The aim of this paper is to develop and apply Neural Network (NN) models in order to forecast regional employment patterns in Germany. NNs are statistical tools based on learning algorithms with a distribution over a large amount of quantitative data. NNs are increasingly deployed in the social...

Many networks such as the Internet have been found to possess scale-free and small-world network properties reflected by so-called power law distributions. Scale-free properties evolve in large complex networks through self-organizing processes and more specifically, preferential attachment. New...

There is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situations and partly by the easy availability and accessibility of sophisticated...

The spatial activity patterns of firms in a multi-regional system are closely connected with the structure and evolution of regional labour markets. Based on an extensive data set (cross-section) on commuting flows in Germany, this paper aims to identify the relationship between entrepreneurial...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

In this paper we analyse interregional freight transport movements in Europe with a view on new spatial patterns based on transport economic scenarios for environmental sustainability. Two different approaches are compared. viz. the logit model and the neural network model. The paper will...

The present paper aims to analyse interregional freight transport movements in Europe with a view on forecasting future patterns of transport flows using simple economic scenarios. In view of the high dimension of our data-base on transport flows, two different approaches are compared, viz. the...

This paper addresses the issue of innovative behaviour of firms in an urban European context. It aims to identify key factors for innovation at the local level, based on micro survey information from firms. In seeking for prominent explanatory variables for entrepreneurial innovation in various...

The present paper aims at developing a new research approach based on the synergy concept as a driving force in network analysis and modelling. Starting from some introductory reflections identifying the role of network synergy in regional development and transportation science, the paper aims...

This paper aims to compare the descriptive and predictive power of two classes of statistical estimation models for multimodal network flows, viz. the logit model and the neural network model. The application concerns a large data set on inter-regional European freight flows for two commodity...