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Wie Roboter die Welt (und das Wirtschaften) verändern: Ein Überblick über Daten, Forschungsergebnisse und wirtschaftspolitische Strategien

  • Anne Jurkat , Rainer Klump EMAIL logo and Florian Schneider
Published/Copyright: August 20, 2024

Zusammenfassung

Der industrielle Einsatz von Robotern und die damit verbundenen Veränderungen wirtschaftlicher und sozialer Beziehungen sind ein schnell wachsendes Forschungsfeld. In diesem Beitrag geben Anne Jurkat, Rainer Klump und Florian Schneider einen Überblick über Datenquellen und aktuelle Ergebnisse der empirischen Forschung zum Robotereinsatz. Nach einer Präsentation der thematischen Schwerpunkte der Forschung erörtern sie die unterschiedlichen Analyseebenen und die drei zentralen Wirkungseffekte des Robotereinsatzes (Produktivitäts-, Substitutions- und Wiedereinsetzungseffekt). Abschließend analysieren sie die aktuellen wirtschaftspolitischen Strategien zum Umgang mit Robotik in Deutschland, die auf die Sicherung von Wettbewerbsfähigkeit und technologischer Souveränität abzielen.

Abstract

The industrial use of robots and the associated changes in economic and social relationships are a rapidly growing field of research. In this article, Anne Jurkat, Rainer Klump and Florian Schneider provide an overview of the data sources and current results of empirical research on the use of robots. After presenting the focal research areas, they discuss the different levels of analysis and the three most important effects of robotization (productivity, substitution and reinstatement effect). As a last point, they analyze current economic policy strategies for dealing with robotics in Germany which aim at securing competitiveness and technological sovereignty.

JEL Classification: O4; O47; O33; J24; E01
  1. Anmerkung: Anne Jurkat und Florian Schneider weisen darauf hin, dass sie in diesem Beitrag ihre persönliche Meinung äußern und nicht diejenige von IFR oder VDMA.

Literaturverzeichnis

Abeliansky, A., M. Beulmann und K. Prettner (2024), Are they coming for us? Industrial robots and the mental health of workers, Research Policy 53(3), 104956.10.1016/j.respol.2024.104956Search in Google Scholar

Abeliansky, A. und K. Prettner (2023), Automation and population growth: Theory and cross-country evidence, Journal of Economic Behavior & Organization 208, S. 345–58.10.1016/j.jebo.2023.02.006Search in Google Scholar

Acemoglu, D., C. Lelarge und P. Restrepo (2020), Competing with robots: Firm-level evidence from France, AEA Papers and Proceedings 110, S. 383–88.10.1257/pandp.20201003Search in Google Scholar

Acemoglu, D. und P. Restrepo (2018), The race between man and machine: Implications of technology for growth, factor shares, and employment, American Economic Review 108(6), S. 1488–542.10.1257/aer.20160696Search in Google Scholar

Acemoglu, D. und P. Restrepo (2019), Automation and new tasks: How technology displaces and reinstates labor, Journal of Economic Perspectives 33(2), S. 3–30.10.1257/jep.33.2.3Search in Google Scholar

Acemoglu, D. und P. Restrepo (2020), Robots and jobs: Evidence from US labor markets, Journal of Political Economy 128(6), S. 2188–244.10.1086/705716Search in Google Scholar

Acemoglu, D. und P. Restrepo (2022), Demographics and automation, The Review of Economic Studies 89(1), S. 1–44.10.1093/restud/rdab031Search in Google Scholar

Adachi, D. (2022), Robots and wage polarization: The effects of robot capital by occupations, unveröffentlichtes Manuskript.Search in Google Scholar

Adachi, D., D. Kawaguchi und Y. Saito (2024), Robots and employment: Evidence from Japan, 1978–2017, Journal of Labor Economics 42(2), S. 591–634.10.1086/723205Search in Google Scholar

Adão, R., M. Kolesár und E. Morales (2019), Shift-share designs: Theory and inference, The Quarterly Journal of Economics 134(4), S. 1949–2010.10.1093/qje/qjz025Search in Google Scholar

Aghion, P., C. Antonin und S. Bunel (2019), Artificial intelligence, growth and employment: The role of policy, Economie et Statistique/Economics and Statistics 510–511–512, S. 149–64.10.24187/ecostat.2019.510t.1994Search in Google Scholar

Aksoy, C., B. Özcan und J. Philipp (2021), Robots and the gender pay gap in Europe, European Economic Review 134, 103693.10.1016/j.euroecorev.2021.103693Search in Google Scholar

Albinowski, M. und P. Lewandowski (2024), The impact of ICT and robots on labour market outcomes of demographic groups in Europe, Labour Economics 87, 102481.10.1016/j.labeco.2023.102481Search in Google Scholar

Alguacil, M., A. Lo Turco und I. Martínez-Zarzoso (2022), Robot adoption and export performance: Firm-level evidence from Spain, Economic Modelling 114, 105912.10.1016/j.econmod.2022.105912Search in Google Scholar

Allianz Industrie 4.0 BW (2023), Lernen und Qualifizierung 4.0, online verfügbar unter: https://www.i40-bw.de/lernen/#lernfabriken.Search in Google Scholar

Anelli, M., I. Colantone und P. Stanig (2021), Individual vulnerability to industrial robot adoption increases support for the radical right, Proceedings of the National Academy of Sciences 118(47), e2111611118.10.1073/pnas.2111611118Search in Google Scholar

Anelli, M., O. Giuntella und L. Stella (2021), Robots, marriageable men, family, and fertility, Journal of Human Resources 1020-11223R1.10.2139/ssrn.3953014Search in Google Scholar

Antón, J.-I. et al. (2022), The labour market impact of robotisation in Europe, European Journal of Industrial Relations 095968012110708.10.1177/09596801211070801Search in Google Scholar

Artuc, E., L. Christiaensen und H. Winkler (2019), Does automation in rich countries hurt developing ones? Evidence from the U. S. and Mexico, World Bank Policy Research Working Paper 8741.10.1596/31425Search in Google Scholar

Backer, K. de und T. DeStefano (2021), Robotics and the global organisation of production, in: J. von Braun et al. (Hrsg.), Robotics, AI, and Humanity: Science, Ethics, and Policy, Cham, Springer International Publishing, S. 71–84.10.1007/978-3-030-54173-6_6Search in Google Scholar

Balcázar, C. (2022), Unions and robots: Automation and the power of labor, SSRN Electronic Journal.10.2139/ssrn.4360315Search in Google Scholar

Balsmeier, B. und M. Woerter (2019), Is this time different? How digitalization influences job creation and destruction, Research Policy 48(8), 103765.10.1016/j.respol.2019.03.010Search in Google Scholar

Barth, E. et al. (2020), How robots change within-firm wage inequality, IZA Discussion Paper 13605.10.2139/ssrn.3679011Search in Google Scholar

Bartik, T. (1991), Who benefits from state and local economic development policies?, Kalamazoo, Mich., W. E. Upjohn Institute for Employment Research.10.17848/9780585223940Search in Google Scholar

Bekhtiar, K., B. Bittschi und R. Sellner (2021), Robots at work? Pitfalls of industry level data, EconPol Working Paper 58.Search in Google Scholar

Benmelech, E. und M. Zator (2022), Robots and Firm Investment, NBER Working Paper 29676.10.3386/w29676Search in Google Scholar

Berger, T. und P. Engzell (2022), Industrial automation and intergenerational income mobility in the United States, Social Science Research 104, 102686.10.1016/j.ssresearch.2021.102686Search in Google Scholar

BMAS & BMBF – Bundesministerium für Arbeit und Soziales & Bundesministerium für Bildung und Forschung (2019), Nationale Weiterbildungsstrategie, online verfügbar unter https://www.bmbf.de/bmbf/de/bildung/weiterbildung/nationale-weiterbildungsstrategie/nationale-weiterbildungsstrategie_node.html.Search in Google Scholar

BMAS & BMBF – Bundesministerium für Arbeit und Soziales & Bundesministerium für Bildung und Forschung (2022), Fortführung und Weiterentwicklung Nationale Weiterbildungsstrategie: Gemeinsam für ein Jahrzehnt der Weiterbildung – Aufbruch in die Weiterbildungsrepublik, online verfügbar unter https://www.bmbf.de/bmbf/de/bildung/weiterbildung/nationale-weiterbildungsstrategie/nationale-weiterbildungsstrategie_node.html.Search in Google Scholar

BMBF – Bundesministerium für Bildung und Forschung (2021), Technologisch souverän die Zukunft gestalten: BMBF-Impulspapier zur technologischen Souveränität, online verfügbar unter https://www.bmbf.de/SharedDocs/Publikationen/de/bmbf/5/24032_Impulspapier_zur_technologischen_Souveraenitaet.html.Search in Google Scholar

BMBF – Bundesministerium für Bildung und Forschung (2023), Zukunftsstrategie Forschung und Innovation, online verfügbar unter https://www.bmbf.de/bmbf/de/forschung/zukunftsstrategie/zukunftsstrategie_node.html.Search in Google Scholar

BMDV – Bundesministerium für Digitales und Verkehr (2022), Digitalstrategie – Gemeinsam digitale Werte schöpfen, online verfügbar unter https://bmdv.bund.de/SharedDocs/DE/Anlage/K/presse/063-digitalstrategie.pdf?__blob=publicationFile.Search in Google Scholar

BMWi – Bundesministerium für Wirtschaft und Energie (2015), Industrie 4.0 und Digitale Wirtschaft: Impulse für Wachstum, Beschäftigung und Innovation, online verfügbar unter https://www.bmwk.de/Redaktion/DE/Publikationen/Industrie/industrie-4-0-und-digitale-wirtschaft.pdf%3F__blob%3DpublicationFile%26v%3D3.Search in Google Scholar

BMWi – Bundesministerium für Wirtschaft und Energie (2017), Entwicklung digitaler Technologien: Die Zukunft der Wirtschaft ist digital, online verfügbar unter https://www.digitale-technologien.de/DT/Redaktion/DE/Downloads/Publikation/entwicklung-digitaler-technologien.html.Search in Google Scholar

BMWi – Bundesministerium für Wirtschaft und Energie (2020), Entwicklung digitaler Technologien, online verfügbar unter https://www.bmwk.de/Redaktion/DE/Publikationen/Technologie/entwicklung-konvergenter-ikt.html.Search in Google Scholar

BMWi – Bundesministerium für Wirtschaft und Energie (2021a), Runderlass Außenwirtschaft Nr. 2/2021, siebzehnte Verordnung zur Änderung der Außenwirtschaftsverordnung, Bundesanzeiger AT 30.04.2021 B2.Search in Google Scholar

BMWi – Bundesministerium für Wirtschaft und Energie (2021b), Siebzehnte Verordnung zur Änderung der Außenwirtschaftsverordnung, Bundesanzeiger AT 30.04.2021 V1.Search in Google Scholar

BMWK – Bundesministerium für Wirtschaft und Klimaschutz (2023a), Das Mittelstand-Digital-Netzwerk, online verfügbar unter https://www.mittelstand-digital.de/MD/Navigation/DE/Home/home.html.Search in Google Scholar

BMWK – Bundesministerium für Wirtschaft und Klimaschutz (2023b), DeepTech & Climate Fonds (DTCF), online verfügbar unter https://www.foerderdatenbank.de/FDB/Content/DE/Foerderprogramm/Bund/BMWi/deeptech-climate-fonds.html.Search in Google Scholar

BMWK – Bundesministerium für Wirtschaft und Klimaschutz (2023c), Digital jetzt – Investitionsförderung für KMU, online verfügbar unter https://www.foerderdatenbank.de/FDB/Content/DE/Foerderprogramm/Bund/BMWi/digital-jetzt-investitionsfoerderung-kmu.html.Search in Google Scholar

Bonfiglioli, A. et al. (2021), Robots, offshoring and welfare, CEPR Discussion Paper 16363.10.4324/9781003275534-3Search in Google Scholar

Bonfiglioli, A. et al. (2023), Robot imports and firm-level outcomes, Center for European Studies Paper 528.10.1093/ej/ueae055Search in Google Scholar

Borjas, G. und R. Freeman (2019), From immigrants to robots: The changing locus of substitutes for workers, RSF: The Russell Sage Foundation Journal of the Social Sciences 5(5), S. 22–42.10.7758/rsf.2019.5.5.02Search in Google Scholar

Borusyak, K., P. Hull und X. Jaravel (2022), Quasi-experimental shift-share research designs, The Review of Economic Studies 89(1), S. 181–213.10.1093/restud/rdab030Search in Google Scholar

BPA – Bundespresseamt (2022), Zukunftsrat des Bundeskanzlers diskutiert Impulse für den Innovationsstandort Deutschland, Pressemitteilung 380, online verfügbar unter https://www.bundeskanzler.de/bk-de/aktuelles/-zukunftsrat-des-bundeskanzlers-diskutiert-impulse-fuer-den-innovationsstandort-deutschland--2152382.Search in Google Scholar

Brall, F. und R. Schmid (2023), Automation, robots and wage inequality in Germany: A decomposition analysis, LABOUR 37(1), S. 33–95.10.1111/labr.12236Search in Google Scholar

Brynjolfsson, E. et al. (2023), Robot hubs: The skewed distribution of robots in US manufacturing, AEA Papers and Proceedings 113, S. 215–18.10.1257/pandp.20231038Search in Google Scholar

Bundesregierung (2018), Strategie Künstliche Intelligenz der Bundesregierung, online verfügbar unter https://www.bundesregierung.de/resource/blob/997532/1550276/3f7d3c41c6e05695741273e78b8039f2/2018-11-15-ki-strategie-data.pdf.Search in Google Scholar

Bundesregierung (2020), Fünfzehnte Verordnung zur Änderung der Außenwirtschaftsverordnung, Drucksache 19/19781.Search in Google Scholar

Bundesregierung (2022), Fachkräftestrategie der Bundesregierung, online verfügbar unter https://www.bmas.de/DE/Service/Publikationen/Broschueren/fachkraeftestrategie-der-bundesregierung.html.Search in Google Scholar

Capello, R., C. Lenzi und G. Perucca (2022), The modern Solow paradox. In search for explanations, Structural Change and Economic Dynamics 63(C), S. 166–80.10.1016/j.strueco.2022.09.013Search in Google Scholar

Carbonero, F., E. Ernst und E. Weber (2020), Robots worldwide: The impact of automation on employment and trade, IAB Discussion Paper 7/2020.Search in Google Scholar

Casas, P. und J. Torres (2024), Government size and automation, International Tax and Public Finance 31(3), S. 1–28.10.1007/s10797-024-09833-0Search in Google Scholar

Caselli, M., A. Fracasso und S. Traverso (2021a), Globalization, robotization, and electoral outcomes: Evidence from spatial regressions for Italy, Journal of Regional Science 61(1), S. 86–111.10.1111/jors.12503Search in Google Scholar

Caselli, M., A. Fracasso und S. Traverso (2021b), Robots and risk of Covid-19 workplace contagion: Evidence from Italy, Technological Forecasting and Social Change 173, 121097.10.1016/j.techfore.2021.121097Search in Google Scholar

Caselli, M. et al. (2021), Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics, GLO Discussion Paper 802.10.2139/ssrn.3873155Search in Google Scholar

Cetrulo, A. und A. Nuvolari (2019), Industry 4.0: Revolution or hype? Reassessing recent technological trends and their impact on labour, Journal of Industrial and Business Economics 46(3), S. 391–402.10.1007/s40812-019-00132-ySearch in Google Scholar

Chen, Y., L. Cheng und C.-C. Lee (2022), How does the use of industrial robots affect the ecological footprint? International evidence, Ecological Economics 198, 107483.10.1016/j.ecolecon.2022.107483Search in Google Scholar

Cheng, H. et al. (2019), The rise of robots in China, Journal of Economic Perspectives 33(2), S. 71–88.10.1257/jep.33.2.71Search in Google Scholar

Cheng, H. et al. (2021), The future of labor: Automation and the labor share in the second machine age, Federal Reserve Bank of Philadelphia Working Paper 21-11.10.21799/frbp.wp.2021.11Search in Google Scholar

Cheng, X. et al. (2023), Labor-replacing automation and finance, SSRN Electronic Journal.Search in Google Scholar

Chiacchio, F., G. Petropoulos und D. Pichler (2018), The impact of industrial robots on EU employment and wages: A local labour market approach, bruegel Working Paper 02.Search in Google Scholar

Chugunova, M. et al. (2021), Robots, China and polls: Structural shocks and Political participation in the US, SSRN Electronic Journal.10.2139/ssrn.3929377Search in Google Scholar

Cilekoglu, A ., R. Moreno und R. Ramos (2024), The impact of robot adoption on global sourcing, Research Policy 53(3) 104953.10.1016/j.respol.2024.104953Search in Google Scholar

Compagnucci, F. et al. (2019), Robotization and labour dislocation in the manufacturing sectors of OECD countries: A panel VAR approach, Applied Economics 51(57), S. 6127–38.10.1080/00036846.2019.1659499Search in Google Scholar

Crafts, N. (2004), Steam as a general purpose technology: A growth accounting perspective, The Economic Journal 114(495), S. 338–51.10.1111/j.1468-0297.2003.00200.xSearch in Google Scholar

Cséfalvay, Z. und P. Gkotsis (2020), Global Race for robotisation – looking at the entire robotisation chain, JRC Technical Report 121184.10.1080/10438599.2020.1849968Search in Google Scholar

Cséfalvay, Z. (2020), Robotization in Central and Eastern Europe: Catching up or dependence?, European Planning Studies 28(8), S. 1534–53.10.1080/09654313.2019.1694647Search in Google Scholar

Cuccu, L. und V. Royuela (2024), Just reallocated? Robots displacement, and job quality, British Journal of Industrial Relations, online.10.1111/bjir.12805Search in Google Scholar

Dahlin, E. (2019), Are robots stealing our jobs?, Socius: Sociological Research for a Dynamic World 5, 237802311984624.10.1177/2378023119846249Search in Google Scholar

Damelang, A. und M. Otto (2023), Who is replaced by robots? Robotization and the risk of unemployment for different types of workers, Work and Occupations 51(2), 181–206.10.1177/07308884231162953Search in Google Scholar

Dauth, W. et al. (2021), The adjustment of labor markets to robots, Journal of the European Economic Association 19(6), S. 3104–53.10.1093/jeea/jvab012Search in Google Scholar

Dekle, R. (2020), Robots and industrial labor: Evidence from Japan, Journal of the Japanese and International Economies 58, 101108.10.1016/j.jjie.2020.101108Search in Google Scholar

Deng, L. et al. (2023), Labor shortage and early robotization in Japan, Economics Letters 233, 111404.10.1016/j.econlet.2023.111404Search in Google Scholar

Destatis (2022), Nutzung von Informations- und Kommunikationstechnologien (IKT) in Unternehmen, Qualitätsbericht 2022, online verfügbar unter https://www.destatis.de/DE/Methoden/Qualitaet/Qualitaetsberichte/Unternehmen/ikt-unternehmen-2022.pdf?__blob=publicationFile.Search in Google Scholar

DeStefano, T. und J. Timmis (2024), Robots and export quality, Journal of Development Economics 68, 103248.10.1016/j.jdeveco.2023.103248Search in Google Scholar

Dierker, W. (2023), Technologische Souveränität: Begriff und Voraussetzungen im transatlantischen Kontext, Wirtschaftsdienst 6/2023, S. 386–93.10.2478/wd-2023-0115Search in Google Scholar

Dixon, J. (2020), How to build a robots! database, Statistics Canada Analytical Studies: Methods and References 028.Search in Google Scholar

Dixon, J., B. Hong und L. Wu (2021), The robot revolution: Managerial and employment consequences for firms, Management Science 67(9), S. 5586–605.10.1287/mnsc.2020.3812Search in Google Scholar

Doorley, K. et al. (2023), Automation and income inequality in Europe, IZA Discussion Paper 16499.10.2139/ssrn.4669076Search in Google Scholar

Dottori, D. (2021), Robots and employment: Evidence from Italy, Economia Politica 38(2), S. 739–95.10.1007/s40888-021-00223-xSearch in Google Scholar

Duan, D. et al. (2023), Industrial robots and firm productivity, Structural Change and Economic Dynamics 67(2), S. 388–406.10.1016/j.strueco.2023.08.002Search in Google Scholar

Duch-Brown, N., F. Rossetti und R. Haarburger (2021), Evolution of the EU market share of robotics: Data and methodology, JRC Technical Report 124114.10.31219/osf.io/4exaySearch in Google Scholar

Edler, J. et al. (2020), Technologiesouveränität: Von der Forderung zum Konzept, Fraunhofer Institut für System- und Innovationsforschung Policy Brief 02/2020.Search in Google Scholar

EFI – Expertenkommission Forschung und Innovation (Hrsg.)(2022), Gutachten zu Forschung, Innovation und technologischer Leistungsfähigkeit Deutschlands 2022, online verfügbar unter https://www.e-fi.de/publikationen/gutachten.Search in Google Scholar

Eggleston, K., Y. Lee und T. Iizuka (2021), Robots and labor in the service sector: Evidence from nursing homes, NBER Working Paper 28322.10.3386/w28322Search in Google Scholar

EPRS – European Parliament Research Service (2021), Key enabling technologies for Europe’s technological sovereignty, Study PE 697184.Search in Google Scholar

EU-Kommission (2017), Attitudes towards the impact of digitisation and automation on daily life, Special Eurobarometer 460.Search in Google Scholar

EU-Kommission (2021), European citizens’ knowledge and attitudes towards science and technology: Special Eurobarometer 516.Search in Google Scholar

EU-Kommission (2023), European economic security strategy, online verfügbar unter https://ec.europa.eu/commission/presscorner/detail/en/IP_23_3358.Search in Google Scholar

Eurostat (2022), Nutzung von 3D Druckern und Robotern, nach Unternehmensgrößenklassen, online verfügbar unter https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_p3d__custom_10063349/default/table.Search in Google Scholar

Faber, M. (2020), Robots and reshoring: Evidence from Mexican labor markets, Journal of International Economics, 103384.10.1016/j.jinteco.2020.103384Search in Google Scholar

Fan, H., Y. Hu und L. Tang (2021), Labor costs and the adoption of robots in China, Journal of Economic Behavior & Organization 186(C), S. 608–31.10.1016/j.jebo.2020.11.024Search in Google Scholar

Feng, S. und S. Liu (2023), Does AI application matter in promoting carbon productivity? Fresh evidence from 30 provinces in China, Sustainability 15(23), 16261.10.3390/su152316261Search in Google Scholar

Fernández-Macías, E., D. Klenert und J.-I. Antón (2021), Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe, Structural Change and Economic Dynamics 58, S. 76–89.10.1016/j.strueco.2021.03.010Search in Google Scholar

Fossen, F., D. Samaan und A. Sorgner (2022), How are patented AI, software and robot technologies related to wage changes in the United States?, Frontiers in Artificial Intelligence 5/2022, 869282.10.3389/frai.2022.869282Search in Google Scholar

Frey, C. und M. Osborne (2017), The future of employment: How susceptible are jobs to computerisation?, Technological Forecasting and Social Change 114, S. 254–80.10.1016/j.techfore.2016.08.019Search in Google Scholar

Frey, C., T. Berger und C. Chen (2018), Political machinery: Did robots swing the 2016 US presidential election?, Oxford Review of Economic Policy 34(3), S. 418–42.10.1093/oxrep/gry007Search in Google Scholar

Fu, X. et al. (2021), Diffusion of industrial robotics and inclusive growth: Labour market evidence from cross country data, Journal of Business Research 122(C), S. 670–84.10.1016/j.jbusres.2020.05.051Search in Google Scholar

Ge, S. und Y. Zhou (2020), Robots, computers, and the gender wage gap, Journal of Economic Behavior & Organization 178, S. 194–222.10.1016/j.jebo.2020.07.014Search in Google Scholar

Gharascio, D., A. Piccirillo und J. Reljic (2024), Will robots replace workers? Assessing the impact of robots on employment and wages with meta-analysis, GLO Discussion Paper 1395.10.2139/ssrn.4750618Search in Google Scholar

Gihleb, R. et al. (2022), Industrial robots, workers’ safety, and health, Labour Economics 78, 102205.10.1016/j.labeco.2022.102205Search in Google Scholar

Giuntella, O. und T. Wang (2019), Is an army of robots marching on Chinese jobs?, IZA Discussion Paper 12281.10.2139/ssrn.3390271Search in Google Scholar

Goldsmith-Pinkham, P., I. Sorkin und H. Swift (2020), Bartik instruments: What, when, why, and how, The American Economic Review 110(8), S. 2586–624.10.1257/aer.20181047Search in Google Scholar

Gottwald, J.-C., J. Schild und D. Schmidt (2019), Das Ende der Naivität gegenüber China? Die Reform des europäischen Investitionskontrollregimes, Integration 42(2), S. 134–48.10.5771/0720-5120-2019-2-134Search in Google Scholar

Graetz, G. und G. Michaels (2018), Robots at work, The Review of Economics and Statistics 100(5), S. 753–68.10.1162/rest_a_00754Search in Google Scholar

Guenat, S. et al. (2022), Meeting sustainable development goals via robotics and autonomous systems, Nature Communications 13(1), 3559.Search in Google Scholar

Gunadi, C. und H. Ryu (2021), Does the rise of robotic technology make people healthier?, Health Economics 30(9), S. 2047–62.10.1002/hec.4361Search in Google Scholar

Haapanala, H., I. Marx und Z. Parolin (2023), Robots and unions: The moderating effect of organized labour on technological unemployment, Economic and Industrial Democracy 44(3), S. 827–52.10.1177/0143831X221094078Search in Google Scholar

Han, Y. (2022), The impact of industrial robots on the skill-based wage gap, American Journal of Industrial and Business Management 12(04), S. 571–602.10.4236/ajibm.2022.124031Search in Google Scholar

HEG-KI – Hochrangige Expertengruppe für künstliche Intelligenz (2019), Eine Definition der KI: Wichtigste Fähigkeiten und Wissenschaftsgebiete, online verfügbar unter https://www.bundesnetzagentur.de/DE/Fachthemen/Digitalisierung/Mittelstand/Downloads/Experten.pdf?__blob=publicationFile&v=1.Search in Google Scholar

Hötte, K., M. Somers und A. Theodorakopoulos (2023), Technology and jobs: A systematic literature review, Technological Forecasting and Social Change 194, 122750.10.1016/j.techfore.2023.122750Search in Google Scholar

Hötte, K., A. Theodorakopoulos und P. Koutroumpis (2024), Automation and taxation, Oxford Economic Paper gpae006.10.1093/oep/gpae006Search in Google Scholar

Huang, G., L.-Y. He und X. Lin (2022), Robot adoption and energy performance: Evidence from Chinese industrial firms, Energy Economics 107, 105837.10.1016/j.eneco.2022.105837Search in Google Scholar

Humlum, A. (2021), Robot adoption and labor market dynamics, unveröffentlichtes Manuskript.Search in Google Scholar

IFR – International Federation of Robotics (2020), World Robotics 2020: Industrial Robots, online verfügbar unter https://ifr.org/ifr-press-releases/news/record-2.7-million-robots-work-in-factories-around-the-globe.Search in Google Scholar

IFR – International Federation of Robotics (2022), Roboter helfen, die UN-Entwicklungsziele für Nachhaltigkeit zu erreichen, Pressemitteilung, online verfügbar unter https://ifr.org/downloads/press2018/DE-2022-05-05_IFR_Pressemeldung_UN-Goals.pdfSearch in Google Scholar

IFR – International Federation of Robotics (2023a), World Robotics 2023: Industrial Robots, online verfügbar unter https://ifr.org/ifr-press-releases/news/world-robotics-2023-report-asia-ahead-of-europe-and-the-americas.Search in Google Scholar

IFR – International Federation of Robotics (2023b), World Robotics 2023: Service Robots, online verfügbar unter https://ifr.org/wr-service-robots/.Search in Google Scholar

Jäger, A. et al. (2015), Analysis of the impact of robotic systems on employment in the European Union, Luxemburg, Publications Office of the EU.Search in Google Scholar

Jäger, A., C. Moll und C. Lerch (2016), Analysis of the impact of robotic systems on employment in the European Union – 2012 data update, Luxemburg, Publications Office of the EU.Search in Google Scholar

Jung, J. und D.-G. Lim (2020), Industrial robots, employment growth, and labor cost: A simultaneous equation analysis, Technological Forecasting and Social Change 159, 120202.10.1016/j.techfore.2020.120202Search in Google Scholar

Jungmittag, A. (2021), Robotisation of the manufacturing industries in the EU: Convergence or divergence?, The Journal of Technology Transfer 46(5), S. 1269–90.10.1007/s10961-020-09819-0Search in Google Scholar

Jurkat, A., R. Klump und F. Schneider (2022), Tracking the rise of robots: The IFR database, Jahrbücher für Nationalökonomie und Statistik 242(5–6), S. 669–89.10.1515/jbnst-2021-0059Search in Google Scholar

Jurkat, A., R. Klump und F. Schneider (2023), Robots and wages: A meta-analysis, ZBW – Leibniz Information Centre for Economics Working Paper.Search in Google Scholar

Kapetaniou, C. und C. Pissarides (2022), Productive robots and industrial employment: The role of national innovation systems, IZA Discussion Paper 15056.10.2139/ssrn.4114600Search in Google Scholar

KfW – Kreditanstalt für Wiederaufbau (2020), KfW Venture Capital Studie 2020: VC-Markt in Deutschland: Reif für den nächsten Entwicklungsschritt, Frankfurt, KfW.Search in Google Scholar

Klenert, D., E. Fernández-Macías und J.-I. Antón (2023), Do robots really destroy jobs? Evidence from Europe, Economic and Industrial Democracy 44(1), S. 280–316.10.1177/0143831X211068891Search in Google Scholar

Klump, R., A. Jurkat und F. Schneider (2021), Tracking the rise of robots: A survey of the IFR database and its applications, MPRA Paper 111812.Search in Google Scholar

Koch, M., I. Manuylov und M. Smolka (2021), Robots and firms, The Economic Journal 131(638), S. 2553–84.10.1093/ej/ueab009Search in Google Scholar

Krenz, A., K. Prettner und H. Strulik (2021), Robots, reshoring, and the lot of low-skilled workers, European Economic Review 136, 103744.10.1016/j.euroecorev.2021.103744Search in Google Scholar

Kromann, L. et al. (2020), Automation and productivity – A cross‐country, cross‐industry comparison, Industrial and Corporate Change 29(2), S. 265–87.10.1093/icc/dtz039Search in Google Scholar

Kugler, A. et al. (2020), U. S. robots and their impacts in the tropics: Evidence from Colombian labor markets, NBER Working Paper 28034.10.3386/w28034Search in Google Scholar

Lai, J., D. Zheng und J. Zhang (2022), The effect of industrial robots’ adoption on urban income inequality in China, Applied Economics Letters 30(17), S. 2388–95.10.1080/13504851.2022.2097176Search in Google Scholar

Leibrecht, M., J. Scharler und Y. Zhoufu (2023), Automation and unemployment: Does collective bargaining moderate their association?, Structural Change and Economic Dynamics 67(4), S. 264–76.10.1016/j.strueco.2023.08.006Search in Google Scholar

Leigh, N., B. Kraft und H. Lee (2020), Robots, skill demand and manufacturing in US regional labour markets, Cambridge Journal of Regions, Economy and Society 13(1), S. 77–97.10.1093/cjres/rsz019Search in Google Scholar

Li, J. et al. (2023), The impact of artificial intelligence on firms’ energy and resource efficiency: Empirical evidence from China, Resources Policy 82, 103507.10.1016/j.resourpol.2023.103507Search in Google Scholar

Li, Y. et al. (2022), Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms, Technology in Society 70, 102034.10.1016/j.techsoc.2022.102034Search in Google Scholar

Lin, C., S. Xiao und Z. Yin (2022), How do industrial robots applications affect the quality upgrade of Chinese export trade?, Telecommunications Policy 46(10), 102425.10.1016/j.telpol.2022.102425Search in Google Scholar

Liu, J. et al. (2020), Influence of artificial intelligence on technological innovation: Evidence from the panel data of China’s manufacturing sectors, Technological Forecasting and Social Change 158, 120142.10.1016/j.techfore.2020.120142Search in Google Scholar

Liu, J. et al. (2022a), The effect of artificial intelligence on carbon intensity: Evidence from China’s industrial sector, Socio-Economic Planning Sciences 83, 101002.10.1016/j.seps.2020.101002Search in Google Scholar

Liu, J. et al. (2022b), Can artificial intelligence improve the energy efficiency of manufacturing companies? Evidence from China, International Journal of Environmental Research and Public Health 19(4), 2091.10.3390/ijerph19042091Search in Google Scholar

Liu, L. et al. (2021), Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel, Economic Analysis and Policy 70, S. 276–93.10.1016/j.eap.2021.03.002Search in Google Scholar

Luan, F. et al. (2022), Industrial robots and air environment: A moderated mediation model of population density and energy consumption, Sustainable Production and Consumption 30, S. 870–88.10.1016/j.spc.2022.01.015Search in Google Scholar

Lv, H. et al. (2022), Intelligent manufacturing and carbon emissions reduction: Evidence from the use of industrial robots in China, International Journal of Environmental Research and Public Health 19(23), 15538.10.3390/ijerph192315538Search in Google Scholar

Mann, K. und D. Pozzoli (2023), Automation and low-skill labor, IZA Discussion Paper 15791.10.2139/ssrn.4664826Search in Google Scholar

Mao, F. et al. (2024), The impact of industrial intelligence on green development: Research based on intra- and inter-industry linkage effect, Clean Technologies and Environmental Policy 26(6), S. 1–18.10.1007/s10098-023-02700-2Search in Google Scholar

Martens, B. und S. Tolan (2018), Will this time be different? A review of the literature on the impact of artificial intelligence on employment, incomes and growth, JRC Digital Economy Working Paper 2018-08.10.2139/ssrn.3290708Search in Google Scholar

Matthes, J. (2020a), Technologietransfer durch Unternehmensübernahmen chinesischer Investoren, Wirtschaftsdienst 2020(8), S. 633–39.10.1007/s10273-020-2723-2Search in Google Scholar

Matthes, J. (2020b), Unternehmensübernahmen und Technologietransfer durch China: Gefahrenpotenziale und Gegenmaßnahmen, IW-Report 34/2020.Search in Google Scholar

Matthess, M. und S. Kunkel (2020), Structural change and digitalization in developing countries: Conceptually linking the two transformations, Technology in Society 63, S. 101428.10.1016/j.techsoc.2020.101428Search in Google Scholar

Matysiak, A., D. Bellani und H. Bogusz (2023), Industrial robots and regional fertility in European countries, European Journal of Population = Revue européenne de démographie 39(1), 11.10.1007/s10680-023-09657-4Search in Google Scholar

Milner, H. (2021), Voting for populism in Europe: Globalization, technological change, and the extreme right, Comparative Political Studies 54(13), S. 2286–320.10.1177/0010414021997175Search in Google Scholar

Mokyr, J., C. Vickers und N. Ziebarth (2015), The history of technological anxiety and the future of economic growth: Is this time different?, Journal of Economic Perspectives 29(3), S. 31–50.10.1257/jep.29.3.31Search in Google Scholar

Mondolo, J. (2021), The composite link between technological change and employment: A survey of the literature, Journal of Economic Surveys 36(4), S. 1027–68.10.1111/joes.12469Search in Google Scholar

Nie, Y. et al. (2023), How does the robot adoption promote carbon reduction? Spatial correlation and heterogeneity analysis, Environmental Science and Pollution Research 30(53), S. 113609–21.10.1007/s11356-023-30424-9Search in Google Scholar

O’Brien, R., E. Bair und A. Venkataramani (2022), Death by Robots? Automation and Working-Age Mortality in the United States, Demography 59(2), S. 607–28.10.1215/00703370-9774819Search in Google Scholar

O’Mahony, M. und M. Timmer (2009), Output, input and productivity measures at the industry level: The EU KLEMS database, The Economic Journal 119(538), F374–403.10.1111/j.1468-0297.2009.02280.xSearch in Google Scholar

OECD – Organisation für wirtschaftliche Zusammenarbeit und Entwicklung (2019), Determinants and impact of automation: An analysis of robots’ adoption in OECD countries, OECD Digital Economy Papers 277.Search in Google Scholar

OTA – Office of Technology Assessment (1984), Computerized Manufacturing Automation: Employment, Education, and the Workplace, OTA-CIT-235.Search in Google Scholar

Park, C.-Y., K. Shin und A. Kikkawa (2021), Aging, automation, and productivity in Korea, Journal of the Japanese and International Economies 59(5), 101109.10.1016/j.jjie.2020.101109Search in Google Scholar

Philbeck, T. und N. Davis (2018), The fourth industrial revolution: Shaping a new era, Journal of International Affairs 72(1), S. 17–22.Search in Google Scholar

Plümpe, V. und J. Stegmaier (2023), Micro data on robots from the IAB establishment panel, Jahrbücher für Nationalökonomie und Statistik 243(3–4), S. 397–413.10.1515/jbnst-2022-0045Search in Google Scholar

Qiu, J., C. Wan und Y. Wang (2024), Labor-saving innovations and capital structure, Journal of Corporate Finance 84, 102510.10.1016/j.jcorpfin.2023.102510Search in Google Scholar

Rodrigo, R. (2022), Robot adoption, organizational capital, and the productivity paradox, Working Papers gueconwpa 22-22-03, Georgetown University, Department of Economics.Search in Google Scholar

Savin, I., I. Ott und C. Konop (2022), Tracing the evolution of service robotics: Insights from a topic modeling approach, Technological Forecasting and Social Change 174, 121280.10.1016/j.techfore.2021.121280Search in Google Scholar

Schöll, N. und T. Kurer (2023), How technological change affects regional voting patterns, Political Science Research and Methods 12(1), S. 94–112.10.1017/psrm.2022.62Search in Google Scholar

Schuh, G. et al. (2020), Der Industrie 4.0 Maturity Index in der betrieblichen Anwendung: Aktuelle Herausforderungen, Fallbeispiele und Entwicklungstrends, acatech Kooperation.Search in Google Scholar

Schwab, K. (2016), The Fourth Industrial Revolution, Genf, World Economic Forum.Search in Google Scholar

Sedláček, T. (2012), Die Ökonomie von Gut und Böse, München, Carl Hanser.10.3139/9783446431133Search in Google Scholar

Sedik, T. und J. Yoo (2021), Pandemics and automation: Will the lost jobs come back?, IMF Working Paper 21/11.10.5089/9781513566849.001Search in Google Scholar

Skilton, M. und F. Hovsepian (2018), The 4th Industrial Revolution: Responding to the Impact of Artificial Intelligence on Business, Cham, Palgrave Macmillan.10.1007/978-3-319-62479-2_1Search in Google Scholar

Solow, R. (1987), We’d better watch out, New York Times Book Review vom 12. Juli.Search in Google Scholar

Song, J., Y. Chen und F. Luan (2023), Air pollution, water pollution, and robots: Is technology the panacea?, Journal of Environmental Management 330, 117170.10.1016/j.jenvman.2022.117170Search in Google Scholar

Sostero, M. (2020) Automation and Robots in Services: Review of Data and Taxonomy, JRC Working Papers Series on Labour, Education and Technology 2020/14.Search in Google Scholar

Stiebale, J., J. Suedekum und N. Woessner (2024), Robots and the rise of European superstar firms, International Journal of Industrial Organization 97, 103085.10.1016/j.ijindorg.2024.103085Search in Google Scholar

SVR – Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung (2016), Zeit für Reformen: Jahresgutachten 16/17, Wiesbaden, Sachverständigenrat.Search in Google Scholar

SVR – Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung (2019), Den Strukturwandel meistern: Jahresgutachten19/20. Wiesbaden, Sachverständigenrat.Search in Google Scholar

SVR – Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung (2023), Wachstumsschwäche überwinden – in die Zukunft investieren: Jahresgutachten 23/24, Wiesbaden, Sachverständigenrat.Search in Google Scholar

Thüringer Aufbaubank (2023), Digitalbonus Thüringen: Fördergrundsätze gemäß Ziffer 2.2 der Richtlinie vom 14.11.2022, Thüringer Staatsanzeiger 1/2023, S. 5.Search in Google Scholar

Traverso, F. (2021), Automation, trade and political outcomes: Evidence from the United States, SSRN Electronic Journal.10.2139/ssrn.3768590Search in Google Scholar

VDMA – Verband Deutscher Maschinen- und Anlagenbau (2023), Good Work Charter of the European Robotics Industry, online verfügbar unter https://www.vdma.org/documents/34570/62363944/110123_VDMA_GWC_Doppelseiten.pdf/1ba11367-42a5-6b36-52d2-fbacc867f64f?t=1677680938586.Search in Google Scholar

Vermeulen, B. et al. (2018), The impact of automation on employment: Just the usual structural change?, Sustainability 10(5), S. 1661.10.3390/su10051661Search in Google Scholar

Vries, G. de et al. (2020), The rise of robots and the fall of routine jobs, Labour Economics 66, 101885.10.1016/j.labeco.2020.101885Search in Google Scholar

Wambach, A. (2023), Renaissance der Industriepolitik, Wirtschaftsdienst 11/2023, S. 722–23.10.2478/wd-2023-0197Search in Google Scholar

Wang, J. (2022), Essays on Trade, Technology, and Banking, Dissertation, Harvard University Graduate School of Arts and Sciences.Search in Google Scholar

Wang, Y. und J. Feng (2022), The adoption of industrial robots and pollution abatement in China, Research Square preprint, online verfügbar unter https://www.researchsquare.com/article/rs-1346398/v1.10.21203/rs.3.rs-1346398/v1Search in Google Scholar

Webb, M. (2020), The Impact of Artificial Intelligence on the Labor Market, Working Paper, online verfügbar unter https://www.michaelwebb.co/webb_ai.pdf.10.2139/ssrn.3482150Search in Google Scholar

Wu, Q. (2023), Sustainable growth through industrial robot diffusion: Quasi‐experimental evidence from a Bartik shift‐share design, Economics of Transition and Institutional Change 31(4), S. 1107–33.10.1111/ecot.12367Search in Google Scholar

Yu, L., C. Zeng und X. Wei (2022), The impact of industrial robots application on air pollution in China: Mechanisms of energy use efficiency and green technological innovation, Science Progress 105(4), 00368504221144093.10.1177/00368504221144093Search in Google Scholar

Zhang, L., T. Gan und J. Fan (2023), Do industrial robots affect the labour market? Evidence from China, Economics of Transition and Institutional Change.10.1111/ecot.12356Search in Google Scholar

Zhang, L. und Q. Shen (2023), Carbon emission performance of robot application: Influencing mechanisms and heterogeneity characteristics, Discrete Dynamics in Nature and Society 2023(1), 4380575.10.1155/2023/4380575Search in Google Scholar

Zhang, Q., F. Zhang und Q. Mai (2022), Robot adoption and green productivity: Curse or Boon, Sustainable Production and Consumption 34, S. 1–11.10.1016/j.spc.2022.08.025Search in Google Scholar

Zhao, P., Y. Gao und X. Sun (2022), How does artificial intelligence affect green economic growth? Evidence from China, Science of The Total Environment 834, 155306.10.1016/j.scitotenv.2022.155306Search in Google Scholar

Zhou, P., M. Han und Y. Shen (2023), Impact of intelligent manufacturing on total-factor energy efficiency: Mechanism and improvement path, Sustainability 15(5), 3944.10.3390/su15053944Search in Google Scholar

Zhu, H. et al. (2023), Have industrial robots improved pollution reduction? A theoretical approach and empirical analysis, China & World Economy 31(4), S. 153–72.10.1111/cwe.12495Search in Google Scholar

Online erschienen: 2024-08-20
Erschienen im Druck: 2024-09-06

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