Competencies of firms, external knowledge sourcing and types of innovation in regions of Europe

Many innovation studies have been focusing on a narrow concept of innovation such as the generation of patents or new products. The performance of companies, however, often depends on innovation defined from a broader perspective. This includes process, organisational and market innovations as was pointed out already by Schumpeter. Drawing on the concept of knowledge bases and innovation networks we argue that these different types of innovation require both internal competencies, and technological and market knowledge from various kinds of external sources. These can be located at regional, national and international levels. In the present paper we are going to analyse evidence from eight European countries in this respect. Based on a multivariate model we are able to show that product, process and organisational innovations indeed rely on quite different types and sources of knowledge, and that in addition also the institutional characteristics of regions and countries matter.

Distributed Estimation with Information-Seeking Control in Agent Network

We introduce a distributed, cooperative framework and method for Bayesian estimation and control in decentralized agent networks. Our framework combines joint estimation of time-varying global and local states with information-seeking control optimizing the behavior of the agents. It is suited to nonlinear and non-Gaussian problems and, in particular, to location-aware networks. For cooperative estimation, a combination of belief propagation message passing and consensus is used. For cooperative control, the negative posterior joint entropy of all states is maximized via a gradient ascent. The estimation layer provides the control layer with probabilistic information in the form of sample representations of probability distributions. Simulation results demonstrate intelligent behavior of the agents and excellent estimation performance for a simultaneous self-localization and target tracking problem. In a cooperative localization scenario with only one anchor, mobile agents can localize themselves after a short time with an accuracy that is higher than the accuracy of the performed distance measurements.Comment: 17 pages, 10 figure

Type-elimination-based reasoning for the description logic SHIQbs using decision diagrams and disjunctive datalog

We propose a novel, type-elimination-based method for reasoning in the description logic SHIQbs including DL-safe rules. To this end, we first establish a knowledge compilation method converting the terminological part of an ALCIb knowledge base into an ordered binary decision diagram (OBDD) which represents a canonical model. This OBDD can in turn be transformed into disjunctive Datalog and merged with the assertional part of the knowledge base in order to perform combined reasoning. In order to leverage our technique for full SHIQbs, we provide a stepwise reduction from SHIQbs to ALCIb that preserves satisfiability and entailment of positive and negative ground facts. The proposed technique is shown to be worst case optimal w.r.t. combined and data complexity and easily admits extensions with ground conjunctive queries.Comment: 38 pages, 3 figures, camera ready version of paper accepted for publication in Logical Methods in Computer Scienc

Spontaneous breaking of rotational symmetry in the presence of defects

We prove a strong form of spontaneous breaking of rotational symmetry for a simple model of two-dimensional crystals with random defects in thermal equilibrium at low temperature. The defects consist of isolated missing atoms.Comment: 18 page

Does combinatorial knowledge lead to a better innovation performance of firms?

The knowledge base concept in the past has often been applied in its "pure" form, i.e. it was assumed that there are dominant knowledge bases in particular sectors and firms, that shape the knowledge- and innovation process and related networks. For example, it has been argued that in the case of "analytical sectors" such as biotech codified knowledge generated by universities and R&D organisations are key for radical innovation, and that such knowledge is often transmitted by formal R&D cooperations and university-firm links. "Synthetic sectors" such as machinery on the other hand were assumed to innovate more incrementally by recombining existing knowledge that was often drawn from suppliers or service firms. Empirical literature partly has confirmed these basic patters, but also has demonstrated that more complex knowledge processes are underlying these overly schematic expectations. In addition, there have been arguments by Asheim, Boschma and Strambach, among others, more recently that combinations of different but related knowledge bases and -assets might be of high relevance for understanding innovation processes of firms in particular sectors and regions. This implies that innovation of firms e.g. in "analytical sectors" might benefit not just from new and basic knowledge generated by research, but also from recombining existing and applied knowledge or by drawing on symbolic knowledge assets. The same argument for the relevance of combinatorial knowledge bases applies for "synthetic" and "symbolic sectors", but in different forms. The paper investigages if the reliance on combinatorial knowledge bases leads to a better innovation performance and more radical forms of innovation than the use of more narrow knowledge assets. The paper investigates the relevance of combinatorial knowledge bases for innovation at first conceptually and based on respective literature. In the second part we analyse this question empirically by drawing on findings for the ICT sector in three regions of Austria (Vienna, Upper Austria, and Salzburg). (authors' abstract)Series: SRE - Discussion Paper