Industry Interconnectedness and Regional Economic Growth in Germany

Urban systems, and regions more generally, are the epicenters of many of today’s social issues. Yet they are also the global drivers of technological innovation, and thus it is critical that we understand their vulnerabilities and what makes them resilient to different types of shocks. We take regions to be systems composed of internal networks of interdependent components. As the connectedness of those networks increases, it allows information and resources to move more rapidly within a region. Yet, it also increases the speed and efficiency at which the effects of shocks cascade through the system. Here we analyzed regional networks of interdependent industries and how their structures relate to a region’s vulnerability to shocks. Methodologically, we utilized a metric of economic connectedness called tightness which quantifies a region’s internal connectedness relative to other regions. We calculated tightness for German regions during the Great Recession, comparing it to each region’s economic performance during the shock (2007–2009) and during recovery (2009–2011). We find that tightness is negatively correlated with changes in economic performance during the shock but positively during recovery. This suggests that regional economic planners face a tradeoff between being more productive or being more vulnerable to the next economic shock.

Evolution of industrial diversification and its determinants in West Germany: Evidence from population data of enterprises

Germany is among the largest countries in the world in terms of total GDP, owing largely to rapid industrialization and expansion of economic activities into several sectors. This paper contributes to the literature on German economic development by investigating the evolution of industry diversification in Germany; particularly focusing on the recent concepts of related (RV) and unrelated variety (UV) in West German regions. It also identifies the statistical and economic determinants of variation in variety over time. Among several industry structure measures; RV is the only measure that reveals a pronounced increasing trend. Since RV is composed of two parts: 1) entropy at five-digit within a two-digit classification, and 2) shares of two-digit sectors in total output, we examined which of the two components dominate. Our findings suggest that the entropy component within two-digit sectoral shares of the RV index is more dominant than the two-digit sectoral shares themselves. We further examined entries and exits of the firms among regions with top and bottom rankings in RV. Findings suggest that both the top and bottom regions experienced an increase in the total number of industries, however, exits were much less pronounced in the bottom regions. It suggests that an increase in variety among top regions is the result of the creative destruction type effect where new industries force inefficient old industries to leave the region. Finally, analysis shows support for the inverse u-shaped relationship between development and diversification.

Pandemics Initially Spread Among People of Higher (Not Lower) Social Status: Evidence From COVID-19 and the Spanish Flu

According to a staple in the social sciences, pandemics particularly spread among people of lower social status. Challenging this staple, we hypothesize that it holds true in later phases of pandemics only. In the initial phases, by contrast, people of higher social status should be at the center of the spread. We tested our phase-sensitive hypothesis in two studies. In Study 1, we analyzed region-level COVID-19 infection data from 3,132 U.S. regions, 299 English regions, and 400 German regions. In Study 2, we analyzed historical data from 1,159,920 U.S. residents who witnessed the 1918/1919 Spanish Flu pandemic. For both pandemics, we found that the virus initially spread more rapidly among people of higher social status. In later phases, that effect reversed; people of lower social status were most exposed. Our results provide novel insights into the center of the spread during the critical initial phases of pandemics.

Change in competence requirements due to the pandemic-related change in work organisation - A learning factory approach on machine learning in production companies

The research project "COVID 19 LL Lessons Learned", funded by the German Federal Ministry of Education and Research (BMBF), aims to identify successful solutions and measures that emerged in three different German regions through a systematic analysis during the pandemic. The regions under consideration are Bavaria (TU Munich), North Rhine-Westphalia (RWTH Aachen) and Saxony (TU Dresden). The aim of the project is to identify the problems that companies and organisations are facing and what they have learned from the change process so far. In this way, it is to be determined whether innovative and digital forms of work that have emerged as a result of the pandemic can provide positive impulses that can prove their worth in the working world in the medium and long term. One of the issues under consideration is the change in competence requirements due to the pandemic-related change in work organisation. The following human-technology-organisation process model was used for the project work.

Automated Event-Triggered GUI Testing and Bug Reproduction for Non-Android Applications

Today’s mobile gadgets are seamlessly incorporating innovative features demanded by the users. Most often, the applications contain bugs or functionality issues reported by the customers. The developers are responsible for reproducing such reported bugs, which are written in natural languages. Reproducing bugs from bug reports make the bug resolution inefficient. Nowadays, various methods are adopted to reproduce crash reports for android applications. But bug reproduction for non-android applications is still a challenging task. This paper proposes a novel approach that is capable of doing bug reproduction from bug reports to help the developers to solve the functionality issues of non-android applications in an automated manner. This approach uses a UI tester called the GUI engine, which is an excel sheet. The use cases which are to be tested can be filled in the GUI engine. All the use cases are to be filled based on a particular syntax. For that purpose, the developer can make use of a set of yaml files containing all the GUI information for all the screens of the application under test. The use cases are executed in the GUI engine and conclusions are made based on the test result. The GUI engine displays two colors green and red showing the working and failing of GUI components of the application under test. So that the developer can easily identify the failing components and take actions accordingly. The test has been done with more than 1000 test cases for one region and the result shows that almost all GUI components work for this method except for animation. It has tested for software developed for US, Europe, and German regions. Also, the proposed method is found to be much faster and efficient than the existing as well as manual testing methods.

Slaughter pigs as carrier of Listeria monocytogenes in Germany

Listeria (L.) monocytogenes as the cause of human listeriosis is widespread in the environment and a hazard considering food safety. Almost all animal species as well as humans can be asymptomatic carriers of this bacterium. In pigs, the tonsils are identified as the organ with the highest detection rate compared to other sample matrices. We sampled 430 pigs in total in two slaughterhouses in Northwest and East Germany, two structurally different and important regions in pig production, to re-examine pigs as a possible source of Listeria-contamination of pork products. We detected a low prevalence of L. monocytogenes in tonsil samples of 1.6% (7/430) on single animal level and of 11.6% (5/43) on herd level with no significant difference between the two German regions. Apart from L. monocytogenes, the usually non-pathogenic L. innocua had a prevalence of 1.2% (5/430) on single animal level. From 200 pigs from Northwest Germany, intestinal content samples were analysed in addition to tonsil samples from the same animals, but no positive sample was found for L. monocytogenes (0.0%, 0/200), while four pigs were positive for L. innocua (2.0%, 4/200). Although the prevalence of L. monocytogenes in tonsils is low, the risk of cross-contaminating meat with the pathogen is still given.

High Innovativeness of SMEs and the Configuration of Learning-by-Doing, Learning-by-Using, Learning-by-Interacting, and Learning-by-Science: a Regional Comparison Applying Fuzzy Qualitative Comparative Analysis

This paper proposes a holistic approach for investigating high innovation performance in SMEs by comparing different German regions. Invoking insights from the innovation mode concept and existing literature on regional innovation, we apply a qualitative comparative analysis (QCA) of 47 interviews with SMEs to show that high innovativeness is based on a bundle of conditions summarized as mechanisms of learning-by-doing, learning-by-using, learning-by-interacting, and learning-by-science. The results indicate that only parts of the DUI mode, in combination with the STI mode, can explain high innovativeness. This has implications for managers as well as for innovation policy, highlighting that there is no universal “best way” to become highly innovative.

Pandemics Initially Spread Among People of High (not Low) Social Status: Evidence from COVID-19 and the Spanish Flu

According to a staple in the social sciences, pandemics particularly spread among people of lower social status. Challenging this staple, we hypothesize that it holds true in later phases of pandemics only. In the initial phases, by contrast, people of higher social status should be at the center of the spread. To test this hypothesis, we conducted two studies. In Study 1, we analyzed region-level COVID-19 infection data from 3,132 U.S. regions, 299 English regions, and 400 German regions. In Study 2, we analyzed historical data from 1,159,920 U.S. residents who witnessed the 1918/1919 Spanish Flu pandemic. Both studies supported our hypothesis in full. During the initial phases of both pandemics, the virus spread more rapidly among people of higher social status. In later phases, that effect consistently reversed, rendering people of lower social status the primarily exposed. Our results provide novel insights into the center of the spread during the critical initial phases of pandemics.