Labor Demand Research Articles

Unemployment as a Consequence of the Liquidation of State Agricultural Farms in 1991-2003

State Agricultural Farms (SAF) were liquidated on the basis of an act adopted in 1991. During the work on the act, the focus was exclusively on issues related to ownership and economic transformations, while the social consequences were not taken into account. SAF employees, especially agricultural workers, constituted a specific, historically shaped socio-professional group characterized by relatively low education and narrow professional qualifications. The aim of article is to identify the genesis of social problems in post-statehood areas, especially unemployment and its regional variation. The source base of the study is mainly the Reports of the Agricultural Property Agency of the State Treasury and sociological research reports carried out in post-statehood areas. The main finding of the research is that policy decisions to abolish state farms were made without taking into account their specific characteristics and territorial distribution. Their mentality was shaped by the nature of work and everyday life, which was entirely connected with the workplace. The workplace organized most of the living and social matters for employees and their families. After the liquidation of the State Agricultural Farms, employees were unable to find their place on the –labour market. Large-area farms established on the basis of the former SAFs radically limited employment, and the lack of appropriate skills and limited demand for labour outside agriculture worsened the situation of blue collar workers in particular. Regional differences were of particular importance for the scale of unemployment – where SAFs dominated, the unemployment problem persists even three decades after their liquidation, although it no longer concerns only former SAF employees, but all residents of former SAF areas.

Analysis of the Impact of the Digital Economy on Employment in China

As Chinas economy gradually transitions towards high-quality development, the growth of the digital economy has created numerous new employment opportunities. To verify the specific impact of the digital economy on labor demand, this paper examines both employment quantity and employment structure. Using relevant data variables from 30 provinces and cities in China from 2012 to 2022, this study applies the entropy method to develop a comprehensive index for the digital economy. This index is then used in regression analyses with total employment and high- and low-technology intensity employment. The findings suggest that overall, the development of the digital economy positively contributes to the growth in labor demand, manifested in the promotion of high-tech employment and the suppression of low-tech employment.

Can wage changes solve the labour crisis in the National Health Service?

This study aimed to examine the healthcare labour demand and supply elasticity regarding wage in the National Health Service (NHS) in England amid a labour crisis. A simultaneous error-correction regression analysis was conducted using secondary data from the NHS and Office for National Statistics from 2009 Q3 to 2022 Q1. Findings indicate both labour demand and supply of HCHS doctors in the NHS are highly inelastic with respect to real wages, with only a 0.1% decrease in NHS staff hiring and a 0.8% rise in NHS staff's willingness to work as full-time equivalents per 10% wage increase. Approximately 22% of the wage disequilibrium adjusts quarterly, indicating moderate speed of wage adjustment. Our results suggest that wage setting is not a sufficient solution to the labour crisis. Innovative and sustainable solutions are needed to reduce the demand for skilled health labour and increase the supply of health labour.

Digital Transformation of Enterprises and Labor Force Structure Upgrading: Research Progress and Prospect

The transformation of the enterprise digital economy has had a profound effect on the employment of the labor force. Although extant document has discussed the digital economy, there is still a large space for deep analysis and theoretical framework construction of the impact of the digital Economy in Workforce Transformation. This research will look at the intrinsic impact of the digital economy on labor transfer or distribution. Digital capital complements a highly skilled labor force and promotes the upgrading of enterprise labor skill structure; digital transformation mainly affects three aspects: adopting new digital technology, optimizing labor organization form and adjusting business model. Changes of labor force in all respects as a result of the digitalization of business. In the background of the popularization of digital technology, the demand for low-skilled labor rises in the market, which promotes the upgrade of a commodity economy and the pursuit of a higher level of life; Digital transformation promotes the upgrading of enterprise labor skill structure, and different development regions and sizes have distinct differences in labor substitution. The effects of the digital transition can positively affect the innovation of the business model. Based on digitalization, The labor market's iterative renewal will have a decisive impact on the improvement of technology levels and the changing labor force structures.

Automation and disappearing routine occupations in Japan

We examine the implications of automation technology in Japan since 1980, comparing different local labor markets with different degrees of automation exposure. First, we do not find evidence that automation reduces employment rate within demographic groups and automation encourages workers to move from regular to non-regular employment. Second, we show that automation shifts employment from routine occupations in the manufacturing sector to service sectors, while increasing the share of establishments and sales in the manufacturing sector. Finally, we show that this shift in labor demand is attributed to younger generations and non-college-educated workers.

Development of optimized artificial diets for enhanced growth of Zophobas atratus larvae

AbstractThis study evaluates the effects of various artificial diets on the development of Zophobas atratus larvae. Artificial diets containing various concentrations of agar were also investigated for their ability to reduce death rates during the early stages of larval development. Our results indicated that larvae fed artificial diets experienced a slightly longer developmental period but achieved significantly higher weights. Notably, wheat bran + fish meal 6% resulted in the highest weight gain; however, wheat bran + fish meal 6%, wheat bran + fish meal 5% + ginseng leaf 1%, and wheat bran + fish meal 4% + ginseng leaf 2% yielded higher death rates. The diet with 4% agar resulted in the shortest developmental period, whereas that with 3% agar produced the highest weight gain. However, considering death rates, the diet with 2% agar provided the most balanced outcome across developmental time, weight gain, and survival, making it the most suitable diet for Z. atratus larvae. In conclusion, wheat bran + fish meal + agar 2% artificial diet is more suitable for Z. atratus larval development than wheat bran, leading to greater weight gain, shorter development periods, and higher adult emergence rates. Additionally, this diet showed the potential to reduce the dust issues and labor demands associated with wheat bran usage. Our findings suggest that wheat bran + fish meal + agar 2% could be an effective artificial diet for the optimal development of Z. atratus larvae.

Monitoring cattle liveweight using a mobile, in-paddock weigh platform: Validation, attendance and utility

Cattle liveweight (LW) monitoring is essential for the effective management of animal productivity and welfare, particularly in decision-making on farms. Traditional static weigh (SW) systems require animals to be moved to fixed scales, posing challenges in extensive beef systems due to labour demands, costs, stress, and weight loss during muster. This study evaluated the relationship between LW measured by a SW system and a mobile in-field weighing system, Optiweigh (OW), in 65 weaners (Angus, Shorthorn, and Angus-Shorthorn cross) grazing forage oats on a commercial beef property in north-west NSW, Australia. Over 22 weeks, cattle were weighed fortnightly using SW scales in the cattle yards while OW continuously monitored LW in the paddock. Lin's concordance correlation coefficient showed a strong association between OW and SW liveweight (CCC = 0.97; P < 0.001), with no influence of breed or sex. However, OW slightly over-predicted LW for lighter cattle (≤ 382 kg) and under-predicted for heavier cattle (> 382 kg), prompting the development of a correction. Further research is needed to understand the reasons for these discrepancies, potentially related to diet. Additionally, cattle attendance at OW was affected by size, season, and individual variation (P < 0.001). Overall, the OW system simply and accurately monitored the temporal changes in cattle LW through voluntary animal attendance in remote systems.

Development Of A User-Friendly Automated Poultry Feeding System

The huge cost and high labor demand associated with the current deep litter system of poultry farming poses a great challenge to poultry farming. These drawbacks which currently threatens this system of farming, have been attributed to the over-involvement of humans in almost all aspects of operation of this farming system. The consequences are increased disease outbreak, weakness and poor bird feeding. To ameliorated some of these challenges, an automated poultry feeding system is developed and presented in this paper. The proposed system mimics the roles of real-life poultry attendants in delivery of feed and water to birds at specified interval of time. The system controls the dispensing of poultry feed (liquid and solid) through a program written on ATmega328P microcontroller via the Arduino Uno. The system senses the level of feed and water in the respective trough and intelligently dispense water and feed in response to the sensed levels. The current system is able to effectively sense and predict the level of feed and water in the farm at an accuracy of 98.79% and dispense same within a response time of 50-60ms.

Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model.

Induction of labor, often used for pregnancy termination, has globally rising rates, especially in high-income countries where pregnant women present with more comorbidities. Consequently, concerns on a potential rise in cesarean section (CS) rates after induction of labor (IOL) demand for improved counseling on delivery mode within this context. We aim to develop a prognostic model for predicting vaginal delivery after labor induction using computational learning. Secondary aims include elaborating a prognostic model for CS due to abnormal fetal heart rate and labor dystocia, and evaluation of these models' feature importance, using maternal clinical predictors at IOL admission. The best performing model was assessed in an independent validation data using the area under the receiver operating curve (AUROC). Internal model validation was performed using 10-fold cross-validation. Feature importance was calculated using SHAP (SHapley Additive exPlanation) values to interpret the importance of influential features. Our main outcome measures were mode of delivery after induction of labor, dichotomized as vaginal or cesarean delivery and CS indications, dichotomized as abnormal fetal heart rate and labor dystocia. Our sample comprised singleton term pregnant women (n = 2434) referred for IOL to a tertiary Obstetrics center between January 2018 and December 2021. Prediction of vaginal delivery obtained good discrimination in the independent validation data (AUROC = 0.794, 95% CI 0.783-0.805), showing high positive and negative predictive values (PPV and NPV) of 0.752 and 0.793, respectively, high specificity (0.910) and sensitivity (0.766). The CS model showed an AUROC of 0.590 (95% CI 0.565-0.615) and high specificity (0.893). Sensitivity, PPV and NVP values were 0.665, 0.617, and 0.7, respectively. Labor features associated with vaginal delivery were by order of importance: Bishop score, number of previous term deliveries, maternal height, interpregnancy time interval, and previous eutocic delivery. This prognostic model produced a 0.794 AUROC for predicting vaginal delivery. This, coupled with knowing the features influencing this outcome, may aid providers in assessing an individual's risk of CS after IOL and provide personalized counseling.

Create or squeeze out? The effect of environmental protection tax on labor demand and labor demand transfer: evidence from China

Create or squeeze out? The effect of environmental protection tax on labor demand and labor demand transfer: evidence from China

Incorporating model selection and uncertainty into forecasts of economic conditions in companion animal clinical veterinarian labor markets.

Following the onset of COVID-19, demand for US veterinary services rapidly increased, similarly driving up demand in upstream veterinary labor markets. This increasing demand starkly contrasted with the "excess capacity" period following the Great Recession, marked by fewer opportunities and low wages for veterinarians. Better models and forecasts of veterinary labor market conditions improve information for decision-making by veterinarians, relevant business owners, professional associations, and educational institutions. Well-performing approaches will adapt to new data as they become available and avoid the assumption that short-term market dynamics will persist permanently. In this paper, we modify an approach often used to identify the forecasting model best suited to the data. Then, using the best forecasting model, we generate forecasts and prediction intervals around them to meet the available data and realities of veterinary labor markets to 2035. This approach removes subjectivity, accommodates model refinements, and acknowledges that the future is unknown. We find that the supply and demand indicators for veterinary services both indicate continued growth. We do not find statistically significant or consistent differences in either supply or demand growth, which would be consistent with a competitive market for veterinary services and labor. The data do not support an expectation of a continued shortage in the US veterinarian labor markets, as suggested in previous studies. We identify several areas where improved data resources and further methodological advancements could shed more light on the economic conditions facing veterinarians.

Does professional identity mediate the relationship between emotional labour and work engagement? A study with Portuguese police officers

Police officers work under demanding emotional, psychological and physical circumstances while interacting with victims, criminals and colleagues. They are faced daily with emotional demands to express positive emotions and, at the same time, are required to suppress negative emotions. Consequently, this influences the emotional regulation strategies (i.e., deep- or surface-acting) they choose to use, which impacts their professional identity and work engagement. We conducted a study to understand whether professional identity mediates the relationship between emotional labour (demands and strategies) and work engagement in a sample of Portuguese police officers. For this purpose, we used a set of four self-administered questionnaires: Emotional Work Requirements Scale (EWRS), Emotional Labour Scale (ELS), Social Identity Scale (SIS) and Utrecht Work Engagement Scale (UWES). 924 police officers from the Portuguese Public Security Police (PSP) participated voluntarily. Our results show that there is a mediating effect of professional identity on the relationship between surface-acting strategies, positive emotion expression and negative emotion suppression demands, and work engagement. Professional identity fully mediates the relationship between negative emotion suppression demands and work engagement. Nevertheless, there seems to be no mediating effect of professional identity on the relationship between deep-acting strategies and emotional variety and intensity demands, and work engagement. To the best of our knowledge, no other study has analysed the aforementioned variables in Portuguese police forces. Meaning that our study is ground-breaking, with clear implications. Further research is needed on this subject to understand better the relationship among these variables in the police population.

Modelling of the Ukrainian labor market: system dynamics approach

The purpose of the article is to develop a System Dynamics model of the functioning and development of the Ukrainian labor market, which can subsequently be used to simulate various government decisions and policies. The Stella Architect software is used to construct the model, allowing to provide insights into the current state of the labor market and forecasts future trends, helping identify potential improvements.The explanatory System Dynamics Model effectively demonstrates the complex interrelationships that influence the dynamics of the Ukrainian labor market. The identified balancing loops highlight key factors such as retirement, business closures, production levels, and the formation of new businesses, all of which shape labor supply and demand. Each loop illustrates how changes in one economic aspect can impact others, underscoring the interconnectedness of labor dynamics, economic growth, and business development. Furthermore, the developed causal loop diagrams emphasize the cyclical nature of these interactions, where increases in labor supply can result in higher wages and GDP, leading to further investment and business creation. This model offers valuable insights into the feedback mechanisms that may stabilize or destabilize the labor market, particularly in response to external shocks or policy interventions. In the future, the developed model can be used to test various policies for major elements of the model and to simulate its behavior.

Testing the Goodwin Model: Can Distribution Battles Trigger Business Cycles? Evidence from a Behavioral Experiment

AbstractThe Goodwin model provides an important explanation for business cycles with its investment decisions based on pro-cyclical wage fluctuations. The purpose of this paper is to test the central hypothesis of the Goodwin model, namely that wage developments influence investments, which creates business cycles. The model used to test this hypothesis was that of a simplified company, where labor demand is related to investments. Thus, more investments lead to higher wages and vice versa. In the behavioral experiment the test subjects played the manager of a company who maximizes their profits through investments. The central assumptions and conclusions of the Goodwin model are supported by behavioral science.

Animal spirits at play? Firm sentiments and labour demand during the COVID‐19 pandemic

Economists have long theorized that sentiments, or spontaneous beliefs that are unjustified by economic fundamentals, are a driver of economic behaviours. In this study, I explore whether such sentiments influenced firms’ behaviours following the outbreak of COVID‐19. Using a sample of Italian firms, I observe that in the immediate aftermath of the outbreak, firms’ expectations about post‐COVID economic recovery largely reflected beliefs unexplained by their COVID‐related experiences. I then show that these beliefs were associated with firms’ labour market behaviours. Firms that displayed more pessimistic beliefs were more likely to implement cost‐cutting labour market measures, such as dismissing employees and reducing work hours.

State-led Maritime Governance, Education and Training Nexus in South Africa

The maritime environment has a significant socio-economic impact on nations, regional and global economies. However, it also experiences many challenges related to safety, security, Education and Training (E &amp; T) which stakeholders such as businesses and government through State institutions play a crucial role in addressing. In addition to high global labour demands, E &amp; T challenges have related to the decreasing number of youth taking up maritime E &amp; T. In addition, technological advancements affect costs, standards, and quality of maritime ET. The Republic of South Africa (RSA) has not been immune to these challenges. Public higher E &amp; T institutions in RSA are the primary providers of tertiary maritime E &amp; T but remain confronted by numerous challenges tied to organisational resources, State funding and the growing demand for increased internal and external capacity. This study’s objective was to examine maritime State-led interventions and challenges in selected public higher E &amp; T institutions offering maritime studies in the coastal province of KwaZulu-Natal (KZN), RSA. Guided by a Systems Thinking approach, this empirical study adopted a qualitative research methodology utilizing interviews with key knowledge holders and secondary data. It was found that there exists a consensual view that higher E &amp; T institutions offering maritime studies in the province are well positioned to play a more meaningful role in addressing the country’s high unemployment rate. However, the current conditions in maritime E &amp; T have undermined this and resulted in the pursuit of international partnerships to address local deficiencies. These findings are significant to stakeholders involved in maritime higher E &amp; T, State-led maritime interventions, policymaking, governance, management, leadership and administration. The findings of the study also point to the need for a holistic understanding of maritime issues and challenges as maritime E &amp; T is a complex global social space. This could eventually facilitate innovation, enhance leadership and contribute to meaningful and crucial partnerships between developed and more developing nations.

Abstract 4124675: Deep Learning Screening of Cardiac MRIs Uncovers Undiagnosed Hypertrophic Cardiomyopathy in the UK BioBank

Introduction: The prevalence of hypertrophic cardiomyopathy (HCM) in the UK Biobank based on ICD-10 codes (.07%) is lower than global estimates of disease prevalence (0.2 - 0.5%). Prior studies using this data have remarked on the limitations of findings given likely underdiagnosis. The availability of cardiac MRI scans on a fraction of the participants offers an opportunity to identify missed diagnoses. Aims: This study seeks to utilize a generalizable deep learning model to detect likely cases of undiagnosed hypertrophic cardiomyopathy from cardiac MRIs in the UK Biobank. Methods: The foundational model was trained on a multi-institutional dataset of 14,073 cardiac MRIs via a self-supervised contrastive learning approach that sought to minimize the divergence between scans and their associated radiology reports. The pre-trained model was fine-tuned to diagnose hypertrophic cardiomyopathy on a distinct cohort of 4,870 MRIs with 368 cases of HCM, achieving an AUC of 0.94. The fine-tuned model was applied to the UK Biobank cardiac MRI dataset to ascertain predicted probabilities of HCM. Cases exceeding a threshold of 95% – correlating to the top 0.5% of cases (expected specificity of 97% and sensitivity of 60%) – were screened in for manual reading. In a blinded fashion, a board-certified radiologist was tasked with diagnosing HCM on a sample of cases composed of high and low predicted probabilities. Results: Of the 43,017 patients with cardiac MRIs, only 9 (.02%) had an ICD diagnosis of HCM. 266 cardiac MRIs were manually reviewed: 216 had greater than 95% predicted probability of HCM; 50 negative controls were randomly selected amongst cases with predicted probability less than 10%. The radiologist concurred with an HCM diagnosis for 115 cases (sensitivity 53%, specificity 98%), 112 of which were previously undiagnosed. The prevalence of hypertension and aortic stenosis did not significantly differ between the cohort of true positives (69.2%) and false positives (76.6%). The corrected prevalence of HCM in the UK BioBank MRI cohort is estimated at 0.28%. Conclusions: The findings of this study illustrate the remarkable ability of a generalizable deep learning model to detect undiagnosed cases of a rare disease process from cardiac MRIs. This is an important milestone that may allow for widespread screening of hypertrophic cardiomyopathy while minimizing demand for radiologist labor, and thereby allow patients to reap the substantial benefits of earlier treatment.

Economic impact of retirement on the elderly population: a literature review

ABSTRACT This literature review examines the economic impact of retirement policies on the elderly, focusing on labor supply, consumption, and health. The aging global population pressures public pension systems, prompting reforms like increasing retirement age and reducing benefits, which significantly affect labor supply, demand, and economic growth. The review discusses the effects of retirement age and pension changes on labor supply, the ‘retirement-consumption puzzle,’ where consumption declines at retirement due to changes in time cost and health shocks, and mixed health outcomes post-retirement influenced by health behaviors. China’s fixed retirement policy offers a unique context for studying these effects, highlighting gender-specific impacts. The review emphasizes the need for balanced retirement policies that consider financial sustainability and health implications, promoting retirees’ consumption levels. This comprehensive analysis aids in evaluating retirement policy reforms’ costs and benefits across different institutional contexts.

Modern conditions for reproduction of the educational potential of the Russian workforce

The relevance of the research is related to the need to substantiate the specifics of reproduction of the educational potential of workforce as a key resource that ensures generation of new knowledge, its successful implementation into practice, and innovative development of domestic enterprises. The purpose of the article is to identify and analyse modern conditions for the reproduction of the educational potential of the workforce. The research methodology is based on the use of an integrated and systematic approach to determining them, comparative and statistical methods of analysis. As conditions for the formation of the educational potential in the post-industrial era, the article considers: demographic conditions, globalisation, formation of a unified information space, and digitalisation of the economy, increasing demand for skilled labour, accelerated development of the service sector, and increase in labour migration. The results of the analysis show that in Russia, the reproduction of the educational potential is hampered as a result of the demographic crisis manifested in the continuation of the trend towards natural population decline and an increase in the number of people of retirement age; increase in the scale of external migration of skilled labour; average level of Internet accessibility to the population, and, as a result, insufficient formation of its digital skills. Attention is focused on the growing need of the national economy for personnel with a high educational and qualification level, digital skills, and information culture due to the formation of a unified information space and digitalisation of the economy, accelerated development of the service sector, globalisation, and the increasing role of universities in shaping the general culture of the population. The prospects for further research are to develop an organisational and economic mechanism for reproducing the educational potential of the workforce.

U.S. Job-Seekers' Organizational Justice Perceptions of Emotion AI-Enabled Interviews

Emotion AI is increasingly used to automatically evaluate asynchronous hiring interviews. Although touted for increasing hiring fit and reducing bias, it is unclear how job-seekers perceive emotion AI-enabled asynchronous interviews. This gap is striking, given job-seekers' marginalized position in hiring and how job-seekers with marginalized identities may be particularly vulnerable to this technology's potential harms. Addressing this gap, we conducted exploratory interviews with 14 U.S.-based participants with direct, recent experience with emotion AI-enabled asynchronous interviews. While participants acknowledged the asynchronous, virtual modality's potential benefits to employers and job-seekers, they perceived harms to job-seekers associated with automatic emotion inferences that our analysis maps to distributive, procedural, and interactional injustices. We find that social identity can inform job-seekers' perceptions of emotion AI, extending prior work's understandings of the factors contributing to job-seekers' perceptions of AI (broadly) in hiring. Moreover, our results suggest that emotion AI use may reconfigure demands for emotional labor in hiring and that deploying this technology in its current state may unjustly risk harmful outcomes for job-seekers - or, at the very least, perceptions thereof, which shape behaviors and attitudes. Accordingly, we recommend against the present adoption of emotion AI in hiring, identifying opportunities for the design of future asynchronous hiring interview platforms to be meaningfully transparent, contestable, and privacy-preserving. We emphasize that only a subset of perceived harms we surface may be alleviated by these efforts; some injustices may only be resolved by removing emotion AI-enabled features.