Islamic banking is one of the fastest-growing sectors of the financial industry. Several works have been written in this field, but none attempt to learn the entire Islamic banking and financial system. Furthermore, the study could not locate any publications investigating the conceptual and intellectual foundations of this emerging field of inquiry. The current study uses bibliometric methodologies to assess the current state of Islamic banking, financial research, and the upcoming trends. For the people who choose interest-free investments, the current research examines a conceptual research context on Islamic banking and finance at various planning and decision-making stages. One thousand research studies appearing in scholarly journals between 2005 and 2023 were reviewed for the purpose. In order to examine the works on Islamic banking and finance, bibliometric techniques were used, including analysis of citation network, content, co-citation, keyword, and publishing trends. By suggesting thirteen clusters, to enhance research on Islamic banking and finance to help interest-free investors learn more, the goal of the research is to promote the body of knowledge. The field of Islamic banking and finance has grown from a young lot to a prominent teaching and research tool. Investigating and identifying current research trends in this area is crucial. As institutions and society are placing more emphasis on Islamic banking to raise individual citizens’ responsibilities in developing interest-free investing strategies, the findings are crucial to the community of interest-free financiers. Further research urges with the studies not restricted to a thousand researches only.

Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.

Studies show that Fourth Industrial Revolution (4IR) technologies can enhance compliance with COVID-19 guidelines within the parties in the construction industry in the future and mitigate job loss. It implies that mitigating job loss improves the achievement of Sustainable Development Goal 1 (SDG 1) (eliminate poverty). There is a paucity of literature concerning 4IR technologies application and COVID-19 impact on South Africa’s construction industry. Thus, this paper investigates the impacts of the pandemic on the sector and the roles of digital technologies in mitigating job loss in future pandemics. Data were collected via virtual semi-structured interviews. The participants proffered unexplored insights into the impact of the pandemic on the sector and the possible roles that 4IR technology can play in mitigating the spread of the virus within the sector. Findings show that the sector was hit, especially the low-income earners, threatens to achieve Goal 1, despite government institutions’ intervention, such as economic support programmes, health and safety guidelines awareness, and medical facilities. Findings group the emerged impacts into health and safety, environmental, economic, productivity, social, and legal and insurance issues in South Africa. The study shows that technology can be advantageous to improving achieving Goal 1 in a pandemic era due to limited job loss.

This study examines the interplay between eco-friendly behaviour (Eco-FB) at multiple systemic levels, addressing the complexity beyond the scope of single-level models. We propose a comprehensive model incorporating traditional individual, organizational, and relational level concepts and a situational construct exemplified by Bali Island Recognition. This model was tested in Bali Island’s tourism firms through online and offline surveys of 500 tourism-related employees and their gateway communities across Bali Island. The research investigates the differences in pro-environmental conduct between two destinations’ social accountability (DSA) groups categorized as high and low DSA clusters. It further explores how ecological value, green intelligence, DSA, and sustainable travel affect public and private Eco-FB. The findings indicate that green intelligence has a strong positive connection with Eco-FB, and high DSA significantly impacts eco-friendly behaviour. This research enhances our understanding of Eco-FB by presenting a multilevel model incorporating the Bali Island factor, revealing distinctive impact mechanisms for both public and private Eco-FB.

This study investigates the impact of various educational and social factors on the digital skills of vocational education and training (VET) students, emphasizing the significance of continuous skill development in the digital age. Utilizing structural equation modeling (SEM), the paper analyzes data from 382 adult VET students in Greece, examining the effects of Erasmus program participation, daily computer use, educational platforms, and social network engagement on digital competencies. The findings reveal that participation in Erasmus programs and the use of educational platforms significantly enhance students’ digital skills, highlighting the value of international experiences and digital learning tools in VET. Conversely, daily computer use alone does not significantly impact digital skills, suggesting that structured and purposeful digital tool integration is essential for skill development. The study also underscores the positive role of social networks in improving content management skills, advocating for their strategic use in educational settings. These results demonstrate the need for targeted digital literacy initiatives within VET programs to prepare students for modern labor market demands. The research contributes to the theoretical understanding of digital skill acquisition and offers practical insights for educators and policymakers to enhance VET curricula, fostering economic and social progress through improved digital literacy.

Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.