matching – Suchprozesse am Arbeitsmarkt
Offene Stellen bei gleichzeitiger Arbeitslosigkeit - was Arbeitsmarkttheorien u. a. mit "unvollkommener Information" begründen, ist für Unternehmen und Arbeitsuchende oft nur schwer nachzuvollziehen: Unternehmen können freie Stellen nicht besetzen, trotzdem finden Arbeitsuchende nur schwer den passenden Job. Wie gestalten sich die Suchprozesse bei Unternehmen und Arbeitsuchenden, welche Konzessionen sind beide Seiten bereit einzugehen, wie lässt sich das "matching" verbessern?
Diese Infoplattform bietet wissenschaftliche Literatur zur theoretischen und empirischen Auseinandersetzung mit dem Thema.
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Literaturhinweis
How workers and firms meet in the labor market and why it matters (2024)
Zitatform
Carillo-Tudela, Carlos, Leo Kaas & Benjamin Lochner (2024): How workers and firms meet in the labor market and why it matters. (VoxEU columns / Centre for Economic Policy Research), London, o. Sz.
Abstract
"Most firms match with workers through job postings, networks of personal contacts, or the public employment agency. This column investigates the effects of search channels on labor market outcomes in Germany. Low-wage firms and low-wage workers are more likely to match via networks or the public agency, while high-wage firms and high-wage workers succeed more often via job postings. Because search channels connect workers and firms at different rungs of the wage distribution, matching technologies matter not only for individual job search outcomes, but also for aggregate employment, productivity, and wage inequality." (Author's abstract, IAB-Doku, © VOXEU) ((en))
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Literaturhinweis
Social media and hiring: a survey experiment on discrimination based on online social class cues (2024)
Zitatform
Galos, Diana Roxana (2024): Social media and hiring: a survey experiment on discrimination based on online social class cues. In: European Sociological Review, Jg. 40, H. 1, S. 116-128. DOI:10.1093/esr/jcad012
Abstract
"Discrimination based on social class is challenging to study, and therefore likely to be underappreciated due to its subtle nature. Social class is often difficult to gauge from traditional resumes, yet, the expansion of social networking platforms provides employers with an additional source of information. Given that many individuals have a social media presence today, employers can increasingly rely on additional information gleaned from such online platforms (e.g., Twitter, Instagram), which may alter hiring decisions. To study the role of social networking platforms vis-à-vis potential discrimination based on social class cues, I leverage an original online survey experiment in the United States. The aim of the investigation is (i) to measure the effect of cultural markers of social class expressed on social media profiles in a hypothetical hiring situation and (ii) to analyse potential channels that might explain class-based discrimination. I show that subjects favour the upper-class-signalling candidate over the lower-class-signalling candidate and that perceived competence and perceived warmth are two channels through which class-based discrimination may occur. The individual’s online presence might not be part of the formal application process, yet it seems to shape inferences about individuals’ employability, competence, and warmth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
No Thanks, Dear AI! Understanding the Effects of Disclosure and Deployment of Artificial Intelligence in Public Sector Recruitment (2024)
Keppeler, Florian;Zitatform
Keppeler, Florian (2024): No Thanks, Dear AI! Understanding the Effects of Disclosure and Deployment of Artificial Intelligence in Public Sector Recruitment. In: Journal of Public Administration Research and Theory, Jg. 34, H. 1, S. 39-52. DOI:10.1093/jopart/muad009
Abstract
"Applications based on artificial intelligence (AI) play an increasing role in the public sector and invoke political discussions. Research gaps exist regarding the disclosure effects—reactions to disclosure of the use of AI applications—and the deploymenteffect—efficiency gains in data savvy tasks. This study analyzes disclosure effects and explores the deployment of an AI application in a preregistered field experiment (n = 2,000) co-designed with a public organization in the context of employer-driven recruitment. The linear regression results show that disclosing the use of the AI application leads to significantly less interest in an offer among job candidates. The explorative analysis of the deployment of the AI application indicates that the person–job fit determined by the leaders can be predicted by the AIapplication. Based on the literature on algorithm aversion and digital discretion, this study provides a theoretical and empirical disentanglement of the disclosure effect and the deployment effect to inform future evaluations of AI applications in the public sector. It contributes to the understanding of how AI applications can shape public policy and management decisions, and discusses the potential benefits and downsides of disclosing and deploying AI applications in the public sector and in employer-driven recruitment." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech (2023)
Avery, Mallory; Vecci, Joseph; Leibbrandt, Andreas;Zitatform
Avery, Mallory, Andreas Leibbrandt & Joseph Vecci (2023): Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech. (Discussion paper / Monash University, Department of Economics 2023-09), Clayton, 69 S.
Abstract
"The use of Artificial Intelligence (AI) in recruitment is rapidly increasing and drastically changing how people apply to jobs and how applications are reviewed. In this paper, we use two field experiments to study how AI in recruitment impacts gender diversity in the male-dominated technology sector, both overall and separately for labor supply and demand. We find that the use of AI in recruitment changes the gender distribution of potential hires, in some cases more than doubling the fraction of top applicants that are women. This change is generated by better outcomes for women in both supply and demand. On the supply side, we observe that the use of AI reduces the gender gap in application completion rates. Complementary survey evidence suggests that this is driven by female jobseekers believing that there is less bias in recruitment when assessed by AI instead of human evaluators. On the demand side, we find that providing evaluators with applicants' AI scores closes the gender gap in assessments that otherwise disadvantage female applicants. Finally, we show that the AI tool would have to be substantially biased against women to result in a lower level of gender diversity than found without AI." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Heterogeneity in firms’ recruitment practices: New evidence from representative employer data (2023)
Zitatform
Brändle, Tobias, Philipp Grunau, Michael Haylock & Patrick Kampkötter (2023): Heterogeneity in firms’ recruitment practices: New evidence from representative employer data. In: German Journal of Human Resource Management, Jg. 37, H. 2, S. 107-136., 2022-07-21. DOI:10.1177/23970022221118346
Abstract
"The hiring and recruitment process is one of the main challenges to the success of companies and a significant driver of total labor costs. We use representative employer data for German private-sector establishments with at least 50 employees to explore recent developments in employer search, selection, and screening activities over the years of 2012–2018. We document changes in hiring policies over time and address heterogeneity across establishments related to size, ownership, and industry sector. Our results show that although establishment characteristics are correlated with different facets of hiring behavior, there is no homogeneous pattern for employer search and selection instruments. We highlight differences of hiring practices targeted at managerial versus non-managerial new hires. Finally, we outline potential mechanisms and research gaps for future work and discuss managerial implications." (Author's abstract, IAB-Doku, © SAGE) ((en))
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Literaturhinweis
Entrepreneurship, the initial labor force, and the location of new firms (2023)
Zitatform
Carias, Cristina, Steven Klepper & Rui Baptista (2023): Entrepreneurship, the initial labor force, and the location of new firms. In: Small business economics, Jg. 60, H. 3, S. 865-890. DOI:10.1007/s11187-022-00618-5
Abstract
"We propose that new firm founders locate their firms close to their home region in order to hire workers they know about through their prior employment, since it is easier to find high productivity employees among talent pools for which you have significant personal experience. We test our proposition using a matched employer–employee dataset for Portugal. Consistent with our predictions, new firms in the same industry as their founder's prior employer (i.e., spinoffs) are more likely to locate in their founder's home region, to hire workers from the founder's prior employer and other firms in the same region and industry, to employ them longer, and to perform better than other new firms. Results suggest that the agglomeration of high performing spinoffs next to their parent firms should facilitate the emergence of successful industrial clusters." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Matching Through Search Channels (2023)
Zitatform
Carillo-Tudela, Carlos, Leo Kaas & Benjamin Lochner (2023): Matching Through Search Channels. (IAB-Discussion Paper 10/2023), Nürnberg, 85 S. DOI:10.48720/IAB.DP.2310
Abstract
"Firmen und Arbeitnehmer/-innen finden überwiegend über Stellenanzeigen, persönliche Kontaktnetzwerke oder die Bundesagentur für Arbeit zueinander. All diese Suchkanäle tragen dazu bei, Friktionen am Arbeitsmarkt zu verringern. In diesem Papier untersuchen wir, inwieweit diese Suchkanäle unterschiedliche Auswirkungen auf den Arbeitsmarkt haben. Anhand einer neuen Datenverknüpfung aus administrativer Daten und Umfragedaten zeigen wir: (i) Niedriglohnfirmen und Niedriglohnbeziehende finden vermehrt über Netzwerke oder die Bundesagentur für Arbeit zueinander, währendessen Hochlohnfirmen und Hochlohnbeziehende häufiger über Stellenanzeigen zusammenkommen. (ii) Dabei nutzen Firmen Stellenanzeigen vor allem bei der Abwerbung und Gewinnung von Hochlohnbeziehenden. Im Vergleich zu anderen Suchkanälen, werden Stellenanzeigen auch vermehrt von Beschäftigten beim Aufstieg auf der Karriereleiter genutzt. Um die Auswirkungen dieser Beobachtungen auf die aggregierte Beschäftigung, die Löhne und die Arbeitsmarktsortierung zu bewerten, schätzen wir strukturell ein Gleichgewichtsmodell, das sich durch Karriereleitern, zweiseitige Heterogenität, mehrere Suchkanäle und endogene Einstellungsintensität auszeichnet. Die Schätzung zeigt, dass Netzwerke der kosteneffizienteste Kanal sind, der es Firmen ermöglicht, schnell einzustellen, aber auch Arbeitskräfte mit geringeren durchschnittlichen Fähigkeiten anzuziehen. Stellenanzeigen sind der kostspieligste Kanal, erleichtern die Einstellung von Arbeitnehmern/-innen mit höheren Fähigkeiten und sind für die Sortierung zwischen Beschäftigten und Firmen am wichtigsten. In kontrafaktischen Berechnungen zeigt sich, dass obwohl die Bundesagentur für Arbeit die geringste Einstellungswahrscheinlichkeit bietet, ihre hypothetische Abschaffung beträchtliche Folgen hätte. Die Gesamtbeschäftigung würde um mindestens 1,4 Prozent sinken und die Lohnungleichheit steigen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Matching Through Search Channels (2023)
Zitatform
Carrillo-Tudela, Carlos, Leo Kaas & Benjamin Lochner (2023): Matching Through Search Channels. (CESifo working paper 10761), München, 32 S.
Abstract
"Firms and workers predominately match via job postings, networks of personal contacts or the public employment agency, all of which help to ameliorate labor market frictions. In this paper we investigate the extent to which these search channels have differential effects on labor market outcomes. Using novel linked survey-administrative data we document that (i) low-wage firms and low-wage workers are more likely to match via networks or the public agency, while high-wage firms and high-wage workers succeed more often via job postings; (ii) job postings help firms the most in poaching and attracting high-wage workers and help workers the most in climbing the job ladder. To evaluate the implications of these findings for employment, wages and labor market sorting, we structurally estimate an equilibrium job ladder model featuring two-sided heterogeneity, multiple search channels and endogenous recruitment effort. The estimation reveals that networks are the most cost-effective channel, allowing firms to hire quickly, yet attracting workers of lower average ability. Job postings are the most costly channel, facilitate hiring workers of higher ability, and matter most for worker-firm sorting. Although the public employment agency provides the lowest hiring probability, its removal has sizeable consequences, with aggregate employment declining by at least 1.4 percent and rising bottom wage inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Matching Through Search Channels (2023)
Zitatform
Carrillo-Tudela, Carlos, Leo Kaas & Benjamin Lochner (2023): Matching Through Search Channels. (CEPR discussion paper / Centre for Economic Policy Research 18575), London, 32 S.
Abstract
"Firms and workers predominately match via job postings, networks of personal contacts or the public employment agency, all of which help to ameliorate labor market frictions. In this paper we investigate the extent to which these search channels have differential effects on labor market outcomes. Using novel linked survey-administrative data we document that (i) low-wage firms and low-wage workers are more likely to match via networks or the public agency, while high-wage firms and high-wage workers succeed more often via job postings; (ii) job postings help firms the most in poaching and attracting high-wage workers and help workers the most in climbing the job ladder. To evaluate the implications of these findings for employment, wages and labor market sorting, we structurally estimate an equilibrium job ladder model featuring two-sided heterogeneity, multiple search channels and endogenous recruitment effort. The estimation reveals that networks are the most cost-effective channel, allowing firms to hire quickly, yet attracting workers of lower average ability. Job postings are the most costly channel, facilitate hiring workers of higher ability, and matter most for worker-firm sorting. Although the public employment agency provides the lowest hiring probability, its removal has sizeable consequences, with aggregate employment declining by at least 1.4 percent and rising bottom wage inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Recruitment Policies, Job-Filling Rates and Matching Efficiency (2023)
Zitatform
Carrillo-Tudela, Carlos, Hermann Gartner & Leo Kaas (2023): Recruitment Policies, Job-Filling Rates and Matching Efficiency. In: Journal of the European Economic Association, Jg. 21, H. 6, S. 2413-2459., 2023-01-09. DOI:10.1093/jeea/jvad034
Abstract
"Recruitment intensity is important for the matching process in the labor market. Using unique linked survey-administrative data, we investigate the relationships between hiring and recruitment policies at the establishment level. Faster hiring goes along with higher search effort, lower hiring standards and more generous wages. We develop a directed search model that links these patterns to the employment adjustments of heterogenous firms. The model provides a novel structural decomposition of the matching function that we use to evaluate the relative importance of these recruitment policies at the aggregate level. The calibrated model shows that hiring standards play an important role in explaining differences in matching efficiency across labor markets defined as region/skill cross products and for the impact of labor market policy, whereas search effort and wage policies play only a minor role." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Matching through Search Channels (2023)
Zitatform
Carrillo-Tudela, Carlos, Leo Kaas & Benjamin Lochner (2023): Matching through Search Channels. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16583), Bonn, 37 S.
Abstract
"Firms and workers predominately match via job postings, networks of personal contacts or the public employment agency, all of which help to ameliorate labor market frictions. In this paper we investigate the extent to which these search channels have differential effects on labor market outcomes. Using novel linked survey-administrative data we document that (i) low-wage firms and low-wage workers are more likely to match via networks or the public agency, while high-wage firms and high-wage workers succeed more often via job postings; (ii) job postings help firms the most in poaching and attracting high-wage workers and help workers the most in climbing the job ladder. To evaluate the implications of these findings for employment, wages and labor market sorting, we structurally estimate an equilibrium job ladder model featuring two-sided heterogeneity, multiple search channels and endogenous recruitment effort. The estimation reveals that networks are the most cost-effective channel, allowing firms to hire quickly, yet attracting workers of lower average ability. Job postings are the most costly channel, facilitate hiring workers of higher ability, and matter most for worker-firm sorting. Although the public employment agency provides the lowest hiring probability, its removal has sizeable consequences, with aggregate employment declining by at least 1.4 percent and rising bottom wage inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Viel hilft viel?! – Welche Wege Betriebe nutzen, um Ausbildungsplatzbewerber/-innen zu finden und wie erfolgreich sie damit sind (2023)
Ebbinghaus, Margit; Heyer, Philipp; Gerhards, Christian; Mohr, Sabine;Zitatform
Ebbinghaus, Margit, Christian Gerhards, Philipp Heyer & Sabine Mohr (2023): Viel hilft viel?! – Welche Wege Betriebe nutzen, um Ausbildungsplatzbewerber/-innen zu finden und wie erfolgreich sie damit sind. (BIBB-Report 2023,03), 16 S.
Abstract
"Auf dem Ausbildungsmarkt wird es für Betriebe zunehmend eng. Die Anzahl ausbildungssuchender Jugendlicher ist seit Jahren rückläufig, was es für mehr und mehr Betriebe zu einer Herausforderung werden lässt, die angebotenen Ausbildungsplätze zu besetzen. Das wirft die Frage auf, wie Betriebe vorgehen, um Ausbildungsplatzbewerber/-innen für sich zu gewinnen. Zur Beantwortung dieser Frage nimmt der vorliegende BIBB Report die von Betrieben genutzten Rekrutierungswege in den Blick. Es zeigt sich, dass sowohl die Anzahl als auch die Art genutzter Rekrutierungswege damit zusammenhängen, ob Betriebe viele Bewerbungen erhalten und alle Ausbildungsplätze besetzen können." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Langzeitarchivierung Nationalbibliothek -
Literaturhinweis
Inefficient Labor Market Sorting (2023)
Eckel, Carsten; Yeaple, Stephen R.;Zitatform
Eckel, Carsten & Stephen R. Yeaple (2023): Inefficient Labor Market Sorting. (Discussion paper / Rationality & Competition, CCR TRR 190 437), München ; Berlin, 47 S.
Abstract
"A growing empirical literature attributes much of the productivity advantages of large, "superstar" firms to their adoption of best practice management techniques that allow them to better identify and use talented workers. The reasons for the incomplete adoption of these "structured management practices" and their welfare implications are not well understood. This paper provides a positive and normative analysis of these issues in a theoretical framework in which structured management practices induce sorting of talent across firms. Incomplete adoption arises because worker talent is in limited supply. In equilibrium there is excessive adoption of structured management practices and too much sorting of talented workers into large firms. In this second-best environment, policy changes that favor large firms, such as trade liberalization, have the potential to lower welfare." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
ChatGPT, Chatbots und mehr – wie wird künstliche Intelligenz in den HR-Abteilungen von Unternehmen genutzt? (2023)
Garnitz, Johanna; Schaller, Daria;Zitatform
Garnitz, Johanna & Daria Schaller (2023): ChatGPT, Chatbots und mehr – wie wird künstliche Intelligenz in den HR-Abteilungen von Unternehmen genutzt? In: Ifo-Schnelldienst, Jg. 76, H. 9, S. 65-68.
Abstract
"Das ifo Institut befragt im Auftrag von Randstad Deutschland quartalsweise deutsche HR-Abteilungen zu personalpolitisch relevanten Themen. Das aktuelle Schwerpunktthema befasst sich mit dem Einsatz von Künstlicher Intelligenz, insbesondere in den HR-Abteilungen. Derzeit nutzen ca. 5% der befragten Unternehmen Künstliche Intelligenz im HR-Bereich, geplant haben dies weitere 25% der Unternehmen. Ein Viertel der Unternehmen ergreift Maßnahmen für den (geplanten) Einsatz von KI, und zwar am häufigsten in Form von Arbeits- und Expertengruppen (53%), gefolgt von Fortbildungen (43%). 86% der Teilnehmenden sind hinsichtlich des Einsatzes von KI skeptisch. Trotzdem sehen sie Potenzial für KI im Personalbereich, besonders im Bereich der Automatisierung von Personalprozessen, in der Rekrutierung und im Bewerbermanagement." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Public Employment Agency Reform, Matching Efficiency, and German Unemployment (2023)
Zitatform
Merkl, Christian & Timo Sauerbier (2023): Public Employment Agency Reform, Matching Efficiency, and German Unemployment. (SOEPpapers on multidisciplinary panel data research at DIW Berlin 1185), Nürnberg, 51 S.
Abstract
"Our paper analyzes the role of public employment agencies in job matching, in particular the effects of the restructuring of the Federal Employment Agency in Germany (Hartz III labor market reform) for aggregate matching and unemployment. Based on two microeconomic datasets, we show that the market share of the Federal Employment Agency as job intermediary declined after the Hartz reforms. We propose a macroeconomic model of the labor market with a private and a public search channel and fit the model to various dimensions of the data. We show that direct intermediation activities of the Federal Employment Agency did not contribute to the decline in unemployment in Germany. By contrast, improved activation of unemployed workers reduced unemployed by 0.8 percentage points. Through the lens of an aggregate matching function, more activation is associated with a larger matching efficiency." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Why Personal Ties (Still) Matter: Referrals and Congestion (2023)
Mylius, F.;Zitatform
Mylius, F. (2023): Why Personal Ties (Still) Matter: Referrals and Congestion. (Cambridge working papers in economics 2356), Cambridge, 21 S.
Abstract
"The internet has reduced search costs significantly, making it much easier to apply for a large number of jobs. In spite of that, the share of jobs found through personal contacts has remained stable over the past decades. My theoretical framework explores a new channel that makes referred candidates favorable for firms: a higher likelihood to accept a job offer. This trait becomes particularly advantageous whenever firms face large uncertainty over whether their candidates would accept their job offer. As we see, if search barriers vanish and workers apply to more firms, a referred candidate expects to face more competitors. On the other hand, with more applications being sent out, workers are, on average, less interested in each firm they apply to, which makes referred candidates stand out more. This means the chances of getting a job offer through a referral can increase if competing workers send out more applications." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
More Than a Match: “Fit” as a Tool in Hiring Decisions (2023)
Zitatform
Nichols, Bethany J., David S. Pedulla & Jeff T. Sheng (2023): More Than a Match: “Fit” as a Tool in Hiring Decisions. In: Work and occupations online erschienen am 17.12.2023, S. 1-29. DOI:10.1177/07308884231214279
Abstract
"The concept of “fit” has become important for understanding hiring decisions and labor market outcomes. While social scientists have explored how fit functions as a legitimized evaluative criterion to match candidates to jobs in the hiring process, less is known about how fit functions as a hiring tool to aid in decision-making when hiring decisions cannot—or should not—be justified. Drawing on in-depth interviews with 53 hiring professionals, we develop a theoretical argument that hiring professionals can use fit as a tool to circumvent legitimized hiring criteria and justify their hiring goals. Specifically, we show how hiring professionals use fit as a tool to explain their hiring decisions when these decisions cannot or should not be justified and we outline two mechanisms through which this process occurs: (1) fit as a tool for circumventing human capital concerns, and (2) fit as a tool to circumvent hiring policies based upon social characteristics. We argue that fit is more than an evaluative criterion for matching individuals to jobs. Hiring professionals deploy fit as a tool to justify their decisions amid uncertainty and constraint. Fit, then, becomes a placeholder when these hiring decisions are not able to be justified through legitimized means. Our findings reveal some of the potential negative consequences of using fit during the hiring process and contribute important theoretical insights about the role of fit in scholarship on inequality and labor markets." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial intelligence and labour market matching (2023)
Zitatform
OECD. Directorate for Employment, Labour and Social Affairs (2023): Artificial intelligence and labour market matching. (OECD social, employment and migration working papers 284), Paris, 86 S. DOI:10.1787/2b440821-en
Abstract
"While still in its infancy, Artificial Intelligence (AI) is increasingly used in labour market matching, whether by private recruiters, public and private employment services, or online jobs boards and platforms. Applications range from writing job descriptions, applicant sourcing, analysing CVs, chat bots, interview schedulers, shortlisting tools, all the way to facial and voice analysis during interviews. While many tools promise to bring efficiencies and cost savings, they could also improve the quality of matching and jobseeker experience, and even identify and mitigate human bias. There are nonetheless some barriers to a greater adoption of these tools. Some barriers relate to organisation and people readiness, while others reflect concerns about the technology and how it is used, including: robustness, bias, privacy, transparency and explainability. The present paper reviews the literature and some recent policy developments in this field, while bringing new evidence from interviews held with key stakeholders." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Studie zur Arbeitsplatzsituation in der Akut- und Langzeitpflege und Ermittlung sowie modellhafte Implementierung von Indikatoren für gute Arbeitsbedingungen in der Langzeitpflege: Ergebnissynthese von Los 1 und Los 2: Studienbericht für das Bundesministerium für Gesundheit (2022)
Braeseke, Grit;Zitatform
(2022): Studie zur Arbeitsplatzsituation in der Akut- und Langzeitpflege und Ermittlung sowie modellhafte Implementierung von Indikatoren für gute Arbeitsbedingungen in der Langzeitpflege. Ergebnissynthese von Los 1 und Los 2: Studienbericht für das Bundesministerium für Gesundheit. (Gesundheit - Mobilität - Bildung - Wohnen), Berlin, 12 S.
Abstract
"Ziel der im Rahmen der Konzertierten Aktion Pflege (KAP) initiierten Arbeitsplatzstudie war es, geeignete Maßnahmen zu identifizieren, mit denen der Arbeitsplatz Pflege attraktiver gestaltet werden kann, um beruflich Pflegende zu gewinnen, im Beruf zu halten und solche, die aus der Pflege ausgeschieden sind, zurückzugewinnen." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Hier finden Sie weitere Berichte -
Literaturhinweis
Zwischen Selbst- und Fremdbestimmung: Stellensuche digital (2022)
Böhringer, Daniela;Zitatform
Böhringer, Daniela (2022): Zwischen Selbst- und Fremdbestimmung: Stellensuche digital. In: Sozialer Fortschritt, Jg. 71, H. 6-7, S. 425-446. DOI:10.3790/sfo.71.6-7.425
Abstract
"In Deutschland setzt besonders die öffentliche Arbeitsvermittlung auf hohe Automatisierung und Digitalisierung bei der Stellensuche und stellt entsprechende online-Suchmöglichkeiten für Bürger*innen zur Verfügung. Im Text wird der Frage nachgegangen, welche interaktiven Besonderheiten diese Begegnung ‚face-to-screen‘ aufweist. Damit wird die Forschung zu Street-level bureaucrats, die gegenwärtig auf die persönliche Begegnung von Angesicht zu Angesicht fokussiert, erweitert. Die Analyse beruht auf Video-Aufzeichnungen von Nutzungssituationen. Dabei wurden vor allem solche Sequenzen analysiert, in denen deutlich wird, dass Probleme und Irritationen in der Mensch-Maschine-Interaktion auftreten. Die Ergebnisse verweisen auf eine Art interaktiven Bias, auf besondere Interaktionsarbeit auf Seiten der Bürger*innen und Bürger in solchen Begegnungen ‚face-to-screen‘." (Autorenreferat, IAB-Doku)