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The main aim of this study is to investigate the role of fathers and mothers in the intergenerational educational persistence for sons and daughters under two dimensions that characterize the clusters of countries: redistributive policy and governance.

Data from the Global Database of Intergenerational Mobility (GDIM), hierarchical cluster analysis on principal components and panel regression are used in this study to estimate intergenerational educational correlation and to investigate its determinants related to the parents’ and descendants’ education variables in 93 countries grouped in four clusters. The empirical analysis is differentiated by gender combinations of parents and descendants.

In the clusters of countries characterized by high inequalities and poor governance, our findings show that the role of the fathers is stronger than that of the mothers in educational transmission; fathers and mothers are more influential for the daughters rather than for the sons; parental educational privilege is the main driver of intergenerational educational persistence; there is an inverse U-curve in the association between educational inequality of the parents and educational correlation for the sons. Differently, in the countries characterized by high income, low redistributive conflict and better governance, the role of the mothers is stronger and education mobility for the daughters is higher than that for the sons.

The authors’ results remark on the importance of social welfare policies aimed to expand a meritocratic public education system including schooling transfers for lower social class students and narrowing the gender gap in educational mobility between daughters and sons. Social welfare policies should also be oriented to spread high quality child care systems that help to foster greater women equality in the labor market, because the strength of educational persistence depends on the position of the mother in the economic hierarchy.

The distinctiveness of the paper can be found in the fact that this study investigates the parental role differentiating by gender and coupling hierarchical cluster analysis on principal components with panel regression models. This allows us to have a sample of 93 countries aggregated in four groups defined in two dimensions: redistributive policy and governance. Amongst the determinants of educational transmission, we consider not only education’s years of the parents but also other determinants, such as educational inequality and privilege of the parents. We also identify the effects of investment in human capital and educational inequalities for the descendants on education mobility.

The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

This study employs firm-level data to evaluate how the knowledge economy impacts the financing constraints of businesses across 106 low- and middle-income nations, focusing on the influence of technological transformation on corporate financing choices.

The research centers on privately held, unlisted firms and examines the distinct effects of knowledge at both the within-country and between-country levels using a panel dataset. Rigorous sensitivity and endogeneity analyses are conducted to ensure the reliability of the findings.

The findings indicate that greater levels of the knowledge economy correlate with reduced financing constraints for firms. However, this effect varies depending on the location within a country and across different geographical regions. Firms situated in larger urban centers and more innovative regions reap the most significant benefits from the knowledge economy when seeking external funding. Conversely, firms in smaller cities, rural areas and regions characterized by structural and institutional inefficiencies in knowledge generation experience fewer advantages.

The impact of knowledge exhibits variability not only within and among countries but also between poor and affluent developing nations, as well as between larger and smaller countries. The knowledge effect on firms' access to external finance is influenced by factors such as financial openness and development, educational quality, technological absorption capabilities and agglomeration conditions within each country.

The aim of this paper is to analyse the spillover effects of microcredit on the economy of Ecuador, with a particular focus on its potential as a poverty alleviation mechanism.

To address our research questions, we take into account the distance between cantons (Ecuador’s own administrative distribution) by adopting a spatial autoregressive (SAR) model. To this end, a database will be constructed with macroeconomic information about the country, broken down by canton (administrative division of Ecuador), and in a 2019 cross section, with a total of 1,331 microcredit operations in all 221 of Ecuador’s cantons.

We find a positive effect of microcredit on these neighbouring regions in terms of wealth generation.

We acknowledge that this study is limited to Ecuadorian cantons. Nonetheless, it is crucial to emphasize that focussing on an under-represented developing country like Ecuador adds significant value to the research.

Facilitating access to microcredit is one of the main solutions to address the goals proposed in the sustainable development goals (SDGs).

Microcredit activity contributes to the creation of value and wealth in Ecuador, exerting a spillover effect in neighbouring areas that can generate positive multiplier effects and alleviate poverty. For all of the above reasons, our proposal for the country is to support and promote microcredit as one of the main solutions to address the goals proposed in the SDGs.

The novelty of this study lies in the use of spatial econometrics to observe the indirect effects of microcredit on the regions bordering the canton in which it was issued, thus examining the spatial effects of microcredit on wealth distribution.

Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

Recent scholarship has explored higher education institutions’ (HEIs) role in transitioning to a sustainable society, but empirically, questions remain regarding their impact on the sustainability of surrounding areas. This study aims to examine the correlation between HEIs’ sustainability actions and local sustainability performance.

This study uses a linear regression model and principal component analysis to examine the sustainability performance of 105 US metropolitan statistical areas (MSAs) using the US cities sustainable development goal (SDG) index, which hosts 427 HEIs known for sustainability efforts. The weighted HEI sustainability performance score is calculated based on the QS sustainability universities ranking.

The correlation between MSA and HEI sustainability performance exhibits a mix of positive and negative associations, with individual and interlinked SDGs serving as proxies. These correlations encompass a wide range of goals, from economic aspects of SDG 1, 2, 3, 7, 9, social aspects of SDG10 and 16, to socio-environmental aspects of SDG12.

Further exploration is needed to identify the causal mechanisms behind associations between SDG measures and HEI sustainability performance, whether influenced by the institution, the individual or both.

This study suggests that HEIs are already associated with some aspects of community sustainability, but greater contributions to a broader array of sustainability measures are possible.

The correlation found between HEI sustainability actions and SDG10, 12 and 16 index performance in an MSA highlights a connection between HEIs and the attainment of societal goals.

To the best of the authors’ knowledge, this study is the first to examine the correlation between HEI and MSA sustainability performance in the US through individual and interlinked SDG proxies. It provides novel empirical evidence that demonstrates an association between HEI and some aspects of community sustainability performance.

The study aims to delve into the influence of tourism on the happiness of city residents, grounded in the overarching concept of livability. It posits that prioritizing residents’ happiness is crucial for effectively addressing cities’ challenges in balancing development and distinctiveness. The study pursues three primary objectives: first, establishing a potential correlation between city tourism and residents’ happiness; second, examining the contributing factors to this correlation and third, identifying potential mediators that influence the connection between tourism development and residents’ happiness.

Using a quantitative single-case design and partial least square analysis, the study underscores the intricate nature of various tourism development components. It specifically explores the roles of cognitive flexibility and social comparison in shaping the relationship between city tourism and happiness.

The findings make a distinctive contribution by revealing that not all tourism domains contribute positively to happiness. Furthermore, it sheds light on how tourism development impacts the emotional and cognitive dimensions of happiness, emphasizing the adverse effects of inequality and feelings of insecurity.

The study acknowledges certain constraints, including its employment of a cross-sectional design, the issue of generalizability, potential sampling bias and the reliance on subjective measurements when evaluating constructs like happiness and satisfaction with life. Using self-reported data introduces susceptibility to social desirability bias and individual perceptual differences, potentially resulting in measurement inaccuracies. Nevertheless, despite these limitations, the study’s findings offer valuable insights that contribute to both theoretical advancement and the realm of urban management.

The findings elucidated through the mediation analyses conducted for hypotheses three to seven shed light on the significant roles played by mental adaptation and social comparison mechanisms in shaping individuals’ happiness. These insights substantially enhance our understanding of this field. Particularly, the dimensions of social and environmental impact within tourism appear to counterbalance the positive effects stemming from the economic and cultural aspects. This suggests a scenario where an excessive focus on tourism development could potentially undermine the overall livability of the city. These outcomes further indicate the necessity for proactive interventions by destination managers. Their efforts should be directed toward enhancing the environmental and social domains, aiming to reinvigorate the sense of community among residents, which appears to be gradually waning.

The outcomes of this study emphasize the utmost significance of prioritizing residents’ happiness above mere considerations of economic growth when formulating efficacious strategies for tourism. By concentrating on the happiness of the local population, a harmonious resonance is established with Sustainable Development Goal 11, which advocates for the creation of habitable cities founded upon the principle that “a city that is not good for its citizens is not good for tourists.” This alignment underscores the interconnected nature of residents’ happiness and the sustainable development of tourism. Moreover, residents’ happiness plays a pivotal role in addressing the challenge that cities face in harmonizing growth and their uniqueness, ensuring competitiveness and sustainability.

The research underscores the need for a people-oriented perspective in urban planning and tourism development initiatives. The study identifies diverse factors impacting residents’ happiness in city tourism, highlighting the complex interplay of environmental, cultural and socioeconomic elements. It emphasizes income’s role but underscores nonmaterial factors and individual preferences. Overall, the study offers timely and valuable insights into the intricate connection between tourism development, residents’ happiness, living conditions and human perception, guiding urban planners and stakeholders.

Despite their pivotal role in classroom social dynamics, teachers are not always aware of, and/or do not know how to respond to, bottlenecks in these dynamics. This study investigated the effectiveness of the Social Classroom Dynamics Intervention with Lesson Study (SKILS, acronym of the Dutch program name) in supporting teachers with regards to improving their classrooms' social dynamics.

A sample of Dutch secondary school classrooms was divided into five SKILS classrooms (n = 86; 53.5% boys; M_age-T0 = 13.62 years and SD = 1.02 years) and nine control classrooms (n = 156; 50.6% boys; M_age-T0 = 13.55 years and SD = 0.89 years). Involvement in bullying and social cohesion was assessed pre- and post-intervention using student peer reports. Teachers of SKILS classrooms formed SKILS teams of five teachers (N = 25; 60% male; M_age-T0 = 42.45 years and SD = 12.81 years; teacher's experience: M_T0 = 11.35 years and SD = 8.36 years). Teachers were interviewed post-intervention.

While SKILS had little effect on classroom bullying dynamics, it had a positive effect on student social cohesion. Teachers indicated a learning effect with regard to identifying bottlenecks within classroom dynamics and felt more competent to intervene in response to bottlenecks due to SKILS.

The findings suggest that teachers can successfully impact classroom social cohesion by increasing their knowledge of classroom dynamics and working in Lesson Study (LS) teams with colleagues to develop tailored interventions for these dynamics.

The purpose of our study is to study the impact of chief executive officer (CEO) optimism and narcissism on the company's capital structure.

(1) The authors opt for regression, machine learning and text analysis to explore the impact of narcissism and optimism on the capital structure. (2) We analyze CEO interviews and employ three methods to evaluate narcissism: the dictionary proposed by Anglin, which enabled us to assess the following components: authority, superiority, vanity and exhibitionism; count of first-person singular and plural pronouns and count of CEO photos displayed. Following this approach, we were able to make a more thorough assessment of corporate narcissism. (3) Latent Dirichlet allocation (LDA) technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs and to find differences between the topics of interviews and letters provided by narcissistic and non-narcissistic CEOs.

Our research demonstrates that narcissism has a slight and nonlinear impact on capital structure. However, our findings suggest that there is an impact of pessimism and uncertainty under pandemic conditions when managers predicted doom and completely changed their strategies. We applied various approaches to estimate the gender distribution of CEOs and found that the median values of optimism and narcissism do not depend on sex. Using LDA, we examined the content and key topics of CEO interviews, defined as positive and negative. There are some differences in the topics: narcissistic CEOs are more likely to speak about long-term goals, projects and problems; they often talk about their brand and business processes.

First, we examine the COVID-19 pandemic period and evaluate how CEO optimism and pessimism affect their financial decisions under specific external conditions. The pandemic forced companies to shift the way they worked: either to switch to the remote work model or to interrupt operations; to lose or, on the contrary, attract clients. In addition, during this period, corporate management can have a different outlook on their company’s financial performance and goals. The LDA technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs. Second, we use three methods to evaluate narcissism. Third, the research is based on a set of advanced methods: machine learning techniques (random forest to reveal a nonlinear impact of CEO optimism and narcissism on capital structure).

In this study, we drew on the theories of social exchange and social learning and hypothesized that the online social capital (SC) and offline SC of social networking affect the online self-disclosure (OSD) of individuals through social self-efficacy (SSE).

After retrieving 514 valid questionnaires, we used structural equation modeling to analyze the data.

The results indicated that the users’ SSE affected their OSD, and that both online and offline bridging and bonding SC increased their SSE. However, online bonding SC directly affected their OSD, whereas online bridging SC did not considerably affect their OSD. Given these findings, we presented both theoretical and practical implications to elucidate SSE and OSD behavior from the perspective of online and offline bridging and bonding SC.

In this study, we drew on theories of social exchange and social learning to examine the effects of online and offline bridging and bonding SC on users’ SSE and OSD on SNSs. Given the importance of SC and SSE in social relationships and the effects of OSD on SNSs, our goal was to provide SNS marketers with a thorough understanding of how to facilitate SSE and OSD from the perspective of online and offline bridging and bonding SC.