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The purpose of the study is to assess if a policy of female inclusive education should be complemented with a policy of female ownership of bank accounts to fight female unemployment. The study therefore examines how female ownership of bank accounts moderates the incidence of female education on female unemployment.

The focus is on 44 sub-Saharan African (SSA) countries for the period 2004–2018 and the empirical evidence is based on interactive quantile regressions. The interactions are tailored such that female ownership of bank accounts influences the effect of female inclusive education on female unemployment.

From the empirical findings it is evident that female ownership of bank accounts does not effectively moderate female education in order to reduce female unemployment unless complementary policies are considered. The complementary policies should be in view of boosting the interaction between female education and female bank account ownership in increasing employment opportunities for the female gender and by extension, reducing female unemployment. The invalidity of the moderating effect is robust to the inclusion of more elements in the conditioning information set as well as accounting for other dimensions of endogeneity such as simultaneity and the unobserved heterogeneity. Policy implications are discussed.

This study contributes to the extant literature by assessing how female ownership of bank accounts complements female inclusive education to reduce female unemployment.

The purpose of this paper is to empirically analyze the impact of social inclusion factors and foreign fund inflows on reducing gender-based unemployment in India.

A time series data set for the period of 1991–2021 has been considered, and an autoregressive distributed lag methodology has been applied to measure the short- and long-run impact of social inclusion and foreign fund inflows on reducing gender-based unemployment in India.

According to the study’s findings, both social inclusion and foreign fund inflows are critical factors for reducing male unemployment. However, in the case of female unemployment, only social inclusion factors play an important role, whereas foreign fund inflows have no role in it.

Analyzing the factors that affect gender-based unemployment has always been a grey area in literature. There are very few studies that capture gender-based unemployment in India, making this study a novice contribution. Second, it examines the relationship between foreign fund inflows, social inclusion and unemployment, which is another novel area of investigation. Finally, this study provides comprehensive and distinct results for both male and female unemployment that can help policymakers devise gender-based unemployment policies.

This study clarifies the intricate nature of globalization's impact on unemployment rates in South Africa. Given the heterogeneous views on globalization's effect on economic development, this study aims to offer a nuanced perspective. Furthermore, it aims to explore the mediating role of entrepreneurial development in shaping the complex relationship between globalization and unemployment.

The study employs four key indicators to measure entrepreneurial development, globalization and unemployment rates in South Africa. Hierarchical regression is used to evaluate the relationship between globalization and unemployment rates, and how entrepreneurial development mediates this relationship. Additionally, both the Sobel test and bootstrapping analyses were employed to verify and validate the mediating relationship.

The study demonstrates that globalization constitutes a crucial determinant of (un)employment rates in South Africa. The study shows that entrepreneurial development, specifically in the context of established business ownership, but not total early-stage entrepreneurial activity, exhibits an inverse relationship with unemployment rates. Moreover, it was observed that the positive impact of globalization on entrepreneurial development in South Africa becomes evident as SMEs advance to the established stage.

The study's concentration on South Africa constrains the applicability of the results to other nations.

Based on the findings of this study, it is essential for emerging economies, such as South Africa, to take measures to foster a robust entrepreneurial ecosystem that can aid in the growth and international competitiveness of young SMEs.

To the best of the authors' knowledge, this study represents the first endeavor to analyze the potential impact of entrepreneurial development, as measured by both nascent and mature SMEs, on the correlation between globalization and unemployment.

The purpose of this study is to analyse numerous aspects affecting residential property price in Malaysia against macroeconomics issues such as gross domestic product (GDP), exchange rate, unemployment and wage.

The hedonic pricing model has been adopted as econometric model for this research to investigate the relationship between residential property price against macroeconomics indicator. The data for residential property price and macroeconomic variables were collected from 1991 to 2019. Multiple linear regression had been adopted to find the relationship between the dependent and independent variables.

The result shows that the GDP has a significant positive impact on residential property price, while exchange rate has no significant impact although it was positive. In addition, the unemployment rate has a significant impact on the residential property price and has a negative relationship. Similar to the wage that shows the negative relationship with residential property prices. Moreover, during the pandemic COVID-19 in Malaysia, this research shows a more transparent view of the relationship between residential property price and the macroeconomic issues of GDP, exchange rate, unemployment and wage.

The findings of this research found that macroeconomics issue cannot be eliminated due to Malaysia is a developing country, and there will always be an issue that will happen, but the issues can be reduced to maximise the advantages, e.g. during COVID-19, the solution to fight against COVID-19 were crucial and weaken the macroeconomics issues.

This study aims to examine how the starting of business by females can be promoted by assessing critical levels of microfinance institutions (MFIs) penetration that policymakers must endeavor to maintain and/or attain in order for female unemployment not to represent a constraint in the doing of business. A constraint in doing business is understood in terms of the procedure that a woman has to go through to start a business.

The focus of the study is on 44 countries in Sub-Saharan Africa for the period 2004–2018, while the empirical evidence is based on interactive quantile regressions.

The following findings are established. The validity of tested hypotheses is exclusively apparent in the lowest and highest quantiles of the conditional distribution of the procedure women have to go through to start a business. MFI penetration levels needed to reverse the unfavorable incidence of female unemployment in doing business are provided. These are minimum MFIs penetration thresholds that are required in order for female unemployment not to negatively affect the procedure that a woman should go through to start a business.

The study complements the extant literature by assessing critical microfinance penetration levels that are needed to promote female doing of business, contingent on existing levels of female doing of business.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.

The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.

Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.

The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338

This literature review aims to assess the current research on healthcare job availability and skilled professionals. The objective of this research is to identify challenges caused by the imbalance between healthcare service demand and qualified professionals and propose potential solutions and future research directions.

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed as the guiding framework for conducting this review. A qualitative research design analyzed 38 peer-reviewed, evidence-based research works from 50 journal publications. Inclusion criteria focused on empirical studies, observational research and comprehensive reviews published within the last ten years. Thematic and discourse analysis categorized themes and factors explored in selected publications.

The findings highlight significant challenges in the healthcare sector regarding job availability and skilled professionals. Developed countries face understaffed healthcare facilities, resulting in increased workloads and compromised care. Developing countries experience high rates of unemployment among healthcare graduates due to limited resources and mentorship.

Improving educational infrastructure, expanding training opportunities and increasing healthcare investments are crucial for nurturing a skilled workforce. Implementing effective retention policies, fostering international collaborations and addressing socioeconomic determinants can create a sustainable job market.

The healthcare sector faces critical challenges in balancing job availability and skilled professionals. Strategic solutions are proposed to create a sustainable and equitable healthcare workforce. By implementing recommendations and conducting further research, access to quality healthcare and global public health outcomes can be improved.

This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.