Policy-driven EU Research Networks: Impact on the Greek S&T System

This paper focuses on the impact of EU-funded collaborative research networks at a national level using a combined method approach, social network analysis and in-depth case study work. First, it examines the participation intensity and role of the Greek organizations in the research network established through the Information Society Technologies priority of the European Community’s 4th, 5th and 6th Framework Programmes. Furthermore, it attempts to assess the impact of the IST research network on the diffusion and deployment of innovation in Greece. Some interesting results with significant policy implications arise: a) Greece exhibits high participation intensity in the EU-funded IST network, b) there are Greek organizations that have assumed an influential role in the network through time, in addition, they are also critical to the connectivity of the more peripheral Greek actors to the IST network, c) the value of the network, lies for the most part in indirect or ‘behavioural’ effects than in immediate project outputs measured in terms of commercialized products or services, d) however, while the knowledge obtained through the network assists organizations to gain better understanding of the market and identify future deployment opportunities this is not always possible due to the lack of sufficient infrastructure and national policies to support market introduction.

Dynamic Capabilities and their Indirect Impact on Firm Performance

This paper investigates the relationship between dynamic capabilities and firm performance. In particular it addresses the question of whether dynamic capabilities impact directly or indirectly on performance. Using data from manufacturing firms, the paper articulates and measures dynamic capabilities as a multi-dimensional construct with three underlying factors: coordination, learning and strategic competitive response. Then, structural equation modelling is employed to explore the relationships among dynamic capabilities, functional competences and firm performance. Empirical findings suggest that dynamic capabilities are antecedents to functional competences which in turn have a significant effect on performance. Direct effects on performance are found to be insignificant. Furthermore, similar effects seem to hold for both higher and lower levels of environmental dynamism. Theoretical and practical implications are discussed.Dynamic capabilities; functional competences; firm performance; indirect impact

The need for an industrial policy for long-term growth

We document and analyse key deficiencies of the Greek economy, with the view to providing new insights and articulate policy proposals. We consider issues which are the purview of both horizontal policies, raising productivity across sectors, and vertical policies, which allow for realignment of activity. With respect to the first dimension, we focus on two specific problem-areas of Greek industry, with high importance: skills and management practices. We also use information from a novel survey on entrepreneurship, technological developments, and regulatory change and examine structural characteristics of innovation and technology adoption of Greek firms, with a focus on the role of size, ownership structure, and global value chain participation. With respect to the second dimension, we provide an overview of Greece’s export performance and analyse its sectoral comparative advantage. In an empirical study we also focus on the determinants of export sophistication. Overall, the collection of our empirical findings provides ample fodder for concrete policy proposals to increase productivity in Greek manufacturing

Role of consumption in the design of the new Museum of Modern Art

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1998.Includes bibliographical references (p. 140-143).In recent years, museum architecture has been extensively subjected to cultural critique. Perceived as an instance of architects' stylistic yearnings, reflecting control strategies, promoting institutions' economic and cultural power, catering for education through forms that increasingly associate it with commercial environments and building structures, museum architecture is examined in this thesis as a significant ground for articulating the relation between cultural and consumer practices. Assuming that contemporary societies increasingly operate within a highly consumptive culture, where people seek new experiences through travel, leisurely activities and cultural exposure, and considering that the physical environment challenges and affects the perception of our material and immaterial worlds, we investigate the role of consumption in recent museum design. In so doing, this study focuses on the new expansion of the Museum of Modern Art in New York, a project that surprised critics both in its choice of participants and the conceptualization of its design process. We discuss the meaning of consumer culture in the context of cultural institutions, outline its effect on the definition of MoMA's institutional identity and study its role and expression in the conceptual and design phases towards the selection of the final project. The objective is to review and expand our understanding of the relationship between consumption and cultural production in museum spaces while aspiring to develop an operative framework for future thought and practice in the shaping of new architectural identities.by Christina Caloghirou.M.S

Spatial Interaction Modelling of Cross-Region R&D Collaborations Empirical Evidence from the EU Framework Programmes

The focus of this study is on cross-region R&D collaboration networks in the EU Framework Programmes (FP's). In contrast to most other empirical studies in this field, we shift attention to regions as units of analysis, i.e. we use aggregated data on research collaborations at the regional level. The objective is to identify determinants of cross-region collaboration patterns. In particular, we are interested whether geographical and technological distances are significant determinants of interregional cooperation. Further we investigate differences between intra-industry networks and public research networks (i.e. universities and research organisations). The European coverage is achieved by using data on 255 NUTS-2 regions of the 25 pre-2007 EU member-states, as well as Norway and Switzerland. We adopt a Poisson spatial interaction modelling perspective to analyse these questions. The dependent variable is the intensity of collaborative interactions between two regions, the independent variables are region-specific characteristics and variables that measure the separation between two regions such as geographical or technological distance. The results provide striking evidence that geographical factors are important determinants of cross-region collaboration intensities, but the effect of technological proximity is stronger. R&D collaborations occur most often between organisations that are located close to each other in technological space. Moreover geographical distance effects are significantly higher for intra-industry than for public research collaborations.Comment: 27 pages; presented at the 1st ICC International Conference on Network Modelling and Economic Systems, Lisbon, 200

Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing

Growing evidence suggests that radiation therapy (RT) doses to the heart and cardiac substructures (CS) are strongly linked to cardiac toxicities, though only the heart is considered clinically. This work aimed to utilize the superior soft-tissue contrast of magnetic resonance (MR) to segment CS, quantify uncertainties in their position, assess their effect on treatment planning and an MR-guided environment. Automatic substructure segmentation of 12 CS was completed using a novel hybrid MR/computed tomography (CT) atlas method and was improved upon using a 3-dimensional neural network (U-Net) from deep learning. Intra-fraction motion due to respiration was then quantified. The inter-fraction setup uncertainties utilizing a novel MR-linear accelerator were also quantified. Treatment planning comparisons were performed with and without substructure inclusions and methods to reduce radiation dose to sensitive CS were evaluated. Lastly, these described technologies (deep learning U-Net) were translated to an MR-linear accelerator and a segmentation pipeline was created. Automatic segmentations from the hybrid MR/CT atlas was able to generate accurate segmentations for the chambers and great vessels (Dice similarity coefficient (DSC) \u3e 0.75) but coronary artery segmentations were unsuccessful (DSC\u3c0.3). After implementing deep learning, DSC for the chambers and great vessels was ≥0.85 along with an improvement in the coronary arteries (DSC\u3e0.5). Similar accuracy was achieved when implementing deep learning for MR-guided RT. On average, automatic segmentations required ~10 minutes to generate per patient and deep learning only required 14 seconds. The inclusion of CS in the treatment planning process did not yield statistically significant changes in plan complexity, PTV, or OAR dose. Automatic segmentation results from deep learning pose major efficiency and accuracy gains for CS segmentation offering high potential for rapid implementation into radiation therapy planning for improved cardiac sparing. Introducing CS into RT planning for MR-guided RT presented an opportunity for more effective sparing with limited increase in plan complexity