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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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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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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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Osterman, Paul (2024): Reconsidering Occupational Internal Labor Markets: Incidence and Consequences. In: ILR review, Jg. 77, H. 3, S. 366-395. DOI:10.1177/00197939241242089

Abstract

"What are useful ways to characterize varying employment systems? This article returns to an older idea, Internal Labor Markets (ILMs). The traditional assumption characterized ILMs as the core of the labor market but current thinking argues that ILMs have frayed. Little direct measurement has been carried out, however, and both viewpoints have relied on proxies or case studies. The author utilizes a new survey of employed US workers to provide an estimate of the incidence of ILMs and finds that between 25 and 40% percent of adult workers are in ILMs. The article then elaborates theory regarding the practices of ILMs, a theory grounded in the idea of complementary bundles of human resource practices, and asks what are the correlates of being in an ILM. Findings show that although wages in ILMs are no higher than non-ILM wages, ILMs are positively associated with other aspects of job quality and attitudes across the board." (Author's abstract, IAB-Doku) ((en))

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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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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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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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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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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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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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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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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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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)

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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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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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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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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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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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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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(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)

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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)

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Carbonero, Francesco & Hermann Gartner (2022): A note on the relation of search costs and search duration for new hires. In: Macroeconomic Dynamics, Jg. 26, H. 1, S. 263-276., 2020-02-11. DOI:10.1017/S136510052000005X

Abstract

"Fixed search costs, that is, costs that do not vary with search duration, can amplify the cyclical volatility of the labor market. To assess the size of fixed costs, we analyze the relation between search costs and search duration using German establishment data. An instrumental variable estimation shows no relation between search duration and search costs. We conclude that search costs are mainly fixed costs. Furthermore, we show that a search and matching model, calibrated for Germany with fixed costs close to 75%, can generate labor market volatility that is consistent with the data." (Author's abstract, IAB-Doku) ((en))

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Fleck, Lara, Nicholas Rounding & Pelin Özgül (2022): Künstliche Intelligenz in der Personalauswahl. (ROA external reports / Researchcentrum voor Onderwijs en Arbeidsmarkt (Maastricht) ai:conomics Kurzdossier Mai 2022), Maastricht, 10 S.

Abstract

"Die Künstliche Intelligenz (KI) als starke Prognosetechniologie kann von Firmen eingesetzt werden, um ihre Effizienz innerhalb verschiedener Prozesse zu erhöhen, von denen einer die Einstellungspraxis im Personalmanagement ist Bogen & Rieke, 2018; Gonzalez et al., 2019; Tambe et al., 2019). Da es eine Vielzahl unterschiedlicher Meinungen und Bedenken bezüglich der Implementierung der KI bei Einstellungen gibt, möchten wir uns auf eine spezifische Debatte fokussieren: ob sie das Potenzial hat, Diskriminierung zu verstärken oder zu reduzieren. Die Diskriminierung bei Einstellungen ist ein schon seit Langem untersuchtes Phänomen, das häufig auf unbewusster, interpersoneller Voreingenommenheit der Anwerber:innen und subjektiven Beurteilungen von Menschen aufgrund unterschiedlicher persönlicher Merkmale basiert." (Autorenreferat, IAB-Doku)

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Folger, Nicholas, Prisca Brosi, Jutta Stumpf-Wollersheim & Isabell M. Welpe (2022): Applicant Reactions to Digital Selection Methods. A Signaling Perspective on Innovativeness and Procedural Justice. In: Journal of Business and Psychology, Jg. 37, H. 4, S. 735-757. DOI:10.1007/s10869-021-09770-3

Abstract

"Research has shown that the use of digital technologies in the personnel selection process can have both positive and negative effects on applicants’ attraction to an organization. We explain this contradiction by specifying its underlying mechanisms. Drawing on signaling theory, we build a conceptual model that applies two different theoretical lenses (instrumental-symbolic framework and justice theory) to suggest that perceptions of innovativeness and procedural justice explain the relationship between an organization’s use of digital selection methods and employer attractiveness perceptions. We test our model by utilizing two studies, namely one experimental vignette study among potential applicants (N = 475) and one retrospective field study among actual job applicants (N = 335). With the exception of the assessment stage in Study 1, the positive indirect effects found in both studies indicated that applicants perceive digital selection methods to be more innovative. While Study 1 also revealed a negative indirect effect, with potential applicants further perceiving digital selection methods as less fair than less digitalized methods in the interview stage, this effect was not significant for actual job applicants in Study 2. We discuss theoretical implications for the applicant reactions literature and offer recommendations for human resource managers to make use of positive signaling effects while reducing potential negative signaling effects linked to the use of digital selection methods." (Author's abstract, IAB-Doku) ((en))

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Freuding, Julia & Johanna Garnitz (2022): Klassisches Recruiting vs. Active Sourcing. Externe Stellenausschreibung weiterhin dominierend. In: Ifo-Schnelldienst, Jg. 75, H. 4, S. 70-73.

Abstract

"Das ifo Institut befragt im Auftrag von Randstad Deutschland quartalsweise über 1 000 deutsche Personalleiter*innen. Im ersten Quartal 2022 wurde unter anderem gefragt, inwieweit der Recruiting-Prozess der Unternehmen durch die Corona-Pandemie und die damit einhergehende Digitalisierung beeinflusst wurde. Grundsätzlich zeigte sich, dass klassisches Recruiting auch weiterhin dominiert. Die aktive Suche von potenziellen neuen Mitarbeiter*innen durch das Unternehmen selbst wird hingegen noch zögerlich betrieben." (Autorenreferat, IAB-Doku)

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Gleiser, Patrick, Sophie Hensgen, Christian Kagerl, Ute Leber, Duncan Roth, Jens Stegmaier & Matthias Umkehrer (2022): Während der Pandemie ist die Suche nach geeignetem Personal für viele Betriebe schwieriger geworden. In: IAB-Forum H. 05.08.2022 Nürnberg, 2022-08-03. DOI:10.48720/IAB.FOO.20220805.01

Abstract

"Für gut vier von zehn Betrieben haben sich die Probleme bei der Besetzung offener Stellen im Jahr 2021 gegenüber 2019 nach eigenen Angaben verschärft. Die Betriebe machen hierfür überwiegend den Rückgang an (geeigneten) Bewerbungen, teils auch pandemiebedingte Einschränkungen im Rekrutierungsprozess verantwortlich. Manche Betriebe mussten daher Überstunden anordnen oder Aufträge reduzieren. Viele Betriebe mussten außerdem häufig Kompromisse eingehen, um Stellen besetzen zu können." (Autorenreferat, IAB-Doku)

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Gutfleisch, Tamara & Robin Samuel (2022): Hiring in border regions: experimental and qualitative evidence from a recruiter survey in Luxembourg. In: Journal for labour market research, Jg. 56. DOI:10.1186/s12651-022-00327-2

Abstract

"Firms in border regions typically deal with heterogeneous applicant pools that include both (foreign) domestic workers and cross-border commuters. However, we know little about recruiters’ workforce needs and hiring practices in cross-border labour markets. Based on a survey of real recruiters in Luxembourg, this study presents experimental and qualitative findings on the role of country of residence in recruiters’ hiring intentions against foreigners. Luxembourg presents a rarely studied but highly relevant case for hiring practices owing to a combination of a strong economy, strict labour market regulations, and a transnational workforce. Drawing on data from a factorial survey experiment, we found no discrimination against Portuguese and French applicants living in Luxembourg. Yet, (highly skilled) cross-border workers from France and Germany faced disadvantages regarding recruiters’ hiring intentions. However, differences in effect sizes between foreigners and cross-border workers were small and not statistically significant. When further asked about the potential challenges of recruiting in Luxembourg’s cross-border labour market, respondents expressed concerns about flexibility, poor social fit, and cultural differences in hiring foreign and cross-border employees. Overall, our study provides further points of reference for studies on hiring intentions in cross-border labour markets across Europe." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))

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Obukhova, Elena & Brian Rubineau (2022): Market Transition and Network-Based Job Matching in China: The Referrer Perspective. In: ILR review, Jg. 75, H. 1, S. 200-224. DOI:10.1177/0019793920937234

Abstract

"To better understand how network-based job matching responds to market development, the authors investigate network matching in China. They examine this question from the perspective of referrers, those who share information about job opportunities with potential job candidates. Using unique data from a population survey and leveraging interprovincial differences in market development, the authors show that market development has a negative association with individuals’ propensity to share job information. People who work at firms that offer a referral bonus and people who work at private firms, however, are more likely to share information and share it with more people, and the number of such employers increases with market transition. This increase can produce a positive association between market development and overall prevalence of job information-sharing. Results clarify the role employer-side processes play in job information-sharing and carry important implications for understanding network matching." (Author's abstract, IAB-Doku) ((en))

Abstract

"Der Personalmarkt und das Recruiting befinden sich im Wandel. Fachkräfte werden branchenübergreifend händeringend gesucht – der Arbeitgebermarkt wandelt sich zum Arbeitnehmermarkt. Unternehmen müssen sich verstärkt bei den Fachkräften bewerben und nicht mehr umgekehrt. Dies führt zu besonderen Herausforderungen für die Recruiter sowohl in den Unternehmen als auch in der Personalvermittlungsbranche. Die Ergebnisse dieser Studie zeigen: Künstliche Intelligenz (KI) kann unterstützend dafür eingesetzt werden, effizienter den perfekt passenden Kandidaten zu finden. Viele Personalvermittler haben auf diesem Gebiet schon einige Erfahrungen sammeln können. Bereits über die Hälfte der befragten Personalvermittlungsunternehmen setzen KI-Tools im Recruiting-Prozess ein. Bei größeren Vermittlungsunternehmen mit über 50 Mitarbeitern liegt der Anteil bereits bei über 60 Prozent. Insgesamt geben über die Hälfte der Vermittler an, dass KI im Recruiting in den nächsten fünf Jahren eine entscheidende Rolle spielen wird." (Textauszug, IAB-Doku)

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Bertheau, Antoine (2021): Employer Search Behavior: Reasons for Internal Hiring. In: Labour Economics, Jg. 73. DOI:10.1016/j.labeco.2021.102064

Abstract

"This article studies reasons for internal hiring, i.e., re-assigning or promoting an employee instead of recruiting an external candidate. We exploit a representative survey of establishments covering all European Union countries to measure employers' search for internal candidates. Internal search is a widespread practice: 66% of establishments typically search internally. The accumulation of specific skills and the provision of incentives for employees are the main advantages of hiring internally in the theoretical literature. Ordered probit estimates show that on-the-job training and internal search are positively associated. On the contrary, incentive schemes such as variable pay are not associated with employer search. These results help to assess competing theories, and in particular, suggest that specific human capital is an important driver of internal hiring. Finally, we uncover two interesting facts that need further research: internal hiring is less likely in service firms and in non-competitive product markets." (Author's abstract, IAB-Doku, © 2022 Elsevier) ((en))

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Desiere, Sam & Ludo Struyven (2021): Using Artificial Intelligence to classify Jobseekers: The Accuracy-Equity Trade-off. In: Journal of Social Policy, Jg. 50, H. 2, S. 367-385. DOI:10.1017/S0047279420000203

Abstract

"Artificial intelligence (AI) is increasingly popular in the public sector to improve the cost-efficiency of service delivery. One example is AI-based profiling models in public employment services (PES), which predict a jobseeker's probability of finding work and are used to segment jobseekers in groups. Profiling models hold the potential to improve identification of jobseekers at-risk of becoming long-term unemployed, but also induce discrimination. Using a recently developed AI-based profiling model of the Flemish PES, we assess to what extent AI-based profiling 'discriminates' against jobseekers of foreign origin compared to traditional rule-based profiling approaches. At a maximum level of accuracy, jobseekers of foreign origin who ultimately find a job are 2.6 times more likely to be misclassified as 'high-risk' jobseekers. We argue that it is critical that policymakers and caseworkers understand the inherent trade-offs of profiling models, and consider the limitations when integrating these models in daily operations. We develop a graphical tool to visualize the accuracy-equity trade-off in order to facilitate policy discussions." (Author's abstract, IAB-Doku) ((en))

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Engbom, Niklas (2021): Contagious Unemployment. (NBER working paper 28829), Cambridge, MA, 46, 24 S.

Abstract

"Recent micro evidence of how workers search for jobs is shown to have critical implications for the macroeconomic propagation of labor market shocks. Unemployed workers send over 10 times as many job applications in a month as their employed peers, but are less than half as likely per application to make a move. I interpret these patterns as the unemployed applying for more jobs that they are less likely to be a good fit for. During periods of high unemployment, it consequently becomes harder for firms to assert who is a good fit for the job. By raising the cost of recruiting, a short-lived adverse shock has a persistent negative impact on the job finding rate. I provide evidence that firms spend more time on recruiting when unemployment is high, quantitatively consistent with the theory." (Author's abstract, IAB-Doku) ((en))

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Galanakis, Yannis (2021): "Are you in the right job?" Human Capital Mismatch in the UK. (GLO discussion paper / Global Labor Organization 976), Essen, 58 S.

Abstract

"This paper examines a problem of worker misallocation into jobs. A theoretical model, allowing for heterogeneous workers and firms, shows that job search frictions generate mismatch between employees and employers. In the empirical analysis, the British Household Panel Survey (BHPS), the UK household Longitudinal Study (UKHLS) and British Cohort Study 1970 (BCS70) data are used to measure the incidence of mismatch, how it changes over time and whether it can be explained by unobserved ability. Results show that (i) the incidence of mismatch increases after the Great Recession. (ii) Individual transitions to/from matching take place due to workers' occupational mobility and over-time skills development. (iii) Employees can find better jobs or their mobility occurs earlier than the aggregate change of skills. (iv) Controlling for individual heterogeneity, measured by cognitive and non-cognitive skill test scores throughout childhood, does not decrease the incidence of mismatch. This suggests that unobserved productivity does not generate mismatch in the labour market." (Author's abstract, IAB-Doku) ((en))

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Gürtzgen, Nicole, Benjamin Lochner, Laura Pohlan & Gerard J. van den Berg (2021): Does Online Search Improve the Match Quality of New Hires? In: Labour Economics, Jg. 70, S. 101981., 2021-03-16. DOI:10.1016/j.labeco.2021.101981

Abstract

"Die Studie untersucht den Effekt der Expansion des Breitbandinternets auf die Matchqualität neu eingestellter Personen. Hierzu werden Daten zur regionalen Internetverfügbarkeit mit administrativen Individualdaten und Vakanzdaten für den deutschen Arbeitsmarkt kombiniert. Die Ergebnisse zeigen, dass eine Ausweitung der Breitbandinternet-Verfügbarkeit keinen größeren Einfluss auf die Stabilität und Entlohnung neu begonnener Beschäftigungsverhältnisse hat. Diese Resultate werden auf Basis von Analysen mit Vakanzdaten bestätigt. Diese Daten erlauben einen expliziten Vergleich der Matchqualität von Personen, die online rekrutiert wurden, mit der Matchqualität von Personen, die über andere Rekrutierungskanäle eingestellt wurden. Weiterhin zeigen die Ergebnisse, dass Online-Rekrutierung nicht nur die Anzahl der Bewerbungen und den Anteil ungeeigneter Bewerbungen erhöht, sondern ebenfalls zu einer höheren Anzahl von Vakanzen führt." (Autorenreferat, IAB-Doku)

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Gürtzgen, Nicole, Benjamin Lochner, Laura Pohlan & Gerard J. van den Berg (2021): Does Online Search Improve the Match Quality of New Hires? (IZA discussion paper 14031), Bonn, 68 S.

Abstract

"This paper studies the effects of the high-speed internet expansion on the match quality of new hires. We combine data on internet availability at the local level with German individual register and vacancy data. Results show that internet availability has no major impact on the stability of new matches and their wages. We confirm these findings using vacancy data, by explicitly comparing match outcomes of online and non-online recruits. Further results show that online recruiting not only raises the number of applicants and the share of unsuitable candidates per vacancy, but also induces employers to post more vacancies." (Author's abstract, IAB-Doku) ((en))

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Gürtzgen, Nicole, Benjamin Lochner, Laura Pohlan & Gerard J. van den Berg (2021): Does Online Search Improve the Match Quality of New Hires? (IAB-Discussion Paper 02/2021), Nürnberg, 66 S.

Abstract

"Die Studie untersucht den Effekt der Expansion des Breitbandinternets auf die Matchqualität neu eingestellter Personen. Hierzu werden Daten zur regionalen Internetverfügbarkeit mit administrativen Individualdaten und Vakanzdaten für den deutschen Arbeitsmarkt kombiniert. Die Ergebnisse zeigen, dass eine Ausweitung der Breitbandinternet-Verfügbarkeit keinen größeren Einfluss auf die Stabilität und Entlohnung neu begonnener Beschäftigungsverhältnisse hat. Diese Resultate werden auf Basis von Analysen mit Vakanzdaten bestätigt. Diese Daten erlauben einen expliziten Vergleich der Matchqualität von Personen, die online rekrutiert wurden, mit der Matchqualität von Personen, die über andere Rekrutierungskanäle eingestellt wurden. Weiterhin zeigen die Ergebnisse, dass Online-Rekrutierung nicht nur die Anzahl der Bewerbungen und den Anteil ungeeigneter Bewerbungen erhöht, sondern ebenfalls zu einer höheren Anzahl von Vakanzen führt." (Autorenreferat, IAB-Doku)

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Gürtzgen, Nicole, Benjamin Lochner, Laura Pohlan & Gerard J. van den Berg (2021): Does Online Search Improve the Match Quality of New Hires? (ZEW discussion paper 21-002), Mannheim, 68 S.

Abstract

"This paper studies the effects of the high-speed internet expansion on the match quality of new hires. They combine data on internet availability at the local level with German individual register and vacancy data. Results show that internet availability has no major impact on the stability of new matches and their wages. The authors confirm these findings using vacancy data, by explicitly comparing match outcomes of online and non-online recruits. Further results show that online recruiting not only raises the number of applicants and the share of unsuitable candidates per vacancy, but also induces employers to post more vacancies." (Autorenreferat, IAB-Doku)

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Hartl, Tobias, Christian Hutter & Enzo Weber (2021): Matching for three: big data evidence on search activity of workers, firms, and employment service. (IAB-Discussion Paper 01/2021), Nürnberg, 14 S.

Abstract

"Wir generieren Maße für die Suchintensität von Arbeitgebern und Arbeitssuchenden und zum ersten Mal - für die Vermittlungsintensität von Arbeitsagenturen. Zu diesem Zweck greifen wir auf Big Data zu Online-Aktivitäten aus der Online Jobbörse der Bundesagentur für Arbeit und ihrer internen Vermittlungssoftware zurück. Wir verwenden diese Daten, um eine erweiterte Matchingfunktion zu schätzen, bei der der Effizienzparameter mit den Such- und Vermittlungsintensitäten variiert. Die Ergebnisse zeigen, dass alle drei Intensitätsmaße erheblich zur Erklärung der Job-findings-Variation beitragen." (Autorenreferat, IAB-Doku)

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Hirzer, Petra (2021): Digitaler Wandel in der Personalgewinnung. Perspektiven und Herausforderungen für eine diversitätsorientierte Personalpolitik. In: SWS-Rundschau, Jg. 61, H. 4, S. 412-430.

Abstract

"Ein Blick auf die von modernen Technologien und algorithmischen Systemen durchdrungene Arbeitswelt zeigt, dass in den letzten Jahren neue Schnittstellen zwischen menschlichen und maschinellen Aufgaben und Entscheidungen entstanden sind. Dieser Artikel diskutiert die Auswirkungen dieser Veränderungen im Bereich der digitalen Personalgewinnung vor dem Hintergrund einer diversitätsorientierten und diskriminierungsfreien Personalpolitik. Die Grundlage bildet eine qualitativ-explorative Untersuchung zur digitalen Transformation in der gegenwärtigen Recruiting-Praxis in Österreich. Der Beitrag gibt einen Überblick zu Perspektiven und potenziellen Herausforderungen im Zusammenhang mit digitalen Praktiken aus Sicht von Expert*innen aus dem Bereich der Personalgewinnung." (Autorenreferat, IAB-Doku)

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Hutter, Christian (2021): Cyclicality of labour market search: a new big data Approach. In: Journal for labour market research, Jg. 55, 2020-12-11. DOI:10.1186/s12651-020-00283-9

Abstract

"This paper exploits big data on online activity from the job exchange of the German Federal Employment Agency and its internal placement-software to generate measures for search activity of employers and job seekers and - as a novel feature - for placement activity of employment agencies. In addition, the average search perimeter in the job seekers’ search profiles can be measured. The data are used to estimate the behaviour of the search and placement activities during the business and labour market cycle and their seasonal patterns. The results show that the search activities of firms and employment agencies are procyclical. By contrast, job seekers’ search intensity shows a countercyclical pattern, at least before the COVID-19 crisis." (Author's abstract, © 2021 Springer) ((en))

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Kraft, Kornelius & Alexander Lammers (2021): The Effects of Reforming a Federal Employment Agency on Labor Demand. (IZA discussion paper 14629), Bonn, 48 S.

Abstract

"In this paper we report the results of an empirical study on the employment growth effects of a policy intervention, explicitly aimed at increasing placement efficiency of the Federal Employment Agency in Germany. We use the Hartz III reform in the year 2004 as an exogenous intervention that improves the matching process and compare establishments that use the services of the Federal Employment Agency with establishments that do not use the placement services. Using detailed German establishment level data, our difference-in-differences estimates reveal an increase in employment growth among those firms that use the agency for their recruitment activities compared to non-user firms. After the Hartz III reform was in place, establishments using the agency grew roughly two percentage points faster in terms of employment relative to non-users and those establishments achieve an increase in the proportion of hires. We provide several robustness tests using, for example, inverse-probability weighting to additionally account for differences in observable characteristics. Our paper highlights the importance of the placement service on the labor demand side, in particular on the so far overlooked establishment level." (Author's abstract, IAB-Doku) ((en))

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Kuhn, Moritz, Iourii Manovskii & Xincheng Qiu (2021): The Geography of Job Creation and Job Destruction. (ECONtribute discussion paper 122), Köln ; Bonn, 45, A-20 S.

Abstract

"Spatial differences in labor market performance are large and highly persistent. Using data from the United States, Germany, and the United Kingdom, we document striking similarities in spatial differences in unemployment, vacancies, job finding, and job filling within each country. This robust set of facts guides and disciplines the development of a theory of local labor market performance. We find that a spatial version of a Diamond-Mortensen-Pissarides model with endogenous separations and on-the-job search quantitatively accounts for all the documented empirical regularities. The model also quantitatively rationalizes why differences in job-separation rates have primary importance in inducing differences in unemployment across space while changes in the job-finding rate are the main driver in unemployment fluctuations over the business cycle." (Author's abstract, IAB-Doku) ((en))

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Laschever, Ron A. & Russell Weinstein (2021): Preference Signaling and Worker-Firm Matching: Evidence from Interview Auctions. (IZA discussion paper 14622), Bonn, 56 S.

Abstract

"We study whether there are improvements in worker-firm matching when employers and applicants can credibly signal their interest in a match. Using a detailed résumé dataset of more than 400 applicants from one university over five years, we analyze a matching process in which firms fill some of their inter- view slots by invitation and the remainder are filled by an auction. Consistent with the predictions of a signaling model, we find the auction is valuable for less desirable firms trying to hire high desirability applicants. Second, we find evidence that is consistent with the auction benefiting overlooked applicants. Candidates who are less likely to be invited for an interview (e.g., non-U.S. citizens) are hired after having the opportunity to interview through the auction. Among hires, these candidates are more represented among auction winners than invited interviewees, and this difference is more pronounced at more desirable firms. Finally, counterfactual analysis shows the auction increases the number and quality of hires for less desirable firms, and total hires in the market." (Author's abstract, IAB-Doku) ((en))

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Mannott, Julian & Harm Alhusen (2021): Digitale Fachkräftegewinnung im Handwerk durch Einsatz sozialer Medien. (Göttinger Beiträge zur Handwerksforschung 59), Göttingen, 27 S. DOI:10.3249/2364-3897-gbh-59

Abstract

"Unbesetzte Stellen sind eine aktuell zentrale Herausforderung für Handwerksbetriebe. Eine Ursache ist der Fachkräftemangel, welcher wiederum im demografischen Wandel begründet ist. Ein weiterer Einflussfaktor kann darüber hinaus in einer unzureichenden Wirkungsweise der von Handwerksunternehmen verwendeten Medien zur Personalbeschaffung begründet sein. Diese Studie beschreibt einen geeigneten Prozess, der es Handwerksunternehmen ermöglicht, ausreichend Bewerber zu generieren, um ihre offenen Stellen zu besetzen. Um einen geeigneten Prozess zu entwerfen wurden leitfadengestützte Interviews mit drei Handwerksunternehmen geführt. Auf dieser Basis wurde zunächst der Prozess der Bewerberbeschaffung modelliert, der IST-Zustand erhoben sowie im nächsten Schritt ein digitaler Prozess implementiert und dessen Wirksamkeit geprüft. Dabei zeigte sich: Die betrachteten Handwerksbetriebe (8, 15 und 16 Mitarbeiter) generierten durch einen weitgehend analogen Werbeprozess zwischen 0 und 4 Bewerber bei Kosten von rd. 1.000 € bis 3.000 €. Die Besetzung neuer Stellen auf diesem Wege dauerte 6 bis 24 Monate. Nach der Implementierung des neuen, digitalen Bewerberbeschaffungsprozesses wurden die Kosten auf rd. 285 € bis 500 € gesenkt. Bei den Betrieben konnten jeweils zwischen 9 und 34 Bewerber akquiriert werden. Die Bewerbungen führten bei den Handwerksbetrieben zu 2-3 Einstellungen bei einer Prozessdauer von 2 bis 4 Wochen. Entlang der definierten Kenngrößen Bewerberzahl, Kosten und Dauer stellt sich bei den drei analysierten Handwerksbetrieben der digitale Bewerberbeschaffungsprozess gegenüber analogen Werbemaßnahmen als überlegen dar. Es zeigt sich folglich, dass soziale Medien eine prozessverbessernde Alternative zu den herkömmlichen Medien der Bewerberbeschaffung darstellen können. Dabei ist der Erfolg der sozialen Medien als Bewerberbeschaffungsmaßnahme ein Ergebnis aus dem erfolgreichen Zusammenspiel der einzelnen Faktoren der Prozessmodellierung, bei denen insbesondere die Stellenanzeige, das Zielgruppenverständnis und die Kommunikation mittels Chatbot entscheidend sind." (Autorenreferat, IAB-Doku)

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Thielsch, Meinald T., Dilara Erdal & Viola Merhof (2021): Recruiting aus Sicht der Bewerber_innen. In: Psychologie und Praxis, Zeitschrift für Arbeits- und Organisationspsychologie, Jg. 65, H. 3, S. 123-137. DOI:10.1026/0932-4089/a000357

Abstract

"Hochwertiges Personalmarketing ist der essenzielle erste Schritt im Recruiting. Qualifizierte Bewerber_innen müssen auf offene Positionen erfolgreich aufmerksam gemacht werden, wofür Unternehmen und Organisationen verschiedene Online- und Offline-Maßnahmen zur Verfügung stehen. Zentral ist dabei die Wahrnehmung des Personalmarketings durch die Bewerbenden, deren Sicht bislang allerdings wenig betrachtet wurde. In der vorliegenden Studie wird daher mithilfe einer für die deutsche Arbeitsbevölkerung repräsentativen Stichprobe (N = 1.070) die Nutzung und Bewertung von klassischen und neuartigen digitalen Personalmarketingmaßnahmen in sozialen Medien untersucht und zusätzlich digitale Ansprachemethoden experimentell überprüft. Bekannte und etablierte Online- und Offline-Personalmarketingmaßnahmen weisen hohe Nutzungszahlen auf und sind zugleich am beliebtesten. Soziale Medien werden hingegen von den Bewerber_innen vergleichsweise wenig präferiert. Kongruent dazu wird im experimentellen Setup die klassische Benachrichtigung per Post neuartigen digitalen Kommunikationswegen (WhatsApp, Facebook, Alexa Voice System) vorgezogen. Die Ergebnisse dieser Studie können in der Praxis zur gezielten Ansprache potenzieller Bewerber_innen und für den optimalen Einsatz verschiedener Methoden genutzt werden." (Autorenreferat, IAB-Doku, © 2021 Hogrefe Verlag)

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Carranza, Eliana, Robert Garlick, Kate Orkin & Neil Rankin (2020): Job Search and Hiring with Two-sided Limited Information about Workseekers' Skills. (Upjohn Institute working paper 328), Kalamazoo, Mich., 70 S. DOI:10.17848/wp20-328

Abstract

"We present field experimental evidence that limited information about workseekers’ skills distorts both firm and workseeker behavior. Assessing workseekers’ skills, giving workseekers their assessment results, and helping them to credibly share the results with firms increases workseekers’ employment and earnings. It also aligns their beliefs and search strategies more closely with their skills. Giving assessment results only to workseekers has similar effects on beliefs and search, but smaller effects on employment and earnings. Giving assessment results only to firms increases callbacks. These patterns are consistent with two-sided information frictions, a new finding that can inform design of information-provision mechanisms." (Author's abstract, IAB-Doku) ((en))

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Carrillo-Tudela, Carlos, Hermann Gartner & Leo Kaas (2020): Recruitment Policies, Job-Filling Rates and Matching Efficiency. (IAB-Discussion Paper 15/2020), Nürnberg, 51 S.

Abstract

"Für das Matching am Arbeitsmarkt spielt das Rekrutierungsverhalten der Betriebe eine zentrale Rolle. Um zu untersuchen, wie das Rekrutierungsverhalten mit der Zahl der Einstellungen zusammenhängt, verknüpfen wir die IAB-Stellenerhebung mit administrativen Daten. Es zeigt sich: Mehr Einstellungen sind mit mehr Suchaufwand verbunden, mit großzügigeren Löhnen und mit geringeren Anforderungen an die Arbeitsuchenden. Um zu analysieren, welcher Mechanismus diesem Muster zugrunde liegt, entwickeln wir ein Modell mit zielgerichteter Suche. Betriebe können dabei bei Produktivitätsschocks ihr Rekrutierungsverhalten über mehrere Stellschrauben anpassen. Im kalibrierten Modell erweist sich das Anforderungsnieveau als wichtigste Stellschraube für die Auswirkung auf die Matching-Effizienz und für die Wirksamkeit von Arbeitsmarktpolitik. Suchaufwand und die Lohnpolitik spielen demgegenüber eine kleinere Rolle." (Autorenreferat, IAB-Doku)

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Faberman, R. Jason (2020): Recruiting intensity. Recruiting intensity is critical for understanding fluctuations in the labor market. (IZA world of labor 21), Bonn, 10 S. DOI:10.15185/izawol.21.v2

Abstract

"Politikansätze zur Schaffung von Arbeitsplätzen, die sich nur darauf konzentrieren, wie oft Arbeitgeber einstellen, und dabei die Anpassungsprozesse der Unternehmen bei der Personalgewinnung ignorieren, drohen ihre Ziele zu verfehlen. Die Rekrutierungsintensität in den USA während und nach der Großen Rezession unterstreicht dies: Nach der Großen Rezession blieb die Rekrutierungsintensität trotz des Anstiegs der Zahloffener Stellen auf ein historisch hohes Niveau anhaltend niedrig. Dass sich Lohnwachstum und Einstellungsrate langsamer erholten, ist zum Teil auf diese geringe Rekrutierungsintensität zurückzuführen." (Autorenreferat, IAB-Doku)

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Gürtzgen, Nicole & Andreas Moczall (2020): Sequential versus non-sequential search among German employers. Evidence from a job vacancy survey. In: Applied Economics Letters, Jg. 27, H. 11, S. 873-879., 2019-07-15. DOI:10.1080/13504851.2019.1646855

Abstract

"In this note, we provide evidence on the extent and determinants of sequential versus non-sequential search among German employers. Using unique representative data on employers' recruitment behaviour, we exploit direct information on whether employers first formed a pool of applicants from which they chose the most suitable candidate (Non-Sequential Search), or whether they hired the first suitable applicant (Sequential Search). We show that non-sequential search is the predominant search strategy, accounting for about 75 per cent of all successful hirings. Hirings by larger employers and those for high-skilled positions are disproportionately represented among the non-sequential search processes. We then proceed to decompose recruitment durations for non-sequential search into an application and a selection period and, for sequential search, into an information and combined application/selection period. With non-sequential search, the application period lasts, on average, about 18 days, whereas the selection period is 45 days long. Sequential search processes start with a very short period of about one day until the very first application arrives, followed by a rather long combined application/selection period of 57 days until a suitable applicant is found." (Author's abstract, IAB-Doku) ((en))

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Köchling, Alina & Marius Claus Wehner (2020): Discriminated by an algorithm. A systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. In: Schmalenbachs Zeitschrift für betriebswirtschaftliche Forschung, Jg. 13, H. 3, S. 795-848. DOI:10.1007/s40685-020-00134-w

Abstract

"Algorithmic decision-making is becoming increasingly common as a new source of advice in HR recruitment and HR development. While firms implement algorithmic decision-making to save costs as well as increase efficiency and objectivity, algorithmic decision-making might also lead to the unfair treatment of certain groups of people, implicit discrimination, and perceived unfairness. Current knowledge about the threats of unfairness and (implicit) discrimination by algorithmic decision-making is mostly unexplored in the human resource management context. Our goal is to clarify the current state of research related to HR recruitment and HR development, identify research gaps, and provide crucial future research directions. Based on a systematic review of 36 journal articles from 2014 to 2020, we present some applications of algorithmic decision-making and evaluate the possible pitfalls in these two essential HR functions. In doing this, we inform researchers and practitioners, offer important theoretical and practical implications, and suggest fruitful avenues for future research." (Author's abstract, IAB-Doku) ((en))