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on Human Capital and Human Resource Management |
| By: | Breulet, Anaïs (RWTH Aachen University); Grund, Christian (RWTH Aachen University) |
| Abstract: | Performance appraisals are one of the most widely used human resource management practices. This study investigates the relationship between performance appraisals and sleep satisfaction using large-scale, representative data from the German Socio-Economic Panel (GSOEP). Sleep satisfaction is used as a comprehensive measure of perceived restfulness and sleep quality. The results show that performance appraisals are negatively associated with sleep satisfaction, even after controlling for a wide range of socio-demographic, work-related, and personality characteristics. This negative relationship is particularly pronounced when evaluations are tied to short-term financial outcomes. These findings highlight that performance evaluation processes may generate psychological pressure that undermines employee´s ability to rest and recover. |
| Keywords: | performance appraisals, sleep satisfaction, monetary incentives, German Socio-Economic Panel |
| JEL: | M5 J28 J81 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18541 |
| By: | Juan Sebastián Ivars (University of Balearic Islands) |
| Abstract: | This paper investigates how market competition shapes the design and provision of incentive contracts for managers. We study a moral hazard setting where two principals each employ a risk neutral agent (manager). Each agent makes a decision on effort leading stochastically to an outcome. These outcomes are observable for each principal and used to design incentives based on their joint realizations. We isolate the effect of market competition in two channels: market information and market structure. First, market information captures the correlation between the outcomes generated by the agents. Second, market structure indicates the profits that each principal obtains from a given realization of agents’ outcomes. As a result, the incentive schemes that are optimal from an informational perspective need not be used in equilibrium when competition reduces the returns to effort. This framework provides a unified explanation for variation in incentive design across competitive environments and clarifies how competition affects managerial discipline through the profitability of incentive provision rather than through the design of performance measures. |
| Keywords: | Moral Hazard, Principal-Agent, Competition, Managerial Incentives |
| JEL: | D21 D43 D86 M12 L13 J33 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:aoz:wpaper:392 |
| By: | Ali Hashim; Gizem Koşar; Wilbert Van der Klaauw |
| Abstract: | The rapid spread of generative AI (AI) tools is reshaping the workplace at a remarkable rate. Yet relatively little is known about whether workers have access to these tools, how the tools affect workers’ daily productivity, and how much workers value the training needed to use the tools effectively. In this post, we shed light on these issues by drawing on supplemental questions in the November 2025 Survey of Consumer Expectations (SCE), fielded to a representative sample of the U.S. population. We find that adoption of AI tools at work is heterogeneous, that a sizable share of workers see AI training as important, and that a significant share of employers are nonetheless not yet providing access to AI tools or training on how to use them. |
| Keywords: | expectations; genAI; worker training; Survey of Consumer Expectations (SCE) |
| JEL: | J2 J3 D84 |
| Date: | 2026–04–14 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:103043 |
| By: | Gabriel Burdin; Ryo Kambayashi; Takao Kato |
| Abstract: | How do limits on working hours affect firms, workers, and households? This paper answers this question by analyzing Japan's 2018Work Style Reform (WSR), which introduced the first binding cap on overtime hours. Using establishment payroll data and worker surveys in a difference-in-differences design, we show that the reform reduced monthly overtime by 5 hours (25%) and compressed the distribution of overtime within firms. Total earnings fell by 1.4% due to the effect of lower overtime pay. The reform also narrowed overtime gaps between standard and nonstandard jobs and reduced gender differences in long hours. Consistent with a reduction in the importance of extreme overtime as a screening device, women gained increased access to standard, career-track positions. We further document improvements in life and leisure satisfaction among female workers, but not among men. These gender differences are not explained by changes in perceived work intensification or time use. Instead, men partially substituted unpaid for paid overtime, consistent with the absence of well-being gains among male workers. Finally, exploiting information on spouses’ working hours, we find suggestive evidence of cross-spousal spillovers on women’s well-being, consistent with household-level complementarities. |
| Keywords: | Working Time Regulations, Overtime, Wages, Employment, Subjective Well-being, Gender, Japan, Work Style Reform Jel Classification: J16, J22, J23, J41 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:usi:wpaper:942 |
| By: | Ambar La Forgia; Manasvini Singh |
| Abstract: | We investigate how the gender mix of expert teams affects performance in a high-stakes setting: childbirth. Using data on 2.5 million births, we exploit the quasi-exogenous assignment of patients to two-member obstetrician teams (Lead–Assisting), and find that: (i) female-only teams achieve the best maternal outcomes, whereas male-only teams have the worst; and (ii) female-led mixed-gender teams perform worse than male-led ones. Specifically, severe maternal complications are 15.8% higher in male-only teams and 7.1-10.8% higher in mixed-gender teams compared to female-only teams. These patterns cannot be explained by patient risk, endogenous team formation, or physician preferences for discretionary practices like C-sections. Instead, gender mix directly affects team decisions and performance, likely through gender norms — a mechanism supported by two findings. First, gender mix affects how closely team decisions reflect member preferences, with female-only teams being especially skilled at this process, possibly due to more collaborative decision-making. Second, gender mix affects team resilience, with female-led mixed gender teams performing especially poorly under challenging conditions (e.g., limited team familiarity), possibly because female leaders invert traditional gender norms. We also document other notable patterns: female-only teams not only achieve the lowest complication rates for Black women, but are also the only team type to have no racial disparity in maternal outcomes. Overall, this study provides new insights into gender dynamics in expert teams, informing managerial efforts to support effective collaboration in increasingly diverse workplaces. |
| JEL: | D91 I1 J16 M54 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35084 |
| By: | Irlenbusch, Bernd (University of Cologne); Rau, Holger (University of Duisburg-Essen and University of Göttingen); Rilke, Rainer (Economics Group, WHU - Otto Beisheim School of Management) |
| Abstract: | We study how human versus LLM-based evaluation and gender transparency shape entry into competitive jobs. In a preregistered online experiment, participants first complete a Niederle and Vesterlund (2007) tournament task to measure competitive preferences, then prepare text-based job applications and decide whether to apply under each of four evaluation regimes—human only, LLM only, and two hybrid human-in-the-loop configurations—while gender disclosure is randomized between subjects. LLM involvement reduces application rates, with stronger effects for women than men, including under hybrid designs. Effects are driven by non-competitive candidates; non-competitive women, the group most exposed to AI-induced deterrence, receive the strongest objective evaluations under pure AI assessment across all subgroups, yet are systematically underconfident and apply least often. Competitive men persistently apply and exhibit overconfidence-driven adverse selection, whereas competitive women show resilience to AI-induced deterrence while remaining well-calibrated under AI evaluation and exhibiting positive self-selection across regimes. We find no effects of gender transparency. |
| Keywords: | AI hiring, LLMs, algorithm aversion, gender differences |
| JEL: | C92 J71 J24 O33 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18517 |
| By: | Pawel, Adrjan (Indeed Hiring Lab and Regent's Park College, University of Oxford); Jessen, Jonas (WZB and IAB); Victoria Lanzón, Carlos (Universidad Complutense de Madrid) |
| Abstract: | We examine whether restricting temporary contracts increases firms' investment in worker training, exploiting Spain's 2022 labour market reform. Using 3.1 million online job postings from 2018 to 2024, we implement a difference-in-differences design that leverages pre-reform variation in reliance on temporary contracts across occupations. More exposed occupations shifted toward permanent hiring and increased advertised training relative to less exposed occupations. Training rose by 4.3 percentage points, fully closing the pre-reform gap by 2024. These results provide evidence that longer expected employment duration increases firms' investment in training, identifying a channel through which labour market regulation can shape human capital formation. |
| Keywords: | temporary employment, on-the-job training, human capital investment, employment contracts |
| JEL: | J24 J41 J63 J68 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18539 |
| By: | Valentin Kecht (University of Bonn); Alessandro Lizzeri (Princeton University, NBER, & CEPR); Farzad Saidi (University of Bonn & CEPR) |
| Abstract: | This paper documents that the age at which CEOs are appointed has risen sharply over the past several decades. Using newly assembled data covering a wide set of firms, we show that this increase is concentrated outside the largest listed firms and driven primarily by longer and more diverse external career paths prior to CEO appointment. These patterns are difficult to reconcile with explanations based on demographics, schooling, or tenure, and are instead consistent with a matching framework in which rising demand for generalist human capital leads firms to trade off peak ability for accumulated experience. We investigate the forces behind this shift. Using variation in consulting networks, we establish that firms place greater weight on diversified managerial experience as operating environments have become increasingly uncertain and complex. We also provide evidence for a supply-side response in which prospective CEOs broaden their skill portfolio as demand for generalist skills rises. |
| Keywords: | CEOs, aging, executive labor markets, generalist skills, uncertainty |
| JEL: | D22 J21 J24 M12 M51 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:404 |
| By: | Bryson, Alex (University College London); Kauhanen, Antti (ETLA); Rouvinen, Petri (ETLA) |
| Abstract: | Utilizing nationally representative cross-sectional and longitudinal data from Finland (2018-2023), we provide a population-level assessment of the relationship between AI and worker well-being. Contrary to international evidence suggesting a positive or an inverted U-shaped relationship, we find no systematic association between AI use intensity and job satisfaction. However, we do find that work engagement is higher among employees who are personally involved with AI, with the strongest association among intensive users for whom AI is an essential part of their work. Furthermore, technology-replacement fears have remained stable despite rapid AI advancement and do not predict subsequent labour market transitions. An interpretation is that Finland's high-trust institutional environment and robust social safety nets may effectively moderate the disruptive psychological and economic shocks typically associated with rapid technological change. |
| Keywords: | artificial intelligence, job satisfaction, work engagement, technology-related fears, labour market transitions |
| JEL: | J28 L23 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18540 |
| By: | Golo Henseke |
| Abstract: | Generative AI diffuses at pace across European workplaces, but unevenly. Using the 2024 European Working Conditions Survey of more than 36, 600 workers across 35 countries, we examine who adopts generative AI and whether early adoption has begun to reshape the task content of jobs. Adoption averages 12\% but ranges from under 3% to 25% across countries. Although occupational exposure strongly predicts uptake, AI does not diffuse passively along exposure lines. At the worker level, individual skills, non-routine cognitive job content within occupations, and employee say in organisational decisions steepen the exposure-adoption gradient; at the country level, so do digitalisation and workplace training provision. A gender gap persists, concentrated in the most exposed occupations. A shift-share design finds no detectable effect of early adoption on worker-reported technology-related task restructuring, consistent with a transitional phase in which AI is fitted into changing work processes rather than actively reshaping them. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.18849 |
| By: | Bick, Alexander (St. Louis Fed & CEPR); Blandin, Adam (Vanderbilt University); Deming, David (Harvard University); Fuchs-Schündeln, Nicola (WZB & Goethe University & CEPR); Jessen, Jonas (WZB & IAB) |
| Abstract: | This paper combines international evidence from worker and firm surveys conducted in 2025 and 2026 to document large gaps in AI adoption, both between the US and Europe and across European countries. Cross-country differences in worker demographics and firm composition account for an important share of these gaps. AI adoption, within and across countries, is also closely linked to firm personnel management practices and whether firms actively encourage AI use by workers. Micro-level evidence suggests that AI generates meaningful time savings for many workers. At the macro level, in recent years industries with higher AI adoption rates have experienced faster productivity growth. While we do not establish causality, this relationship is statistically significant and similar in magnitude in Europe and the US. We do not find clear evidence that industry-level AI adoption is associated with employment changes. We discuss limitations of existing data and outline priorities for future data collection to better assess the productivity and labor market effects of AI. |
| Keywords: | generative AI, technology adoption, labor productivity |
| JEL: | J24 M16 O14 O33 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18521 |