This paper uses data for 255 NUTS-2 European regions over the period 1995-2003 to test the relative explanatory performance of two important rival theories seeking to explain variations in the level of economic development across regions, namely the neoclassical model originating from the work...

This paper investigates the impact of knowledge capital stocks on total factor productivity through the lens of the knowledge capital model proposed by Griliches (1979), augmented with a spatially discounted cross-region knowledge spillover pool variable. The objective is to shift attention from...

A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects optimal decision rules with a minimal set of features necessary and sufficient for classification of real-valued data. A rough set knowledge discovery...

The focus of this paper is on the neural network modelling approach that has gained increasing recognition in GIScience in recent years. The novelty about neural networks lies in their ability to model non-linear processes with few, if any, a priori assumptions about the nature of the...

Questions of convergence have received increasing attention in recent years, in light of the pressure for greater integration and enlargement of the European Union [EU] to countries in Central and Eastern Europe [CEE]. This paper looks at the evidence for convergence of per capita income between...

The focus in this paper is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. High-technology is defined to include the ISIC-sectors aerospace (ISIC 3845), electronics-telecommunication (ISIC 3832), computers and office equipment (ISIC 3825), and...

In this paper we view learning as an unconstrained non-linear minimization problem in which the objective function is defined by the negative log-likelihood function and the search space by the parameter space of an origin constrained product unit neural spatial interaction model. We consider...

This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure,...

This paper attempts to develop a mathematically rigid and unified framework for neural spatial interaction modeling. Families of classical neural network models, but also less classical ones such as product unit neural network ones are considered for the cases of unconstrained and singly...

This paper centres around two research questions: first, the identification of five types of networks that manufacturing firms located in the metropolitan region of Vienna may have created for different purposes; and second, the question to what extent the likelihood of interfirm cooperation is...