Classification Techniques in Quantitative Comparative Research: A Meta-Comparison

Peter Nijkamp, Piet Rietveld and Laura Spierdijk
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Laura Spierdijk: Free University

Chapter 7 in Spatial Economic Science, 2000, pp 102-124 from Springer

Abstract: Abstract In our information age there is often an abundance of fragmented data and an overwhelming presence of segmented methodological approaches. There is also an increasing demand for more integrated scientific insights and perspectives. And clearly, there is a need for more research synthesis in the empirical sciences. Empirical research is often based on controlled experimentation, as is witnessed in the research methodology in the natural sciences. In the social sciences however, it appears to be very difficult to apply this research methodology, as both contextual (environmental) conditions and behavioural factors are subject to change. As a consequence, we have witnessed in recent years the emergence of comparative case study research with a view to the identification of common knowledge patterns from distinct classes of information (Bergh et al. 1997; Nijkamp and Pepping 1998). There is an increasing recognition of the added value of empirical research synthesis in the social sciences.

Keywords: Neural Network; Membership Function; Discriminant Analysis; Probit Model; Social Science Research (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1007/978-3-642-59787-9_7

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