in the description of
dynamics of scientific systems and in the description of the
characteristics of research productivity. This is not a surprise as
scientific systems are nonlinear, open and dissipative.
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