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The study aims to examine the impact of intellectual and social capital in funding businesses.

The study made use of fixed-effects panel data models with a sample of 142 countries from the five continents during the period 1998–2018.

It was found that human capital (HC), relational capital, structural capital and social capital play a role in investors’ decisions to fund a business. The study revealed that investors’ funding decisions in low human development index countries are based mainly on education, while those in high human development index countries are based mainly on the creativity component of HC and on relational, structural and social capital.

The study needs to be replicated using firm-level data within each country. Moreover, the search for new proxies for intellectual and social capital (although the list of variables is exhaustive) both at the country and firm level, constitutes an interesting avenue for future research.

Countries should pay attention to intellectual and social capital to encourage business activity. In particular, low human development countries should strengthen HC, such as the school enrollment rate, with early entrepreneurial training and increase research and development investments, while high human development countries should continue to foster strategic alliances, protect intellectual property and maintain or increase the level of trust in the country.

The study contributes to literature by being the first to explore such a variety of intellectual and social capital variables from a country-level perspective.

El estudio tiene como objetivo examinar el impacto del capital intelectual y social en la financiación de las empresas.

Utilizamos modelos de datos de panel de efectos fijos con una muestra de 142 países de los cinco continentes durante el periodo 1998-2018.

Encontramos que el capital humano (CH), el capital relacional, el capital estructural y el capital social juegan un papel en las decisiones de los inversionistas para financiar un negocio. Encontramos que las decisiones de financiamiento de los inversionistas en los países con bajo índice de desarrollo humano se basan principalmente en la educación, mientras que las de los países con alto índice de desarrollo humano se basan principalmente en el componente de creatividad del CH y en el capital relacional, estructural y social.

Sugerimos replicar el estudio utilizando datos a nivel de empresa dentro de cada país. Por otra parte, la búsqueda de nuevos indicadores de capital intelectual y social (aunque nuestra lista de variables es exhaustiva) tanto a nivel de país como de empresa, constituye una vía interesante para futuras investigaciones.

Los países deben prestar atención al capital intelectual y social para fomentar la actividad empresarial. En particular, los países con bajo desarrollo humano deberían fortalecer el CH, como la tasa de matriculación escolar, con una formación empresarial temprana y aumentar las inversiones en investigación y desarrollo, mientras que los países con un alto nivel de desarrollo humano deberían seguir fomentando las alianzas estratégicas, proteger la propiedad intelectual y mantener o aumentar el nivel de confianza en el país.

El estudio contribuye a la literatura al ser el primero en explorar tal variedad de variables de capital intelectual y social desde una perspectiva a nivel de país.

The literature currently offers only fragmentary insights into the research on the relationship between employee emotions and human resource management (HRM). Therefore, further research is essential to bridge this knowledge gap. Our study aims to identify the mediating effects of positive employee emotions and exhaustion in the relationship between HRM and employee engagement.

Drawing on the literature review findings, a conceptual model was formulated to illustrate the relationship between HRM, employee emotions and engagement. A confirmatory analysis was conducted using structural equation modelling (SEM CFA) on a sample of 1,000 employees to validate the proposed model. The data were collected in 2021, with a particular emphasis on exploring the indirect influence of HRM on engagement through positive employee emotions and exhaustion.

The quantitative research aimed to test a model depicting the relationship between HRM and employee emotions. The findings indicate the robust effect of HRM on positive employee emotions and exhaustion. The authors observed significant variation in the level of impact depending on the size of the organisation (stronger in large firms) and the sector (stronger in the public sector).

The study bridges the gap in our understanding of the link between HRM and employee emotions. It would be advisable to further explore the specific impact of individual HRM practices on both positive and negative employee emotions. It is worth extending the scope of future research to explore components of the investigated constructs as well as mediators and moderators of the relationship between HRM and employee emotions.

Findings in the literature indicate leading financial analysts attract high levels of market attention and provide more accurate earnings forecasts prior to becoming all-star analysts. Furthermore, these analysts significantly impact the investment decisions of other market participants and thus the market price of assets. Therefore, this study examines the information role of leading financial analysts and identifies two significant conclusions. First, the positive outcomes of these analyst leaders are more informative and attract more followers. Second, informational herding by followers of these analysts is not as naïve as suggested in previous studies, as followers who smartly use information from analyst leaders tend to perform better. We also find that analysts who practice smart learning by studying and selectively employing analyst-leader decisions achieve better career outcomes.

The authors analyzed the evolution of working from home (WFH) within industries in 12 European countries in the period 2008–2017 and studied its relationship with information and communication technologies (ICT).

The authors used data from the European Union Labour Force Survey (EU-LFS) to document the trends and levels of WFH within industries in 12 European countries. The authors further used the EU-KLEMS database and a difference-in-difference approach to study whether the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less.

The authors show that WFH has increased almost everywhere and that there is significant heterogeneity across industries. The authors provide evidence that the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less. This result also holds within age, gender and occupation groups. While the authors find no significant differences among gender and occupation groups, the positive association between the fall in ICT prices and WFH increases with age.

This paper has two main contributions: First, it reports that WFH has increased in European countries in the period 2008–2017. Second, it provides new explorations about the relationship between ICT and WFH by using the price variation of ICT.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

This article aims to analyse the trait emotional intelligence (TEI) of business students of various programmes. This study aims to answer the question, to what extent these future leaders are uniformly equipped with essential emotional intelligence competences, necessary in the VUCA world.

The Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure TEI of 120 business students. Spearman's and Tau–Kendall's rank correlation coefficients show the strength of the correlation between age and TEI level. The non-parametric Mann–Whitney U test was employed to evaluate the consistency of TEI-level distributions in selected subgroups of respondents.

Future business leaders and management specialists are unequally prepared to manage teams and organizational change effectively. Their TEI distribution is significantly different regarding the type of programme of study. Students of “social fields” (Management, Communication and Psychology in Business) show higher TEI than students of “analytical fields” (Economics, Finance and Accounting, Logistics). Master's students are characterized by higher TEI compared to undergraduates. However, there were no statistically significant differences in TEI between: full-time and part-time, female and male, as well as working and non-working students.

The results provide valuable guidance for organizations recruiting junior managers and for business universities.

This research was based on a well-established concept of emotional intelligence using a reliable research tool. The obtained results complement the existing research on TEI of various professional groups and provide a precious reference point for future, more in-depth analyses of TEI.

The Organization for Economic Cooperation and Development (OECD) countries are facing unprecedented challenges related to climate change and population aging. The purpose of the analysis is to explore the relationship between population aging and environmental degradation, accounting for human capital, using a sample of 19 OECD countries over the period 1980–2019.

On the empirical methodology, the analysis uses panel estimators with heterogenous coefficients and an error structure that takes into consideration cross-country heterogeneity and cross-sectional dependence for a panel of 19 OECD countries over the period 1980–2019. To examine the relationship between population aging and environmental degradation, the authors employ two alternative measures of environmental degradation that is energy consumption and CO2 emissions in metric tons per capita. Concerning the regressors, the authors account for two alternative aging indicators, namely the elderly population and the old-age dependency ratios to confirm robustness.

The analysis provides evidence that population aging and human capital development (IHC) lead to lower energy consumption in the OECD sample. Overall, the growing number of elderly people in the OECD seems to act as a mitigating factor for energy consumption. The authors view these results as conveying the message that the evolution of population aging along with channeling government expenditures towards human capital enhancement are important drivers of curbing energy consumption and ensuring environmental sustainability. The authors' research is of great significance for environmental policymakers by illuminating the favorable energy consumption patterns that population aging brings to advanced economies.

The main limitation of this study concerns data availability. Future research, and subject to greater data availability in the future, could dig deeper into understanding the dynamics of this complex nexus by incorporating additional control variables. Similarly, the authors focus on aggregate renewable energy consumption, and the authors do not explicitly model the sources of renewable energy (wind, hydropower, solar power, solid biofuels and other). Additional analysis of the breakdown of renewable energy sources would be insightful – subject to data availability – especially for meeting the recently agreed new target of 42.5% for European Union (EU) countries by 2030. A deep transformation of the European energy system is needed for the EU to meet the target. Finally, extending the model to include a range of non-OECD countries that are also experiencing demographic transformations is a promising avenue for future research.

To the best of the authors' knowledge, this study is the first to examine the effects of population aging and human capital on environmental degradation using a broad set of OECD countries and advanced spectrum estimation methods. Given cross-sectional dependencies and cross-country heterogeneity, the authors' empirical results underline the importance of cross-OECD policy spillovers and knowledge diffusions across the OECD countries. The new “energy culture” calls for concerted policy action even in an aging era.

This paper investigates the two-way relationship between foreign direct investment (FDI) inflows and higher education across 36 Organisation for Economic Co-operation and Development (OECD) countries for 1998–2019 periods. To demonstrate this relationship, the authors take into account the total number of graduates as well as the number of graduates from different fields. Accordingly, the authors gathered graduates in four groups which are education, social sciences, technical sciences (tech) and health. In addition to investigating two-way relationship between FDI and graduates, the authors also examined the contribution of primary and secondary level education to FDI.

The authors use two models to investigate the bidirectional relationship between FDI inflows and graduates from four fields. In the first model, the dependent variable is FDI inflows, and in the second model, graduates from each field are the dependent variable. To investigate the dual relationship, the authors employ ordinary least squares (OLS) and two-step system generalized method of moments (GMM) developed by Arellano Bover (1995) and Blundell Bond (1998).

For the first model, the results show that secondary level and higher education have a positive impact on FDI. In terms of graduates by fields, it is seen that education and health graduates contributed the most to FDI. For the second model in which the authors analysed the effect of FDI on total graduates and graduates from different fields, the authors find that FDI positively affects the number of graduates from all fields, and the strongest effect is on graduates from the social science field.

Based on the results, the authors can say that well-educated people promote FDI inflows to OECD countries, and FDI is also a driving force in raising highly educated people. So, the authors think that the results will help design higher education policies in accordance with FDI and higher education connection.

To the best of the authors’ knowledge, this paper is the first to examine the impact of FDI inflows on graduates by fields and also to investigate the impact of graduates by fields on FDI.

This theoretical study aims to clarify the (a priori) ambiguous effect of homeownership on unemployment. In general, in fact, homeownership discourages job mobility, but homeowners are less likely to be unemployed than tenants, since homeownership would seem to be positively related to human capital.

This study develops a modified version of the benchmark theoretic model of the labour market – the well-known “equilibrium unemployment theory” – where homeownership affects both the “Beveridge Curve” (BC, by means of job immobility) and the “Job Creation Condition” (JCC, by means of human capital).

The general result is that an increase in homeownership increases unemployment. Therefore, policymakers could encourage job mobility, before facilitating homeownership. This policy implication, however, may not apply in the case of high inflation and/or low nominal interest rate, and when the job destruction rate depends on the homeownership rate.

The model studies the steady-state equilibrium of the labour market, so the policy implications only relate to the long-run. The model, therefore, does not consider the short-run effects of homeownership on unemployment (which may differ from the long-term results).

The model suggests a public policy characterised by large investment in rail lines and subsidised commuter fares. By promoting a more efficient allocation of workers across regions (and, thus, job mobility), indeed, this policy can be a good way to increase employment, without harming homeownership.

The practical implication of this model is also a social implication, since it relates to homeownership and housing tenure.

To the best of author’s knowledge, this is the first model that introduces the key role of homeownership in the so-called “Equilibrium unemployment theory”. Precisely, the model uses a modified version of both the BC (which includes the negative effect of homeownership on the overall job search intensity of unemployed workers) and the JCC (which includes the positive effect of homeownership on both the business start-up and the human capital of workers). By comparing these two opposite effects, this theoretical work makes clearer the net effect of homeownership on unemployment.

This study examines the relationship between partners' locus of control and their spouses' domains of job satisfaction (job satisfaction and its domains, personal income and promotion) among Australian couples.

Data were obtained from the Household, Income and Labor Dynamics of Australia (HILDA) Survey. Various estimation strategies including ordinary least squares (OLS), Mundlak approach and instrumental variable (IV) method are used to reveal the relationship between spouse's locus of control and domains of job satisfaction.

To reduce sex heterogeneity, the analysis used in this study is disaggregated by sex. In particular, the findings of this study show that wives' locus of control positively influences husbands' satisfaction with pay and working hours, while there is no relationship between husbands' locus of control and wives' domains of job satisfaction.

The study's findings emphasize the importance of locus of control in couples. A good work–life balance and a healthy marital relationship potentially facilitate positive effects of characteristics from the partner on employees' job satisfaction. Thus, on the organizational level, employers may consider creating a working environment that promotes a healthy marital relationship for their staff, including flexible working schedules, work from home options, family days or family-extended staff events.

This study is the first to reveal the relationship between spousal locus of control and domains of job satisfaction, enriching the current literature on this topic.