873 publications from this institution
In this chapter we shall discuss the anatomy of the Vienna innovation system. We begin with a profile of the region concerned (Section 2.1) followed by a brief characterisation of the Austrian R&D system (Section 2.2) and then move on to the institutional setting...
This paper evaluates the classification accuracy of three neural network classifiers on a satellite image-based pattern classification problem. The neural network classifiers used include two types of the Multi-Layer-Perceptron (MLP) and the Radial Basis Function Network. A normal (conventional) classifier is used as a benchmark to evaluate the performance of neural network classifiers. The satellite image consists of 2,460 pixels selected from a section (270 x 360) of a Landsat-5 TM scene from the city of Vienna and its northern surroundings. In addition to evaluation of classification accuracy, the neural classifiers are analysed for generalization capability and stability of results. Best overall results (in terms of accuracy and convergence time) are provided by the MLP-1 classifier with weight elimination. It has a small number of parameters and requires no problem-specific system of initial weight values. Its in-sample classification error is 7.87% and its out-of-sample classification error is 10.24% for the problem at hand. Four classes of simulations serve to illustrate the properties of the classifier in general and the stability of the result with respect to control parameters, and on the training time, the gradient descent control term, initial parameter conditions, and different training and testing sets. (authors' abstract)
The paper emphasises the importance of a research programme focused on developing and making widely available GIS relevant spatial analysis technology. It outlines generic criteria able to discriminate between GIS-relevant and GIS-irrelevant spatial analysis tools and outlines a list of six researchable spatial analysis themes. It is argued that presently there is an opportunity to develop a EU based spatial analysis research programme and then install the technology in the World's GIS.
This article investigates the impact of knowledge capital stocks on total factor productivity (TFP) 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 firms and industries to regions and to estimate the impact of cross‐region knowledge spillovers on TFP in Europe. The dependent variable is the region‐level TFP, measured in terms of the superlative TFP index suggested by Caves, Christensen, and Diewert (1982). This index describes how efficiently each region transforms physical capital and labor into output. The explanatory variables are internal and out‐of‐region stocks of knowledge, the latter capturing the contribution of cross‐region knowledge spillovers. We construct patent stocks to proxy annual regional knowledge capital stocks for N=203 regions during 1997–2002. In estimating the effects, we implement a spatial panel data model that controls for spatial autocorrelation as well as individual heterogeneity across regions. The findings provide a fairly remarkable confirmation of the role of knowledge capital contributing to productivity differences among regions and add an important spatial dimension to discussions in the literature by showing that productivity effects of knowledge spillovers increase with geographic proximity.
The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.
No abstract is provided for this article.
The dissemination of digital spatial databases, coupled with the ever wider use of GISystems, is stimulating increasing interest in spatial analysis from outside the spatial sciences. The recognition of the spatial dimension in social science research sometimes yields different and more meaningful results than analysis which ignores it. The emphasis in this book is on spatial analysis from the perspective of Geo- Computation. GeoComputation is a new computational-intensive paradigm that increasingly illustrates its potential to radically change current research practice in spatial analysis. This volume contains selected essays of Manfred M. Fischer. By drawing together a number of related papers, previously scattered in space and time, the collection aims to provide important insights into novel styles to perform spatial modelling and analysis tasks. Based on the latest developments in esti- tion theory, model selection and testing this volume develops neural networks into advanced tools for non-parametric modelling and spatial interaction modelling. Spatial Analysis and GeoComputation is essentially a multi-product und- taking, in the sense that most of the contributions are multi-authored publications. All these co-authors deserve the full credit for this volume, as they have been the scientific source of the research contributions included in the present volume. This book is being published simultaneously with Innovation, Networks and Knowledge Spillovers: Selected Essays. I would also like to thank Gudrun Decker, Thomas Seyffertitz and Petra Staufer- Steinnocher for their capable assistance in co-ordinating the various stages of the preparation of the book.
The paper is concerned with the impact of market research prior to integration, on the structures of noncompetitive industries in integrated economy. The analysis focuses on separated, single commodity, monopolistic markets with stochastic demand. Monopolistic firms are considered in dynamic multiperiod model, where intertemporal links are determined by expenditures on market research in a present period and benefits from this activity (i.e., smaller variance of the prediction error) in the future. Assuming that each firm maximizes its total discounted expected utility from profit in indefinite time, we show that the optimal market research strategy is stationary and depends on market size. Consequently, in the period following integration firms operating prior to integration in small markets (such as Slovenia, Czech Republic, Hungary or Estonia) are expected to have much less information about the integrated market than their competitors operating before integration on European market. This informational asymmetry may affect the structure of the industry in integrated economy. In the extreme case, the firm operating before integration in the small market can be ruled out from the integrated market.
Die Zerreißprüfungen zeigen, daß Querrupturen, Abrißfrakturen oder sonstige Risse auf Grund reiner linear auseinander gerichteter Zugkr
No abstract is provided for this article.
This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities.
Artificial intelligence (Al) has received an explosion of interest during the last five years in various fields. There is no longer any question that expert systems and neural networks will be of central importance for developing the next generation of more intelligent geographic information systems. Such knowledge based geographic information systems will especially play a key role in spatial decision and policy analysis related to issues such as environmental monitoring and management, land use planning, motor vehicle navigation and distribution logistics. This paper sketches briefly the major characteristics of conventional geographic information systems, and then looks at some of the potentials of Al principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.
Having read 18 chapters that represent the frontier in spatial analysis, we ask ourselves the following questions: What can be said about the state of knowledge in this area? What directions appear to be the most promising? In this conclusion, the editors attempt to...
A general framework to analyze communication media choice behavior in the university setting is proposed which integrates a stated preference experimental design procedure into a discrete choice modeling framework. The framework is empirically tested using hypothetical choice experiments in which traditional mail, courier mail, telephone, facsimile, and electronic mail services were choice options to carry out information communication tasks. For this purpose face-to-face interviews were conducted in six universities in Austria and Switzerland. The choice modeling approach developed emphasizes the influence of communication context specific characteristics, individual and organizational characteristics of the communication initiator as well as the individual's perceptions and feelings about the communication media on the formation of preferences. Empirical results are presented using stated preference models of communication media choice behavior for a series of communication situations. Specific emphasis is laid on crossnational differences in choice behavior.
No abstract is provided for this article.
Jahrzehntelang haben österreichische und ungarische Botaniker die Suaeda prostrata irrigerweise als S. „pannonica“ bezeichnet und die echte S. pannonica als S. „maritima“ fehlbestimmt. Vom 19. Jahrhundert bis 1996 wurden die beiden Arten in Österreich und Ungarn verkannt und falsch benannt. Seit den 1930er-Jahren ist die kontinentale, von Süd-Mähren und dem östlichen Österreich bis Südsibirien verbreitete S. prostrata fälschlich S. „pannonica“ genannt worden, wohingegen die in der Pannonischen und Pontischen Florenprovinz endemische echte S. pannonica mit der deutlich verschiedenen, weit verbreiteten Küstenart S. maritima verwechselt worden war. Suaeda pannonica unterscheidet sich von S. prostrata hauptsächlich durch derberen Habitus, längere Laubblätter, zygomorphes bis unregelmäßiges Fruchtperigon mit mindestens einem behöckerten Perigonzipfel, größeren Samen und überdies durch andersartige Standortsökologie. Suaeda prostrata ist der S. maritima sehr ähnlich und mit ihr nah verwandt (wenn nicht konspezifisch). Erst in den Jahren 1990 bzw. 1996 ist der Irrtum durch P. Tomšovic und H. Freitag & al. entdeckt und berichtigt worden.
