Employment Trends Research Articles

Sustainable Vocational Preparation for Adults with Disabilities: A Metaverse-Based Approach

This research introduces a sustainable, metaverse-based vocational preparation program designed to empower adults with disabilities, providing them with the necessary skills to secure and retain employment in a landscape drastically altered by the Fourth Industrial Revolution and the COVID-19 pandemic. After implementing the program with nine adults with disabilities, the Wilcoxon signed-rank test was used to analyze the differences in the pre- and post-tests of the study participants. As a result, the participants’ interpersonal relationships, problem-solving abilities in the workplace, and online interview skills were significantly improved. This study holds significance in its innovative approach to vocational education, adapting to shifts in employment trends and providing interventions in the metaverse that transcend traditional educational settings.

MODERN STATISTICAL TRENDS OF EMPLOYMENT AND OUTPUT OF PRODUCTS IN THE REGIONS OF GEORGIA

Simon Gelashvili
 E-mail: simon.gelashvili@tsu.ge
 Doctor of Economic Sciences, Professor Ivane Javakhishvili Tbilisi State University 
 Tbilisi, Georgia
 https://orcid.org/0009-0004-8574-9383
 Abstract: The presented work concerns a very relevant topic - the quantitative research of employment and output of products in the administrative regions of Georgia. What is the employment situation according to the administrative regions of the country is of great economic and social importance. The purpose of the research is to identify and evaluate statistical trends in employment and output of products. The analysis period covers the years 2010-2022. Accordingly, on the basis of official statistical data, appropriate indicators are calculated, their changes are determined and their mutual comparison is given.
 In the research process, methods of statistical science are used, such as: data grouping, relative, average and variation indicators, presentation, etc. 
 As a result of the conducted analysis, it was determined that the obtained indicators are heterogeneous according to various signs - according to regions, according to time, volume of employment level, volume of released products and labor productivity. According to the mentioned indicators, very different trends were revealed.
 To determine the degree of economic inequality of regions, it is of great importance to study their economic activity, to identify and evaluate appropriate trends. Such an analysis, first of all, allows to determine different types of disproportion, which is a good basis for developing and implementing regional economic and social policies. The level of economic development of the country's administrative regions can be assessed by various quantitative and qualitative criteria. In this case, the following quantitative criteria will be considered: the level of employment, the volume of output of product and the level of labor productivity.
 Analyzing the data of the official statistics, it is clear that Adjara and Imereti take the leading position after Tbilisi in terms of the number of employees, where the number of employees increased in 2010-2022. In these regions, the population is relatively larger, which, of course, is proportionally reflected in the level of employment. In the analysis period, the average annual number of employees in all administrative regions of Georgia is characterized by a clearly expressed rapid growth trend: the number of employees increased 2 times and more in Mtskheta-Mtianeti (2.7times), Guria - 2.5 times and Adjara - 2.4 times. Racha-Lechkhumi and Kvemo Svaneti regions showed relatively lower growth rate.
 One of the main characteristics of the region's economic activity is the volume of output of the product per employee on average, which measures the level of labor productivity. We have calculated the mentioned indicator according to all administrative regions of Georgia, on the basis of which it is possible to statistically assess the level of labor productivity in the regions according to each year of the analysis period and also to reveal a 12-year trend. In 2010, the highest level of labor productivity was in Kvemo Kartli, Mtskheta-Mtianeti and St. in Tbilisi, and the lowest in Racha-Lechkhumi and Kvemo Svaneti, as well as in Kakheti. The positioning of these regions according to the mentioned indicator was the same in 2022.
 An important statistical characteristic is the positioning of regions according to the share of output of product. In 2022, the city is in the leading position with this indicator. Tbilisi, which is not surprising, because the largest part of the enterprises of the real sector of the economy is located here. The next position is held by Adjara, which moved from the 4th position in 2010 to the second and Kvemo Kartli. Racha-Lechkhumi and Kvemo Svaneti and Guria are in the last positions with the smallest share. These 2 regions were in the same positions in 2010.
 As a result of the comparative analysis of the indicators of the employment level and the volume of output and the evaluation of the range of variation, a disproportion of different degrees between individual regions was revealed, which has a certain impact on economic growth and the level of socio-economic inequality.

A bilateral employment situation prediction model for college students using GCN and LSTM.

Due to the prevailing trend of globalization, the competition for social employment has escalated significantly. Moreover, the job market has become exceedingly competitive for students, warranting immediate attention. In light of this, a novel prognostic model employing big data technology is proposed to facilitate a bilateral employment scenario for graduates, aiding college students in promptly gauging the prevailing social employment landscape and providing precise employment guidance. Initially, the focus lies in meticulously analyzing pivotal aspects of college students' employment by constructing a specialized employment platform. Subsequently, a classification model grounded in a graph convolution network (GCN) is built, leveraging big data technology to comprehensively comprehend graduates' strengths and weaknesses in the employment milieu. Furthermore, based on the outcomes derived from the comprehensive classification of college students' qualities, a college students' employment trend prediction method employing long and short term memory (LSTM) is proposed. This method supplements the analysis of graduates' employability and enables accurate forecasting of college students' employment trends. Empirical evidence substantiates that my proposed methodology effectively evaluates graduates' comprehensive qualities and successfully predicts their employment prospects. The achieved F-values, 82.45% and 69.89%, respectively, demonstrate the efficacy of anticipating the new paradigm in graduates' dual-line employment.

The Federal Reserve's Interest Rate Policy and Its Impact Against a Background of Inflation and High Unemployment Rate

This research adopts various economic data sources to investigate the effects of Federal Reserve (Fed) policies on the US economy. Specifically, the study focuses on labor market flows, short and long-term inflation expectations, and interest rates from 1960 to 2023. The findings suggest that over the past three decades, the Fed has artificially manipulated interest rates to curb long-term increases in unemployment. In this regard, this paper discusses the Impact of Business Financing and Costs, Labor Costs and Prices, Impact on Market Supply and Demand on interest rate changes from three perspectives. This study delves into detailed micro data on job vacancy rates and average earnings coefficients for different workers. By analyzing these factors and interest rate data, the paper argues that there is a strong correlation between employment trends and the Federal Reserve's monetary policy. Based on the data, the study projected that even if long-term inflation expectations remained stable, underlying inflation would still be half a percentage point above its long-term trend by the end of 2023. Overall, the paper provides valuable insight into the complex relationship between Fed policy, employment trends, and inflation in the U.S. economy.

Impacts of educational debt on physical therapist employment trends

BackgroundNewly graduated physical therapists have high amounts of educational debt.Educational debt may negatively affect job satisfaction, aspirations for professional development, and choice of workplace setting. Research has not shown this association directly, yet it is conceptually supported by the Labor-Search Model. The purpose of this study was to understand the role that educational debt has on additional factors related to job choice in the Labor-Search Model.MethodsRetrospective data were captured through the Virginia Longitudinal Data System (VLDS) for 12,594 licensed physical therapists within the Commonwealth of Virginia from 2014 to 2020. A fixed effects panel analysis, with inflation-adjusted educational debt as the variable of interest, was conducted to assess whether patterns of professional certifications, volume of work, workplace setting, and job satisfaction were related to educational debt.ResultsEducational debt was positively correlated with higher professional degrees (p = 0.009), the number of hours worked per week (p = 0.049), and expected number of years until retirement (p = 0.013). Job satisfaction was statistically significant (p = 0.042) and negatively correlated with educational debt.Conclusions Those with higher educational debt appear to have the habit of working more hours per week and have a longer time horizon until retirement. Newly licensed physical therapists with higher amounts of educational debt are more likely to experience this trend. Income and job satisfaction demonstrated an interaction effect on educational debt, such that those with lower levels of income had a stronger, negative relationship between their debt and job satisfaction, as compared to those with higher income.

Employment Trends of COVID-19 Graduates: The Case of a Malaysian Public University

Employment Trends of COVID-19 Graduates: The Case of a Malaysian Public University

The influence of government policies on the nurse practitioner and physician assistant workforce in the Netherlands, 2000–2022: a multimethod approach study

BackgroundMany countries are looking for ways to increase nurse practitioner (NP) and physician assistant/associate (PA) deployment. Countries are seeking to tackle the pressing issues of increasing healthcare demand, healthcare costs, and medical doctor shortages. This article provides insights into the potential impact of various policy measures on NP/PA workforce development in the Netherlands.MethodsWe applied a multimethod approach study using three methods: 1) a review of government policies, 2) surveys on NP/PA workforce characteristics, and 3) surveys on intake in NP/PA training programs.ResultsUntil 2012, the annual intake into NP and PA training programs was comparable to the number of subsidized training places. In 2012, a 131% increase in intake coincided with extending the legal scope of practice of NPs and PAs and substantially increasing subsidized NP/PA training places. However, in 2013, the intake of NP and PA trainees decreased by 23% and 24%, respectively. The intake decreased in hospitals, (nursing) home care, and mental healthcare, coinciding with fiscal austerity in these sectors. We found that other policies, such as legal acknowledgment, reimbursement, and funding platforms and research, do not consistently coincide with NP/PA training and employment trends. The ratios of NPs and PAs to medical doctors increased substantially in all healthcare sectors from 3.5 and 1.0 per 100 full-time equivalents in medical doctors in 2012 to 11.0 and 3.9 in 2022, respectively. For NPs, the ratios vary between 2.5 per 100 full-time equivalents in medical doctors in primary care and 41.9 in mental healthcare. PA-medical doctor ratios range from 1.6 per 100 full-time equivalents in medical doctors in primary care to 5.8 in hospital care.ConclusionsThis study reveals that specific policies coincided with NP and PA workforce growth. Sudden and severe fiscal austerity coincided with declining NP/PA training intake. Furthermore, governmental training subsidies coincided and were likely associated with NP/PA workforce growth. Other policy measures did not consistently coincide with trends in intake in NP/PA training or employment. The role of extending the scope of practice remains to be determined. The skill mix is shifting toward an increasing share of medical care provided by NPs and PAs in all healthcare sectors.

Trends in Employment, Productivity, Real Wages and Labour Standards in Indian Manufacturing in Recent Years

Trends in Employment, Productivity, Real Wages and Labour Standards in Indian Manufacturing in Recent Years

The imbalance of the labor market in Ukraine: current trends and guidelines for overcoming disproportions

The imbalance of the labor market in Ukraine: current trends and guidelines for overcoming disproportions

The economic impact of social distancing: Evidence from state-collected data during the 1918 influenza pandemic

What are the long-run economic impacts of the policy responses to control pandemics? We investigate this question by exploiting state-collected data spanning one of the most consequential global pandemics in centuries, the 1918 influenza pandemic. Specifically, we use a difference-in-differences framework to examine the effects of non-pharmaceutical interventions (NPIs), ultimately finding no long-run impact of NPIs on employment, positive or negative. Employment trends prior to 1918 suggest that World War One is an important confounding factor in analyses of the pandemic, since cities with tighter NPIs grew rapidly between 1914 and 1918. We identify new control variables that account for war production and find that social distancing did not have long run employment impacts. The evidence underscores the importance of accounting for confounding economic and policy factors for understanding the impact of pandemics on economic outcomes.

Human Resource Analytics on Data Science Employment Based on Specialized Skill Sets with Salary Prediction

The research aims to perform meaningful human resource analysis on data science employment using the strong influences of specialized skills set with assisting salary prediction. With explosive big data development, a data science job shortage has occurred with high accurate recruitment demand to hire suitable professionals for specific data science roles. To achieve such outcomes, the current data science employment trends were analyzed based on a secondary dataset. Useful analytics insights for job securement and better career development were provided through the main dashboard. Besides, the significant in-demand data science skill variables were also identified for further effective model building. Particularly, certain data pre-processing techniques were performed extensively to prepare and optimize the dataset for the mentioned human resource analytics purposes. The ensemble model was selected as the most suitable salary prediction model with the lowest Average Squared Error (ASE) on validation. Despite the low prediction accuracy caused by numerous filtered skill variables, the salary prediction model’s main objective was to interpret the relationships between input variables and the target salary levels variable. Overall, the results from both the human resource analytic dashboard and salary prediction model were tally where a detailed analytic report was provided to encourage different data science roles with specific and effective career development guidance, using salary as the motivation key.

Transformation of Labor Market of Ukraine: Professional Qualifications Assessment

The article analyzes the structural shifts in professional qualifications employment of the Ukrainian population, revealing the trends and nature of their changes. It has been found that the labor market is characterized by multidirectional trends. On the one hand, according to formal features, the professional qualifications structure of the population is approaching the indicators peculiar to a developed labor market: set against the reduction of the employed in the simplest occupations, there is an increase in the number of professionals, and trade and services workers. At the same time, the analysis of the interprofessional distribution of the workforce, carried out by the method of resulting shifts, has shown that in a number of professional groups of exclusive value for the country’s economic development, there is a net outflow of workforce.
 The revealed destructive processes indicate the absence of a well-formed basis for a profound qualitative restructuring of the national labor market. The available trends are due to the following key factors: inadequate level of the institutional provision of the labor market, and the impact of global employment trends. With the beginning of the full-scale Russian military aggression against Ukraine, the national labor market initially froze, but is gradually adapting to war conditions. Under the outlined conditions, the priority tasks of state bodies will be the complex reconstruction and development of the real sector on an innovative basis in connection with the labor market development strategy, the key task of which is to improve the wage mechanism and increase the cost of labor.

Characterizing the landscape of plant science careers in the United States I: Government and private sector perspectives

Societal Impact StatementHumans are dependent upon plants for oxygen, food, textiles, and medicines. Climate change and deforestation represent serious threats to our planet, causing significant disruptions to our ability to access and utilize these plant resources; this makes a botanically literate workforce and plant science careers more important than ever. Unfortunately, the current state of botanical career opportunities and training programs in the United States remains unclear. This study focuses on the current employment trends of government and private sector botanists and what skills future plant scientists will need to be successful in these careers.Summary Plant science plays a crucial role in our society and in ongoing efforts to address many global challenges, including food insecurity and climate change. Yet, despite a predicted increase in plant science career opportunities in the United States, the botanical career landscape outside of academia is not well understood. To further our understanding of the training required for non‐academic botanical careers, the botanical sub‐disciplines used on the job, and career challenges faced by plant scientists, we surveyed 61 scientists working in government and 59 scientists working in the private sector in the United States. In both career sectors, > 80% of survey participants reported recent hires at the bachelor's degree level. New personnel with master's degrees were more commonly reported in the government sector (95%) than in the private sector (69%). Most plant scientists working in government reported a focus on plant ecology and resource management. By contrast, most industry/non‐profit work involved horticulture and biotechnology, with some specific skills spanning both sectors. Notably, one prediction made nearly a decade ago appears to be manifesting: plant scientists seem to be retiring more quickly than they are being replaced. Survey respondents reported that attempts to hire full‐time staff are met with obstacles, including insufficient funding. Plant science professionals in both career sectors emphasized their routine use of botanical skills developed as students, highlighting the need for effective training at the undergraduate level. We discuss the implications of these findings and present several recommendations for preparing future generations of plant scientists and increasing the scientific community's botanical capacity.

Assessment of risks and prospects of employment and income of the rural population of Ukraine

Employment, total household resources, in particular, income and expenditures of the rural population in any country are a direct reflection of well-being and a substantial criterion for socio-economic development. The purpose of the study is to identify risks, compare and determine the prospects for employment and income of the rural population of Ukraine. The methodological basis of the research is a systematic approach. Comparative analysis, graphical method, trend, index, correlation-regression analysis is used in the analytical study. Current conditions are analysed and trends in rural employment in Ukraine and their income level for 1991-2021 are determined. It was established that over the past 30 years, the socio-economic crisis in rural areas continues to worsen, which is manifested in increased unemployment and poverty. The main external and internal factors influencing the incomes of the rural population are identified and systematised. It is determined that the main influence is exerted by economic factors. Considering the recovery plan of Ukraine and other indicators, the level of employment, salaries, and incomes of the rural population is predicted. It is proved that ensuring employment and overcoming poverty should be based on the diversification of agricultural production and beyond agricultural activities. The main provisions and conclusions presented in the study can be used in the process of justifying and making managerial decisions by state management bodies in the development and implementation of an effective long-term national policy in the field of employment of the rural population of Ukraine, optimising approaches to the development of programmes to increase the income of the rural population.

Assessing the economic consequences of an energy transition through a biophysical stock-flow consistent model

The biophysical foundations of socio-economic systems are underrepresented in the vast majority of macroeconomic models. This lack is particularly troublesome when considering the links between energy, matter and the economy in the context of the energy transition. As a remedy, we present here a biophysical stock-flow consistent macroeconomic model calibrated at the global scale, that combines detailed bottom-up estimates for the high capital intensity of renewable energies and the decreasing energy return on investment (EROI) of fossil fuels. We find that the completion of a global energy transition scenario compatible with the 1.5 °C objective of the Paris Agreement leads to a decrease of the system’s EROI and to high investment share, employment and inflation trends, characteristic of a “war economy”. Our results further indicate that a slower growth rate eases the transition, and call for further work on post-growth scenarios studies.

Identifying social thresholds and measuring social achievement in social-ecological systems: A cross-regional comparison of fisheries in the United States

In marine social-ecological systems (SESs), environmental and human-induced stressors can push ecosystems from a high-functioning state into a new, often undesirable state (i.e., regime shift) with limited delivery of ecological goods and services (e.g., high to low fisheries production). While ecological regime shifts are well studied, social regime shifts within SESs are underexplored. Socioeconomic indicators were used to identify thresholds and trends in fisheries and coastal employment for six marine SESs around the U.S. These study sites represent coastal regions delineated by the National Oceanic and Atmospheric Administration for which periodic monitoring and data collection occur. We first used Generalized Additive Modeling to identify periods of change, then linked them to potential regional and national drivers. Social outcomes were ranked using composite social and environmental indices for each region, constructed using Data Envelopment Analysis. Technological innovation and national regulatory changes (e.g., Magnuson Stevens Act) co-occurred with detected nationwide shifts in fisheries productivity, while engagement in specific fisheries determined local regional shifts. Our study demonstrates the effectiveness of the complementary threshold analysis and outcome ranking methods in identifying regimes and assessing performance. Together, they provide management information and insight into possibilities for preventing unfavorable shifts and to assess society’s ability to adapt to those shifts.

Trends in Kazakhstan labor market development in the context of economy transformation

The main employment trends are formed under the influence of structural transformations in the economy. The aim of this article is to determine the trends in the Kazakhstan labor market development in in the context of economy transformation over the past 10 years by studying the dynamics and structure of employment, depending on changes in the structure of republic’s gross domestic product. Generalization, comparison, economic-statistical (horizontal and vertical) and correlation analysis served as the main research methods. The statistical base of the study was the indicators of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan on employment and gross domestic product by type of economic activity for 2011, 2016 and 2021. During the study, it was determined that there is a pronounced (noticeable) direct statistical relationship between trends in the labor market and trends in the structure of the economy. It was revealed that the trends in labor market development in Kazakhstan are determined and depend on the trends of change and transformation of the economy structure. During the period from 2011 to 2021, the country's economy was transformed, namely, the share of the tertiary sector increased. The same trend is observed in the labor market. Thus, wholesale and retail trade, transport and warehousing, real estate transactions account for almost a third of the country's GDP. At the same time, the number of people employed in these areas is a quarter of the total number of employed. These sectors account for the highest labor productivity rates along with the mining industry. Interest in the service sector on the part of employed Kazakhstanis is growing, while in agriculture, forestry and fisheries is falling. The results of the study can serve as a scientific justification for the implementation of an effective policy in the field of labor and employment.

Optimizing Workplace Support for Breastfeeding in Female Worker; A Narrative Review

Introduction: The increasing participation of women in the labour market has led to a growing trend of female employment. This has a significant impact on women’s roles as mothers, particularly breastfeeding mothers. Objective: This review aims to discuss the benefits and challenges of breastfeeding faced by female workers in the workplace and how to counter itDiscussion: Breastfeeding in the workplace has several advantages for mothers, which may act as an incentive to combine breastfeeding and work. The advantages include reduced absenteeism, increased productivity, and decreased turnover rates. However, breastfeeding in the workplace presents several challenges, including the lack of research on the topic, the lack of support from employers, distance between home and work, the lack of lactation facilities on-site, and reduced milk production during work hours. This situation drives the development of a lactation promotion model that can support breastfeeding in the workplace. The lactation promotion model, comprised of seven major components, can be implemented in the workplace to increase exclusive breastfeeding and boost female worker productivity. Conclusion: It is recommended to give workers with under-6-month children the option of working part-time or returning home earlier and for companies to provide lactation support staff, educational materials, and peer support groups to help working mothers breastfeed at work. The role of company occupational doctors takes a very important place in this lactation promotion model to achieve high breastfeeding rate in female workers.

Mining Migrant Worker Recruitment Policy and the Production of a Silicosis Epidemic in Late 20th-Century Southern Africa.

Between the 1980s and 2000s, an epidemic of silicosis was identified in migrant black gold miners, many from neighbouring countries, who had worked in the South African gold mines. This study uses the newly available employment database of a large gold mining company to demonstrate how a sustained rise in employment duration in a new cohort of black migrant workers resulted from changes in recruitment policy, and it examines the implications for current surveillance and redress. Contract data of 300,774 workers from the employment database of a multi-mine gold mining company were analysed for 1973-2018. Piecewise linear regression was applied to determine trends in cumulative employment, including South African versus cross-border miners. The proportions with cumulative employment of at least 10, 15, or 20 years, typical thresholds for chronic silicosis, were also calculated. Five calendar phases were identified between 1973 and 2018. During the second phase, 1985-2013, mean cumulative duration of employment rose fivefold, from 4 to 20 years. Cumulative employment continued to rise, although more slowly, before peaking in 2014 at 23.5 years and falling thereafter to 20.1 years in 2018. Over most of the 1973-2018 period, miners from neighbouring countries had greater cumulative employment than South African miners. Overall, the proportion of miners exiting with at least 15 years of cumulative employment rose from 5% in 1988 to 75% in 2018. This report identifies a number of fundamental changes in labour recruitment policy in the gold mining industry in the 1970s which provide an explanation for the subsequent rise in cumulative exposure and associated silicosis risk. These new data support the hypothesis of a silicosis epidemic driven by increasing cumulative silica dust exposure in a new cohort of circular migrant workers from the 1970s. They inform current programmes to improve surveillance of this neglected population for silicosis and related disease and to provide medical examinations and compensation to a large number of former gold mines. The analysis highlights the lack of information on cumulative employment and silicosis risk among migrant miners in previous decades. The findings have global relevance to the plight of such migrant workers in hazardous occupations.

Investigating the application of a commercial and residential energy consumption prediction model for urban Planning scenarios with Machine Learning and Shapley Additive explanation methods

Building energy forecasting methodologies utilized by municipal governments tend to be geared heavily towards depicting broader qualitative representations of regional change and are in need of complementary data-driven models that can produce quantitatively reliable depictions of future energy consumption at the neighborhood-level. The current research demonstrates an application of a Machine Learning (ML) model in the form of an Extreme Gradient Boosting (XGBoost) algorithm for forecasting the energy use of commercial and residential buildings. The methodology serves to improve on municipal scenario planning by providing a more spatially granular representation of future energy use. In this way, city government and urban planners can more accurately set carbon emission benchmarks and target specific locales for sustainability initiatives. The second major contribution of the study is to demonstrate how scenario planning approaches can utilize existing Machine Learning techniques to compensate for gaps in the data. This work is developed through a case study of Philadelphia. The study begins with the construction of residential and commercial energy models for the year 2015 and corresponding models for the year 2045. The forecast models integrate regional socioeconomic trends from the Delaware Valley Regional Planning Commission (DVRPC) scenario of Enduring Urbanism. The commercial energy use model is developed from the DVRPC’s open-source Geographic Information System (GIS) datasets, the Commercial Buildings Energy Consumption Survey (CBECS), and CoStar commercial real estate data. The residential model applies the Residential Energy Consumption Survey (RECS), the Public Use Microdata Sample (PUMS), and Census Bureau American Community Survey (ACS) estimates. A corresponding SHAP (SHapley Additive exPlanations) analysis is implemented to pinpoint feature contributions to the model’s energy estimates. By using the PopGen software, the model’s energy estimates could be analyzed at the household level, the smallest possible scale. To provide a useful resource for key stakeholders, the study aggregates model output by Traffic Analysis Zone (TAZ) and Public Use Microdata Area (PUMA) to display a detailed forecast of energy use. The results indicate that the DVRPC Enduring Urbanism trends in income and employment do not significantly affect energy consumption for the study area. However, features related to lower building intensity (e.g., lower square footage, fewer floors per building) were associated with reduced energy use in both models. Additionally, the study found residential buildings under the “single-family attached” zoning designation to correspond with higher energy estimates.