Research on zakat has captured the attention of scholars since 1981, exhibiting an increasing trend in publications and citations. This trend presents an opportunity for the author to delve into zakat research. The primary aim of this study is to dissect 10 years of zakat research, spanning from 2013 to 2022, with a focus on evaluating past achievements, current research patterns, and potential future research directions. Utilising bibliometric analysis as the primary tool, this study has formulated seven research questions derived from the primary objective. Key findings indicate a consistent upward trajectory in both publication and citation rates over the past decade, with 2013 being a pivotal year. Notably, Malaysia, Indonesia, and Saudi Arabia emerged as the top three countries actively contributing to zakat research during this period. This study further outlines eight contemporary research trends, exploring various facets of zakat over the past decade. Additionally, this study identifies four prospective areas in zakat for future scholars to explore. This study’s outcomes offer three significant contributions: 1) signalling to scholars that zakat research continues to burgeon; 2) providing inspiration and ideas for current scholars; and 3) motivating future scholars to embark on research ventures in untapped areas within the realm of zakat.

Latin America is increasingly contributing to scientific research on leadership, although less than other regions. What are the predominant paradigms on leadership within the scientific community in Mexico? The article reviews doctoral dissertations on leadership from the National Autonomous University of Mexico (UNAM) and the Anahuac University of Mexico (UA) defended before 2021. The findings highlight that 1) the number of doctoral dissertations has grown from 2016 onwards, especially in educational leadership. 2) In both universities a “functionalist” paradigm prevails, based on the transformational leadership model. 3) Two other leadership paradigms are present, referred to in this article as ‘political’ and ‘humanistic’. 4) These three paradigms have their characteristics and preferences in terms of research methodology, language, and reference authors. 5) The use of a paradigm is associated with the type of faculty rather than the type of university (public or private): in business faculties the functionalist paradigm predominates, in education faculties the humanist paradigm, and in political science or communication faculties the political paradigm. In conclusion, it is recommended to confirm the exploratory result obtained and to promote the dialogue between leadership paradigms.

A comprehensive survey was conducted in 2012 and 2020 to assess the financial culture of Hungarian higher education students. The findings revealed that financial training effectiveness had not improved over time. To address this, a conative examination of financial personality was initiated by the Financial Compass Foundation, which gathered over 40,000 responses from three distinct age groups: Children, high school students, and adults. The study identified key behavioral patterns, such as excessive spending and financial fragility, which were prominent across all age groups. These results informed Hungary’s seven-year strategy to enhance financial literacy and integrate economic education into the National Core Curriculum. The research is now expanding internationally with the aim of building a comparative database. The study’s main findings highlight the widespread need for improved financial education, with more than 80% of adults demonstrating risky financial behaviors. The implications of these findings suggest the importance of early financial education and tailored interventions to foster long-term financial stability. The international expansion of this research will allow for the examination of country-specific financial behaviors and provide data-driven recommendations for policy development.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.

Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.