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Of key interest are the mechanisms that facilitate the transfer of routines and capabilities between organizations. Routines and capabilities do not automatically diffuse between organizations due to their tacit nature. Rather, they diffuse through mechanisms, particularly spillovers, spinoffs, labor mobility, mergers and acquisitions, and inter-organizational networks. This PhD thesis investigates how these mechanisms, in conjunction with relatedness, induce growth and structural change of local economies and plants. The key unit of interest is the composition of activities within regions and plants. To what extent are these compositions coherent as in consisting of related activities? How does the composition of activities affect the growth of activities? And how do new activities develop in certain compositions of activities and through which mechanisms? In investigating these questions, this PhD thesis starts the investigation at the regional level and gradually moves down the level of analysis, ending at the level of the economic establishment and individual worker. The following research questions are addressed: To what extent is the impact of related variety on regional employment growth conditioned by the technological intensity of the local industries concerned?; What determines the creation of knowledge transfer ties between organizations?; Compared to the benefits of co-location with firms in the same industry, to what extent do intra-industry mergers and acquisitions increase the performance of firms? And to what extent do intra-industry mergers and acquisitions foster the spatial clustering of an industry over time?; Who are the main agents of structural change in a region?; What is the impact of new influx of capabilities into plants, through the recruitment of top managers and top technicians, on plant diversification?

Sensor, weapon and command systems on board modern naval ships have a high dependence on support systems, particularly distributed fluid systems. Distributed Intelligent Networked Control Systems (DINCS) offers timely and efficient reconfiguration of these support systems in case of malfunctions or weapon-induced failures. Software agents contained within DINCS autonomously detect, isolate and reconfigure distributed fluid systems to maintain as much of the ship’s fight-through capability as possible. First this paper analyses the performance of DINCS with the survivability analysis tool RESIST (REsilience SImulation for Ship Targets) to validate the impact of DINCS on the ship’s survivability. This work determines the effects of weapon hits and assesses the combined consequences for the ship’s state after the incident. Results show that the fight-through capability, expressed as the number of tasks the ship is still able to perform in accordance with the command aim, increases strongly when using DINCS, whilst the vulnerability of the platform support systems to battle damage is minimised. Secondly, increased automation often raises questions about the impact on operator situational awareness. In this paper new Human Machine Interface (HMI) concepts for the DINCS technology demonstrator to improve the crewmembers’ situational awareness are discussed, with due consideration of relevant standards and legislation. These concepts support the operator in: presenting system status; monitoring and alerting on leaks and battle damage; displaying consequences of battle damage and informing the operator of autonomously conducted isolations and reconfigurations; suggesting solutions when DINCS is set to non-autonomous; presenting tasks for the ship’s crew to return to full operational capability and providing situational awareness at the correct level of detail. In multiple subject matter expert reviews, these designs have been improved iteratively by using cognitive walkthroughs of various scenarios. Furthermore the evaluation set-up to test the operator situational awareness of the final HMIdesign is described.

This study investigates the usefulness of exponential random graph models (ERGM) to analyze the determinants of cross-regional R&D collaboration networks. Using spatial interaction models, most research on R&D collaboration between regions is constrained to focus on determinants at the node level (e.g. R&D activity of a region) and dyad level (e.g. geographical distance between regions). ERGMs represent a new set of network analysis techniques that has been developed in recent years in mathematical sociology. In contrast to spatial interaction models, ERGMs additionally allow considering determinants at the structural network level while still only requiring cross-sectional network data. The usefulness of ERGMs is illustrated by an empirical study on the structure of the cross-regional R&D collaboration network of the German chemical industry. The empirical results confirm the importance of determinants at all three levels. It is shown that in addition to determinants at the node and dyad level, the structural network level determinant “triadic closure” helps in explaining the structure of the network. That is, regions that are indirectly linked to each other are more likely to be directly linked as well.

This paper investigates the impact of related variety on regional employment growth in Finland between 1993 and 2006 by means of a dynamic panel regression model.We find that related variety in general has no impact on growth. Instead, after separating related variety among low-and-medium-tech sectors from related variety among high-tech sectors, we find that only the latter affects regional growth. Hence, we find evidence that the effect of related variety on regional employment growth is conditioned by the technological intensity of the local sectors involved.

Using eye-tracking data, we examine the impact of motivation and repetition on visual attention to advertisements differing in argument quality. Our analyses indicate that repetition leads to an overall decrease in the amount of attention. However, while at first high motivation subjects attend to the ad for a longer time than low motivation subjects, this effect of motivation disappears after two exposures. More specifically, our results suggest that the second exposure counts most. In contrast, the order in which the ad elements am attended to is unaffected by repetition and motivation. Yet, the number of ad elements that are skipped becomes larger as the number of exposures increases. Implications of our results for theories of advertising repetition are formulated.

We report a study in which eye tracking data were gathered to examine the impact of time-pressure and task motivation on the flow of visual attention during choice processing from a naturalistic stimulus-based product display. We find patterns of adaptation of visual attention to time pressure in terms of acceleration, filtration, and strategy shift that have not been reported previously. In addition we find, regardless of condition, strong correlation's between visual attention to the brands in the choice set and preference for the brands. Results are discussed in terms of strategic and non-strategic information acquisition during stimulus-based choice, and implications for attention theory are offered. ispartof: DTEW Research Report 9670 pages:1-21 status: published

Deficiency of human fumarylacetoacetase (FAH) activity results in hereditary tyrosinemia type I. Using the restriction enzymes BglII, KpnI and StuI and a 1.3-kb cDNA probe for the FAH gene, we have found 6 restriction fragment length polymorphisms (RFLPs). These RFLPs were utilised in 3 tyrosinemia families in which one or both parents are carriers of both a tyrosinemia and a pseudodeficiency gene for FAH. Full information was obtained in two of these families. The polymorphisms identified 6 haplotypes. The haplotype distribution was significantly different in 32 unrelated tyrosinemia patients compared with a reference population of 100 individuals. The combined polymorphism information content was 0.77.