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David B. Audretsch, Oliver Falck and Stephan Heblich

This comprehensive research review integrates pathbreaking and seminal scholarship from two interrelated fields – innovation and entrepreneurship. The authors seek to introduce and contextualize some of the most important research.
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David B. Audretsch, Oliver Falck and Stephan Heblich

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David B. Audretsch, Oliver Falck and Stephan Heblich

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David B. Audretsch, Oliver Falck and Stephan Heblich

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Edited by David B. Audretsch, Oliver Falck, Stephan Heblich and Adam Lederer

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Edited by David B. Audretsch, Oliver Falck, Stephan Heblich and Adam Lederer

Leading researchers use their outstanding expertise to investigate various aspects in the context of innovation and entrepreneurship such as growth, knowledge production and spillovers, technology transfer, the organization of the firm, industrial policy, financing, small firms and start-ups, and entrepreneurship education as well as the characteristics of the entrepreneur.
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David Oliver, Loizos Heracleous and Claus D. Jacobs

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Marlène Villanova-Oliver, David Noël, Jérôme Gensel and Pierre Le Quéau

The objective of this chapter is to contribute to a finer knowledge of the reasons why households make residential choices whose sequence generates a residential trajectory. Via a study of residential trajectories, it aims to make sense of urban migration processes and to understand the underlying reasons that cause people to move, at what time in their life and to what places: family- and job-related reasons, as well as factors related to leisure or other aspects of people’s lives. Describing and understanding migrations is a major tool for urban planning to make more informed decisions regarding housing supply, among others. This multidisciplinary research makes a contribution in terms of methods and tools to observe urban and/or peri-urban migration and to understand metropolitan dynamics. The preliminary findings show that this generic approach may be used to model multidimensional life course trajectories since individuals are observed from several perspectives: spatial, temporal and thematic. The other major feature of this approach is its integration of the capacity to explain the reasons behind a given choice. Villanova-Oliver, No'l, Gensel and Le Quéau also argue that this framework, which is rooted in the semantic web, is well equipped from the perspectives of methodology and software, which guarantees its relatively easy implementation. Finally, the authors discuss data collection issues in order to feed data to the model and as a precondition to analyse life course trajectories.