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The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The purpose of this study is to analyse the gender wage gap (GWG) in Spain adopting a labour market segmentation approach. Once we obtain the different labour segments (or idiosyncratic labour markets), we are able to decompose the GWG into its observed and unobserved heterogeneity components.

We use the data from the Continuous Sample of Working Lives for the year 2021 (matched employer–employee [EE] data). Contingency tables and clustering techniques are applied to employment data to identify idiosyncratic labour markets where men and/or women of different ages tend to match/associate with different sectors of activity and occupation groups. Once this “heatmap” of labour associations is known, we can analyse its hottest areas (the idiosyncratic labour markets) from the perspective of wage discrimination by gender (Oaxaca-Blinder model).

In Spain, in general, men are paid more than women, and this is not always justified by their respective attributes. Among our results, the fact stands out that women tend to move to those idiosyncratic markets (biclusters) where the GWG (in favour of men) is smaller.

It has not been possible to obtain remuneration data by job-placement, but an annual EE relationship is used. Future research should attempt to analyse the GWG across the wage distribution in the different idiosyncratic markets.

Our combination of methodologies can be adapted to other economies and variables and provides detailed information on the labour-matching process and gender wage discrimination in segmented labour markets.

Our contribution is very important for labour market policies, trying to reduce unfair inequalities.

The study of the GWG from a novel labour segmentation perspective can be interesting for other researchers, institutions and policy makers.

In this research, we explore the dynamics among measures of income inequality in the USA, male and female unemployment rates, and growth in government transfer using time series data.

This research adopts a macro-econometric approach to estimate a structural VAR model using time series data.

Our structural impulse responses found that growth in government transfer increases unemployment rates for both males and females. Female income inequality declines with increased government transfer. When the female income ratio rises, we observe that government transfer outlays fall over the forecast horizon. Variance decomposition finds that growth in government transfers is impacted by the male unemployment rate relatively more than the female unemployment rate. This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research investigates the dynamics among income inequality, government transfer, and unemployment rates. There is a dearth of research articles that adopt a macro-econometric in this area.

This article employs a panel vector autoregression (PVAR) model to examine the relationship between digital financial inclusion (DFI), economic growth (EG), and gender equality (GE) across different levels of financial development.

Based on the current financial development dynamics, this study applies the PVAR method to two groups of countries: the first group represents the high financial development group, and the second group represents the low financial development group, during the period from 2015 to 2021.

The findings from impulse response functions reveal that digital financial inclusion fosters economic growth in nations with advanced financial systems, while simultaneously mitigating gender inequality. Conversely, in countries with less developed financial infrastructures, digital financial inclusion stimulates economic growth but exacerbates gender disparities. Moreover, the variance decomposition analysis indicates that the linkage between economic growth, digital financial inclusion, and gender inequality is more intertwined in countries with limited financial development than in those with well-established financial systems.

Effective deployment of new technologies relies heavily on technological infrastructure. This policy focuses on constructing and developing information technology infrastructure to create favorable conditions for the implementation of new DFI technologies. This study also emphasizes promoting equitable education and training by ensuring that both women and men have equal opportunities to access quality education and training. This may involve investing in early childhood education, providing access to primary education, and offering scholarships to women in technology, science, and engineering fields.

Tourism, Technology and Climate Change: The tourism industry is indispensable both for its socio-cultural offerings and its profound economic implications. The economic multiplier effects inherent in the drivers of tourism can stimulate the regional economy even before these areas emerge as tourism meccas. While vast amounts of research have detailed tourism's overarching significance, there is an evident void in understanding its multifaceted impacts, particularly where technological advances, environmental performance (EP) and economic benefits converge. A thorough examination of 907 research records led to this chapter, which identifies these gaps by referencing nine observational and 11 intervention studies. Achieving a Cohen's kappa value of 0.75, the authors note a strong consensus among reviewers, adhering to Cohen's (1940) standards. The findings from the first quarter highlight several areas within the tourism industry that have been under-researched. Particularly, the integration of technology, from ATM infrastructures enhancing tourist financial experiences to digital platforms elevating traveller education and awareness, and tech-driven solutions addressing demographic and ethical considerations in tourism, remains insufficiently explored. Additionally, the authors recognise an existing gap in knowledge regarding the nexus between tourism development and its climatic repercussions, especially before tourism ventures are fully realized. This chapter aims to channel future research into these lesser-trodden areas, fostering a comprehensive grasp of tourism's evolution in the face of rapid technological advancements and its interplay with environmental shifts.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate money, to contribute effort, the feeling of belonging in the party network and social trust in the party network.

In this article, we study how different extra-parliamentary online and offline activities are associated with in-party commitment amongst political party members from the six largest Finnish parties. We especially delve into the differences between members of the Finnish parties.

We found that extra-parliamentary political activity, including connective action through social media networks and collective action through civic organisations, is highly associated with members’ in-party commitment. Additionally, members of the newer identity parties more effectively utilised social media networks, whilst the traditional interest parties were still more linked to traditional forms of extra-parliamentary political action.

By employing the sociological network theory perspective, the study contributes to ongoing discussions surrounding the impact of social media on political participation amongst party members, both within and beyond the confines of political parties.

Young graduates in Morocco are encountering an increasingly challenging labor market environment. Confronted with intense competition, job insecurity, and unclear career trajectories, many find themselves in low-skilled positions despite possessing relevant qualifications. This issue is particularly pronounced among vocational training graduates, who experience professional downgrading at a rate three times higher (33.6%) compared to their peers from general education (11.6%) (HCP, 2018). Our study aims to investigate professional downgrading among young vocational training graduates in Morocco, focusing on the factors contributing to this phenomenon and identifying potential solutions to address it.

Our study is based on the insertion and career path survey conducted by the Department of Professional Training with graduates of professional training programs in Morocco. For this edition, the survey was conducted in 2020, encompassing all 31,498 graduates of the 2016 professional training programs. The Heckman self-selection model is employed to analyze and explore various dimensions of downgrading. Factors such as gender, age, marital status, parental education, and the choice of vocational training field are scrutinized to understand their influence on downgrading.

The study reveals several key findings: Women exhibit a lower probability of professional downgrading compared to men. Young graduates are more vulnerable to downgrading, emphasizing the necessity for career guidance and mentorship programs to facilitate their entry into the job market. Marital status plays a role, with married individuals having a higher likelihood of downgrading. Parental education, particularly that of mothers, proves critical in preventing subjective downgrading of vocational training graduates, highlighting the need for adult literacy and education programs. The effectiveness of the National Agency for the Promotion of Employment and Competencies (ANAPEC) programs in preventing downgrading among vocational training graduates is questioned, suggesting the need for program revisions tailored to this population. The choice of vocational training field significantly impacts downgrading, with graduates of technical training programs experiencing advantages. This emphasizes the importance of diversifying training fields and aligning them with market demands.

This study provides valuable insights into the phenomenon of professional downgrading among young vocational training graduates in Morocco. The findings emphasize the need for targeted policy interventions. Recommendations include supporting young graduates, reassessing programs offered by the ANAPEC, and enhancing technical training to better align with the evolving demands of the labor market.

Research suggests the hotel industry has grown to integrate corporate social responsibility (CSR) programs towards addressing issues relating to the sustainable development goals (SDGs). Nevertheless, how the progression of research has influenced the field of CSR and the SDGs remains unexplored. This paper aims to address the knowledge gap.

The research is based on a review of 230 papers from Scopus Indexed Journals – both mainstream and specialty. A content analysis was conducted to identify the major themes and the evolution of CSR research in the hotel industry.

Recent CSR research has tended to shift towards issues such as CSR communication and reporting from its earlier focus on the perceptions and practices of CSR. The SDGs, in general, and environmental sustainability, in particular, remain on the periphery of hotel industry’s CSR initiatives. This raises concern about the ability of CSR programs to facilitate the SDGs by 2030. This study highlights that both stakeholders (e.g. consumers, employees) and business forces (e.g. financial bottom line) can shape the hotel industry’s CSR strategies in contributing to the SDGs and greater sustainability.

The research advances the CSR and sustainability literature by undertaking a comprehensive review of business research on CSR in the hotel industry focusing on the SDGs, and advancing and facilitating discussion on existing knowledge in this field and how the field can be further developed.