In recent years, climate change and its economic effects increasingly have become the focus of public attention. Previous investigations, however, have dealt with large spatial units and thus have blurred small-scale distinctions. This paper analyses the future economic impacts of climate change at the regional level in order to ascertain local positive and negative development trends. To this end, scenarios based on different climate, societal and economic trends are used to estimate on an unprecedented small scale prospective tourism demand and the derived economic development for the districts studied.

This article explores entrepreneurship research in Germany, paying particular attention to its origins and current "re-emergence." Since the late 1990s, the field has gained ground, as is reflected in an increasing number of entrepreneurship chairs at universities, and the establishment of an annual national entrepreneurship conference. A particular strength of the German approach to researching entrepreneurship, which can be traced back directly to the historical roots, is found to be its consideration of context specificity and embeddedness, going hand-in-hand with a strong multidisciplinary tendency. These are two features where entrepreneurship research in Germany could add a distinctive flavor to the current mainstream debate. In practice, the diffusion of this perspective is inhibited by an insufficient exchange with the international scientific community.

No abstract

Executive Summary2. Development of AI competencies across society: We do not only need top research. We also need broadly distributed AI competencies in society. Thus AI should not only be taught in computer sciences, but core AI modules should also be integrated into engineering and natural science programs, and be taught at schools of applied sciences.3. Data as a basic resource for AI development: A strong AI ecosystem needs data for research and for the development of AI applications in industry, particularly with regard to deep learning (DL). This dimension of the ecosystem needs far more attention in Germany. Possible approaches to mobilize data for AI include the development of data pools and more advanced methods of anonymizing or synthesizing data. It is hard to compete with the big Internet platforms from the United States and China in terms of quantity of data. Instead, special emphasis on machine data, quality of data and alternative approaches to AI that can work with little data could be the cornerstones of an alternative path to a strong AI ecosystem. 4. Infrastructure demands for AI: Deep learning requires not only huge amounts of data but also great computing power. A national AI strategy would address the question of how we can ensure middle-and longterm access to the most powerful processing hardware possible for German AI research and applications. 5. AI development and AI application in the economy: The German economy and industry already struggles with digitalization. AI exacerbates this issue because it represents the next step of digitalization. Smalland medium-sized businesses in Germany, known as the Mittelstand, especially need support. This support could be, for example, through state-funded AI laboratories, in which companies can experiment with AI with little risk and at low costs. Mobilizing venture capital through public funds and providing better incentives for AI investments represent two more critical challenges.6. Societal dimension of AI: The ethical and regulatory questions regarding AI need to be openly discussed and require input from many different stakeholders in German society. Here, we already see numerous initiatives and approaches, representing the topic's arrival on the political agenda. However, more has to be done to make AI competencies and technologies more familiar within society. 7. A national AI strategy in an international context: Germany can only succeed in the international competition in the long-term as part of an EU-wide approach. Striving for cooperation with France offers the chance to push for a comprehensive European AI strategy. Germany, and Europe as a whole, have to become more conscious of their strategic interests in AI and act accordingly.A German AI strategy should focus on the ecosystem approach and propose concrete ideas and recommendations. The strategy also needs to address how we can identify and, if possible, measure how the strategy is being implemented, and how the AI ecosystem in Germany is developing. There are many important indica...

No abstract