Digitale Arbeitswelt – Chancen und Herausforderungen für Beschäftigte und Arbeitsmarkt
Der digitale Wandel der Arbeitswelt gilt als eine der großen Herausforderungen für Wirtschaft und Gesellschaft. Wie arbeiten wir in Zukunft? Welche Auswirkungen hat die Digitalisierung auf Beschäftigung und Arbeitsmarkt? Welche Qualifikationen werden künftig benötigt? Wie verändern sich Tätigkeiten und Berufe?
Diese Infoplattform dokumentiert Forschungsergebnisse zum Thema Arbeit 4.0 in den verschiedenen Wirtschaftsbereichen.
- Forschung und Ergebnisse aus dem IAB
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte
- Bundesländer
- andere Länder/ internationaler Vergleich
- Besondere Personengruppen
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Literaturhinweis
The impact of ICT and robots on labour market outcomes of demographic groups in Europe (2024)
Zitatform
Albinowski, Maciej & Piotr Lewandowski (2024): The impact of ICT and robots on labour market outcomes of demographic groups in Europe. In: Labour Economics, Jg. 87. DOI:10.1016/j.labeco.2023.102481
Abstract
"We study the age- and gender-specific labour market effects of two key modern technologies, Information and Communication Technologies (ICT) and robots. Our sample includes 14 European countries between 2010 and 2018. We use the variation in technology adoption between industries and apply the instrumental variables strategy proposed by Acemoglu and Restrepo (2020) to identify the causal effects of technology adoption. We find that exposure to ICT and robots increased the shares of young and prime-aged women in employment and in the wage bills of particular sectors. However, it reduced the shares of older women and prime-aged men. We do not detect significant effects of technology adoption on the relative wages of most demographic groups. Between 2010 and 2018, the growth in ICT capital played a larger role than robot adoption in the changes in the withinsector labor market outcomes of demographic groups." (Author's abstract, IAB-Doku, ©2024 Elsevier) ((en))
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Literaturhinweis
De-Routinization in the Fourth Industrial Revolution - Firm-Level Evidence (2024)
Zitatform
Arntz, Melanie, Sabrina Genz, Terry Gregory, Florian Lehmer & Ulrich Zierahn-Weilage (2024): De-Routinization in the Fourth Industrial Revolution - Firm-Level Evidence. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16740), Bonn, 65 S.
Abstract
"This paper examines the extent to which aggregate-level de-routinization can be attributed to firm-level technology adoption during the most recent technological expansion. We use administrative data and a novel firm survey to distinguish frontier technologies from older technologies. We find that adopters of frontier technologies contribute substantially to deroutinization. However, this is driven only by a subset of these firms: large adopters replace routine jobs and less routine-intensive adopters experience faster growth. These scale and composition effects reflect firms' readiness to adopt and implement frontier technologies. Our results suggest that an acceleration of technology adoption would be associated with faster de-routinization and an increase in between-firm heterogeneity." (Author's abstract, IAB-Doku) ((en))
Beteiligte aus dem IAB
Lehmer, Florian;Weiterführende Informationen
auch erschienen als: ZEW DISCUSSION PAPER NR. 24-005 -
Literaturhinweis
Which Migrant Jobs are Linked with the Adoption of Novel Technologies, Robotization, and Digitalization? (2024)
Barišić, Antea; Ghodsi, Mahdi; Stehrer, Robert;Zitatform
Barišić, Antea, Mahdi Ghodsi & Robert Stehrer (2024): Which Migrant Jobs are Linked with the Adoption of Novel Technologies, Robotization, and Digitalization? (WIIW working paper 241), Wien, 66 S.
Abstract
"In recent decades, the development of novel technologies has intenzified due to globalization, prompting countries to enhance competitiveness through innovation. These technologies have significantly improved global welfare, particularly in sectors like healthcare, where they have facilitated tasks and boosted productivity, for example playing a crucial role in combating the COVID-19 pandemic. However, certain technologies, such as robots, can negatively impact employment by replacing workers and tasks. Additionally, the emergence of artificial intelligence as digital assets not only replaces specific tasks but also introduces complexities that may displace employees who are unable to adapt. While the existing literature extensively explores the heterogeneous effects of these technologies on labor markets, studies of their impact on migrant workers remain scarce. This paper presents pioneering evidence on the effects of various novel technologies on migrant employment in the European Union. The analysis covers 18 EU member states from 2005 to 2019 focusing on the impact of novel innovations, robot adoption, three types of digital assets, and total factor productivity, on migrant employment. The key findings reveal that innovations measured by the number of granted patents increase both the number and proportion of migrant workers relative to the overall workforce. While robots do replace jobs, their impact on native workers surpasses that of migrant workers, resulting in a higher share of migrant workers following robot adoption. Total factor productivity positively influences migrant workers, while the effects of digital assets are heterogeneous. Moreover, the impacts of these technologies on migrant workers vary significantly across different occupation types and educational levels." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Who is Replaced by Robots? Robotization and the Risk of Unemployment for Different Types of Workers (2024)
Zitatform
Damelang, Andreas & Michael Otto (2024): Who is Replaced by Robots? Robotization and the Risk of Unemployment for Different Types of Workers. In: Work and occupations, Jg. 51, H. 2, S. 181-206. DOI:10.1177/07308884231162953
Abstract
"We study the effects of robotization on unemployment risk for different types of workers. We examine the extent to which robotization increases inequality at the skill level and at the occupational level using two theoretical frameworks: skill-biased technological change and task-biased technological change. Empirically, we combine worker-level data with information on actual investments in industrial robots. Zooming in on the German manufacturing industry, our multivariate results show that robotization affects different types of workers differently. We do not observe an increase in unemployment risk for low- and medium-skilled, but we find a considerably lower unemployment risk among high-skilled workers. Moreover, the unemployment risk is significantly higher in occupations with highly substitutable tasks, but only in industries that invest largely in robots." (Author's abstract, IAB-Doku, © SAGE) ((en))
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Literaturhinweis
Rebalancing AI (2023)
Acemoglu, Daron; Johnson, Simon;Zitatform
Acemoglu, Daron & Simon Johnson (2023): Rebalancing AI. In: Finance and development, S. 26-29.
Abstract
"Optimistic forecasts regarding the growth implications of AI abound. AI adoption could boost productivity growth by 1.5 percentage points per year over a 10-year period and raise global GDP by 7 percent ($7 trillion in additional output), according to Goldman Sachs. Industry insiders offer even more excited estimates, including a supposed 10 percent chance of an “explosive growth” scenario, with global output rising more than 30 percent a year. All this techno-optimism draws on the “productivity bandwagon”: a deep-rooted belief that technological change— including automation—drives higher productivity, which raises net wages and generates shared prosperity. Such optimism is at odds with the historical record and seems particularly inappropriate for the current path of “just let AI happen,” which focuses primarily on automation (replacing people). We must recognize that there is no singular, inevitable path of development for new technology. And, assuming that the goal is to sustainably improve economic outcomes for more people, what policies would put AI development on the right path, with greater focus on enhancing what all workers can do?" (Text excerpt, IAB-Doku) ((en))
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Literaturhinweis
Robots and Workers: Evidence from the Netherlands (2023)
Zitatform
Acemoglu, Daron, Hans R. A. Koster & Ceren Ozgen (2023): Robots and Workers: Evidence from the Netherlands. (NBER working paper / National Bureau of Economic Research 31009), Cambridge, Mass, 60 S.
Abstract
"We estimate the effects of robot adoption on firm-level and worker-level outcomes in the Netherlands using a large employer-employee panel dataset spanning 2009-2020. Our firm-level results confirm previous findings, with positive effects on value added and hours worked for robot-adopting firms and negative outcomes on competitors in the same industry. Our worker-level results show that directly-affected workers (e.g., blue-collar workers performing routine or replaceable tasks) face lower earnings and employment rates, while other workers indirectly gain from robot adoption. We also find that the negative effects from competitors' robot adoption load on directly-affected workers, while other workers benefit from this industry-level robot adoption. Overall, our results highlight the uneven effects of automation on the workforce." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums (2023)
Agrawal, Ajay K.; Gans, Joshua S.; Goldfarb, Avi;Zitatform
Agrawal, Ajay K., Joshua S. Gans & Avi Goldfarb (2023): The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums. (NBER working paper / National Bureau of Economic Research 31767), Cambridge, Mass, 12 S.
Abstract
"We ask whether a technical objective of using human performance of tasks as a benchmark for AI performance will result in the negative outcomes highlighted in prior work in terms of jobs and inequality. Instead, we argue that task automation, especially when driven by AI advances, can enhance job prospects and potentially widen the scope for employment of many workers. The neglected mechanism we highlight is the potential for changes in the skill premium where AI automation of tasks exogenously improves the value of the skills of many workers, expands the pool of available workers to perform other tasks, and, in the process, increases labor income and potentially reduces inequality. We label this possibility the “Turing Transformation.” As such, we argue that AI researchers and policymakers should not focus on the technical aspects of AI applications and whether they are directed at automating human-performed tasks or not and, instead, focus on the outcomes of AI research. In so doing, our goal is not to diminish human-centric AI research as a laudable goal. Instead, we want to note that AI research that uses a human-task template with a goal to automate that task can often augment human performance of other tasks and whole jobs. The distributional effects of technology depend more on which workers have tasks that get automated than on the fact of automation per se." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Structural Labour Market Change, Cognitive Work, and Fertility in Germany (2023)
Zitatform
Bogusz, Honorata, Anna Matysiak & Michaela Kreyenfeld (2023): Structural Labour Market Change, Cognitive Work, and Fertility in Germany. (Working papers / Faculty of Economic Sciences, University of Warsaw 2023-08), Warsaw, 44 S.
Abstract
"Technological change and globalisation have been transforming the structure of labour demand in favour of workers performing cognitive tasks. Even though past research has found that labour force participation is an important determinant of fertility behaviour, few studies have addressed the fertility effects of the long-term structural changes of labour market. To fill this gap, we measure the cognitive task content of work at the occupation level using data from the Employment Survey of the German Federal Institute for Vocational Education and Training (BiBB). We link this contextual information with employment and fertility histories of women and men from the German Socio-Economic Panel 1984-2018 (GSOEP). With event history models, we find that fertility transitions of men working in occupations characterised by high cognitive task intensity are accelerated. We also observe elevated birth risks among women in occupations requiring cognitive labour. However, this pattern is more ambiguous, as we find that non-working women also experience elevated birth rates." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The macroeconomics of artificial intelligence (2023)
Brynjolfsson, Erik; Unger, Gabriel;Zitatform
Brynjolfsson, Erik & Gabriel Unger (2023): The macroeconomics of artificial intelligence. In: Finance and development, S. 20-25.
Abstract
"Economists have a poor track record of predicting the future. And Silicon Valley repeatedly cycles through hope and disappointment over the next big technology. So a healthy skepticism toward any pronouncements about how artificial intelligence will change the economy is justified. Nonetheless, there are good reasons to take seriously the growing potential of AI—systems that exhibit intelligent behavior, such as learning, reasoning, and problem-solving —to transform the economy, especially given the astonishing technica ladvances of the past year. AI may affect society in a number of areas besides the economy—including national security, politics, and culture. But in this article, we focus on the implications of AI on three broad areas of macroeconomic interest: productivity growth, the labor market, and industrial concentration. AI does not have a predetermined future. It can develop in very different directions. The particular future that emerges will be a consequence of many things, including technological and policy decisions made today. For each area, we present a fork in the road: two paths that lead to very different futures for AI and the economy. In each case, the bad future is the path of least resistance. Getting to the better future will require good policy—including • Creative policy experiments • A set of positive goals for what society wants from AI, not just negative outcomes to be avoided • Understanding that the technological possibilities of AI are deeply uncertain and rapidly evolving and that society must be flexible in evolving with them." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Does artificial intelligence kill employment growth: the missing link of corporate AI posture (2023)
Bughin, Jacques;Zitatform
Bughin, Jacques (2023): Does artificial intelligence kill employment growth: the missing link of corporate AI posture. In: Frontiers in artificial intelligence, Jg. 6. DOI:10.3389/frai.2023.1239466
Abstract
"Introduction An intense debate has been on-going about how artificial intelligence (AI) technology investments have an impact on employment. The debate has often focused on the potential of AI for human task automation, omitting the strategic incentive for firms to cooperate with their workers as to exploit AI technologies for the most relevant benefit of new product and service innovation. Method We calibrate an empirical probit regression model of how changes in employment relate to AI diffusion, based on formalizing a game-theoretical model of a firm exploiting the twin role of AI innovation and AI automation for both absolute and competitive advantage. Results The theoretical game-theory prediction is that employment following AI technology adoption is not negative, and ultimately depends on how AI leads to new success in innovation, competition which defines the competitive reward of innovation and profit sharing between workers and firms. Our estimation, is based on a global survey of 3,000 large companies across 10 countries, demonstrates that a firm employment growth depends on two strategic postures, that is, the firm relative maturity of AI adoption as well as its relative bias toward AI-based product innovation. Discussion The contribution of this research is to highlight the twin role of firm and workers in shaping how technology will affect employment. AI in particular marries the potential of task automation with even more potential for expansion." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Fall of the Labor Income Share: the Role of Technological Change and Hiring Frictions (2023)
Zitatform
Carbonero, Francesco, Enzo Weber & Christian J. Offermanns (2023): The Fall of the Labor Income Share: the Role of Technological Change and Hiring Frictions. In: Review of Economic Dynamics, Jg. 49, S. 251-268., 2022-01-09. DOI:10.1016/j.red.2022.09.001
Abstract
"Die Veränderungen in der funktionalen Einkommensverteilung erhalten in der Forschung viel Aufmerksamkeit. Wir dokumentieren einen durchschnittlichen Rückgang des labour share (Anteil des Faktors Arbeit an der Einkommensverteilung) von 8 Prozentpunkten für acht europäische Länder und die USA zwischen 1980 und 2007. Wir untersuchen theoretisch und empirisch zwei Mechanismen: Substitution zwischen Informations- und Kommunikationstechnologie (IKT) und Arbeit sowie Friktionen bei Beschäftigungsanpassungen. Wir finden, dass Substitution zwischen IKT und Arbeit wesentlich den Rückgang des labour share erklären kann. Wenn Arbeitsmarktfriktionen berücksichtigt werden, übernehmen diese allerdings einen Teil der Erklärungskraft. Insbesondere spielen Einstellungskosten in Europa eine größere Rolle als in den USA. Schließlich wird die Subsitutionselastizität zwischen IKT und Arbeit als Funktion institutioneller und struktureller Variablen modelliert und festgestellt, dass sie mit dem Anteil von Routine-Berufen positiv und mit dem Anteil hochqualifizierter Arbeiter negativ korreliert." (Autorenreferat, IAB-Doku)
Ähnliche Treffer
frühere (möglw. abweichende) Version: IAB-Discussion Paper 28/2017 -
Literaturhinweis
Why Hours Worked Decline Less after Technology Shocks? (2023)
Cardi, Olivier; Restout, Romain;Zitatform
Cardi, Olivier & Romain Restout (2023): Why Hours Worked Decline Less after Technology Shocks? (Economics working paper series / The Department of Economics, Lancaster University Management School 2023,07), Lancaster, 187 S.
Abstract
"The contractionary effect of aggregate technology shocks on hours worked has shrunk over time in OECD countries. Our estimates suggest that this finding can be attributed to the increasing share of the variance of technology improvements driven by asymmetric technology shocks across sectors. While technology improvements uniformly distributed across sectors are found empirically to give rise to a dramatic decline in total hours worked, asymmetric technology shocks do the opposite. By depreciating non-traded prices, symmetric technology shocks generate a contractionary effect on non-traded labor and thus on total hours. In contrast, by appreciating non-traded prices, technological change concentrated toward traded industries puts upward pressure on wages which has a strong expansionary effect on total hours worked. A two-sector open economy model with frictions into the movements of inputs can reproduce the time-increasing response of both total and sectoral hours worked we estimate empirically once we allow for factor-biased technological change and we let the share of asymmetric technology shocks increase over time. A model with endogenous technology decisions reveals that two-third of the progression of asymmetric technology shocks is driven by greater exposition of traded industries to the international stock of knowledge." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation, digitalization and decarbonization in the European automotive industry: a roadmap towards a just transition (2023)
Zitatform
Cetrulo, Armanda, Giovanni Dosi, Angelo Moro, Linnea Nelli & Maria Enrica Virgillito (2023): Automation, digitalization and decarbonization in the European automotive industry: a roadmap towards a just transition. (LEM working paper series / Laboratory of Economics and Management 2023,36), Pisa, 30 S.
Abstract
"This position paper outlines the characteristics of the trends at stake in affecting the twin transition in the European automotive industry, and the political economy of the actors behind such transition. We first describe the automation and digitalization processes in the automotive sector and their effects on employment. Possible scenarios are analysed, illustrating actual cases of electrification conversion of some European plants of the key OEMs companies as practical examples to understand the employment effects. We then consider the role of the regulatory push in fostering the transition of the automotive sector towards electrification, highlighting the non-neutrality of the process and the risk of a quite limited space for decarbonization. Finally, we discuss the space and capacity of trade unions' actions to orient the twin transition toward social and climate justice." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI technologies and employment: micro evidence from the supply side (2023)
Zitatform
Damioli, Giacomo, Vincent Van Roy, Daniel Vertesy & Marco Vivarelli (2023): AI technologies and employment: micro evidence from the supply side. In: Applied Economics Letters, Jg. 30, H. 6, S. 816-821. DOI:10.1080/13504851.2021.2024129
Abstract
"In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000–2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The employment impact of AI technologies among AI innovators (2023)
Zitatform
Damioli, Giacomo, Vincent Van Roy, Daniel Vertesy & Marco Vivarelli (2023): The employment impact of AI technologies among AI innovators. (MSI discussion paper / KU Leuwen 2306),: KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven 36 S.
Abstract
"This study supports the labour-friendly nature of product innovation among developers of artificial intelligence (AI) technologies. GMM-SYS estimates on a worldwide longitudinal dataset covering 3,500 companies that patented inventions related to AI technologies over the period 2000-2016 show a positive and significant impact of AI patent families on employment. The effect is small in magnitude and limited to service sectors and younger firms, which are front-runners of the AI revolution. We also detect some evidence of increasing returns suggesting that innovative companies more focused on AI technologies are those obtaining larger impacts in terms of job creation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and Income Inequality in Europe (2023)
Zitatform
Doorley, Karina, Jan Gromadzki, Piotr Lewandowski, Dora Tuda & Philippe Van Kerm (2023): Automation and Income Inequality in Europe. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16499), Bonn, 44 S.
Abstract
"We study the effects of robot penetration on household income inequality in 14 European countries between 2006–2018, a period marked by the rapid adoption of industrial robots. Automation reduced relative hourly wages and employment of more exposed demographic groups, similarly to the results for the United States. Using robot-driven wage and employment shocks as input to the EUROMOD microsimulation model, we find that automation had minor effects on income inequality. Household labour income diversification and tax and welfare policies largely absorbed labour market shocks caused by automation. Transfers played a key role in cushioning the transmission of these shocks to household incomes." (Author's abstract, IAB-Doku) ((en))
Ähnliche Treffer
auch erschienen als ibs working paper 06/2023 -
Literaturhinweis
Wer mit KI-Technologien erfolgreich sein will, sollte die Wirkungen valide abschätzen können (2023)
Zitatform
Fregin, Marie-Christine & Michael Stops (2023): Wer mit KI-Technologien erfolgreich sein will, sollte die Wirkungen valide abschätzen können. In: Ifo-Schnelldienst, Jg. 76, H. 8, S. 12-15., 2023-08-16.
Abstract
"Marie-Christine Fregin, Universität Maastricht, und Michael Stops, Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg, zeigen, dass die KI bisher insgesamt wenig quantitative Beschäftigungseffekte verursacht hat, da KI-Systeme in der deutschen Wirtschaft noch recht wenig verbreitet sind. Zudem müssten Beschäftigte bei der Einführung neuer Systeme oftmals neue Tätigkeiten ausführen und teilweise erlernen; andererseits sei erwartbar, dass bestimmte Tätigkeiten, die bisher den Beschäftigten vorbehalten waren, von der KI unterstützt und manchmal sogar übernommen werden könnten. Unternehmen sollten wissen, wie der Erfolg einer Technologieeinführung zu messen sei." (Textauszug, IAB-Doku)
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Literaturhinweis
Digitalization is not gender-neutral (2023)
Zitatform
Genz, Sabrina & Claus Schnabel (2023): Digitalization is not gender-neutral. In: Economics Letters, Jg. 230. DOI:10.1016/j.econlet.2023.111256
Abstract
"Using unique linked employer-employee data for Germany and a matching approach, we provide novel insights on the individual-level employment effects of digitalization. We show that the first-time introduction of digital technology in an establishment affects women more strongly than men. This holds both in terms of lower days employed and higher days unemployed. We find that employment losses are largest for individuals conducting non-routine tasks, and again it is women who suffer the most. Our insights imply that digitalization is not gender-neutral, suggesting that it is important to avoid a gender bias in technological progress." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
The puzzle of changes in employment and wages in routine task-intensive occupations (2023)
Zitatform
Ghosh, Pallab & Zexuan Liu (2023): The puzzle of changes in employment and wages in routine task-intensive occupations. In: Empirical economics, Jg. 65, H. 4, S. 1965-1980. DOI:10.1007/s00181-023-02394-x
Abstract
"Autor and Dorn (Am Econ Rev 103(5):1553–1597, 2013) provide an explanation of the polarization of US employment and wages for the period 1980–2005. Using the 1980 Census and 2005 American Community Survey data, this study replicates the estimation results of Autor and Dorn (2013) for employment polarization in all major occupation groups and qualitatively matches the wage polarization results. Also, we investigate the puzzle of why employment and wages changed in opposite directions only in clerical and administrative support occupations in 1980–2005." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Wer profitiert von der Digitalisierung? Deutschlandweite Follow-up-Studie zu Entwicklungsverläufen und Unterschiedseffekten bei Beschäftigten verschiedener Industriebranchen und Tätigkeitsfelder (2023)
Härtwig, Christian; Sapronova, Anna; Sigmund, Nils-Levin;Zitatform
Härtwig, Christian, Anna Sapronova & Nils-Levin Sigmund (2023): Wer profitiert von der Digitalisierung? Deutschlandweite Follow-up-Studie zu Entwicklungsverläufen und Unterschiedseffekten bei Beschäftigten verschiedener Industriebranchen und Tätigkeitsfelder. In: Zeitschrift für Arbeitswissenschaft, Jg. 77, H. 4, S. 578-592. DOI:10.1007/s41449-023-00386-2
Abstract
"Bei der Digitalisierung werden oft verschiedene Szenarien diskutiert wie eine mögliche Substitution, eine Polarisierung zwischen verschiedenen Qualifikationsniveaus oder ein allgemeines Upgrading von Arbeit; eine breite empirische Datenbasis fehlt jedoch zumeist. Mit dem „Monitor Digitalisierung “ liegt eine der größten deutschlandweiten Follow-up-Studien in verschiedenen Industriebranchen vor. In der Ersterhebung 2019 zeigte sich, dass die Digitalisierung noch am Anfang stand und geprägt war durch IKT. Bedeutsame Unterschiede lagen eher zwischen Blue- und White-Collar-Tätigkeitsfeldern als zwischen einzelnen Branchen. Bei der Zweitbefragung 2022 mit 11.316 Befragten aus 1559 Betrieben zeigte sich als allgemeiner Trend eine zunehmende IKT-Nutzung und digitale Unterstützung sowie stabil-positive Veränderungsbereitschaft und Digitale Selbstwirksamkeit, aber auch höhere Belastung, mäßige betriebliche Unterstützungsformen und zunehmende Kognitive Irritation. Digitalisierungsspezifische Unterschiede zwischen White- und Blue-Collar-Tätigkeitsfeldern verfestigten bzw. verstärkten sich: Meist profitierten von der Digitalisierung eher Beschäftigte aus IT, Leitung, Verwaltung oder Forschung und Entwicklung, während Beschäftigte aus Produktion, Technik, Logistik, Service und Labor ungünstigere Werte und Veränderungen berichteten. Für die Diskussion der Entwicklungsszenarien zeigte sich, dass allgemeine Substitutionsvermutungen derzeit eher zu verwerfen sind, die Entwicklungen vielmehr eher als zunehmende digitale Durchdringung und Diversifizierung angesehen werden kann. Praktische Relevanz : Es werden Disparitäten zwischen verschiedenen Beschäftigtengruppen aufgezeigt. Bei der Einführung digitaler Systeme sollten sowohl allgemein wirksame Effekte, als auch Belange spezifischer Tätigkeitsgruppen v. a. aus dem Blue-Collar-Bereich in den Blick genommen werden." (Autorenreferat, IAB-Doku)
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- Forschung und Ergebnisse aus dem IAB
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
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- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
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