The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector
| Název práce: | The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector |
|---|---|
| Autor(ka) práce: | Do, Thi Ngoc Huyen |
| Typ práce: | Diploma thesis |
| Vedoucí práce: | Mazouch, Petr |
| Oponenti práce: | Lichard, Tomáš |
| Jazyk práce: | English |
| Abstrakt: | This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change. |
| Klíčová slova: | Technological change; employment dynamics; workforce transformation; panel data analysis |
| Název práce: | The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector |
|---|---|
| Autor(ka) práce: | Do, Thi Ngoc Huyen |
| Typ práce: | Diplomová práce |
| Vedoucí práce: | Mazouch, Petr |
| Oponenti práce: | Lichard, Tomáš |
| Jazyk práce: | English |
| Abstrakt: | This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change. |
| Klíčová slova: | Technological change; workforce transformation; panel data analysis; employment dynamics |
Informace o studiu
| Studijní program / obor: | Economic Data Analysis/Data Analysis and Modeling |
|---|---|
| Typ studijního programu: | Magisterský studijní program |
| Přidělovaná hodnost: | Ing. |
| Instituce přidělující hodnost: | Vysoká škola ekonomická v Praze |
| Fakulta: | Fakulta informatiky a statistiky |
| Katedra: | Katedra ekonomické statistiky |
Informace o odevzdání a obhajobě
| Datum zadání práce: | 8. 4. 2025 |
|---|---|
| Datum podání práce: | 5. 5. 2025 |
| Datum obhajoby: | 2. 6. 2025 |
| Identifikátor v systému InSIS: | https://insis.vse.cz/zp/92117/podrobnosti |