Hate speech in higher education institutions is a pressing issue that threatens democratic values and social cohesion. This research explores student perspectives on hate speech within the university setting, examining its forms, causes, and impacts on democratic principles such as freedom of expression and inclusivity. This research is extended to determine the debates and theories elaborated from different perspectives qualitative and quantitative analysis of data collected from 108 participants at Higher Education in Kosovo. From the communication standpoint, analyzing hate speech in the media and social media is key to understanding the type of message used, its emitter, how the message rallies supporters, and how they interpret message. The findings highlight the need for proactive policies and educational interventions to mitigate Research on hate speech in higher education in Kosovo is crucial for fostering social cohesion and inclusivity in its diverse society. Hate speech undermines the academic environment, negatively affecting students’ mental health, learning outcomes, and overall well-being, necessitating efforts to create safer educational spaces. The study aligns with Kosovo’s aspirations for European integration, emphasizing adherence to human rights and anti-discrimination principles. Despite the issue’s significance, there is a lack of empirical data on hate speech in Kosovo’s higher education, making this research vital for evidence-based policymaking. With a youth-centric focus, the study aims to educate and empower young people as future leaders to embrace respect and inclusivity. By addressing hate speech’s local challenges and global relevance, the research supports institutional reforms and offers valuable insights for post-conflict and multicultural societies. Hate speech while fostering a culture of mutual respect and democratic engagement.

This article aims to measure and identify the factors influencing the decision to use Chatbot in e-banking services for GenZ customers in Vietnam through 292 customers. Testing methods: Cronbach’s Alpha trust factor, EFA discovery factor analysis, and regression analysis have shown that 07 factors directly affect GenZ’s decision to use Chatbot. Those factors include (1) Customer attitude; (2) Useful perception; (3) Perception of ease of use; (4) Behavioral control perception; (5) Risk perception; (6) Subjective norms and (7) Trust. On that basis, the article has set out management implications for Vietnamese commercial banks to approach and increase the decision of customers aged 18–24 years in Vietnam.

The proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.

This study is considered one of the few studies that attempted to explore the relationship between exports and foreign direct investment in the Kingdom of Saudi Arabia. The study aims to determine the nature of the relationship between exports and foreign direct investment in the Kingdom of Saudi Arabia during the period between (1990–2023). Employing Ender’s methodology using cointegration and error correction model. The study also relies on data on Saudi exports and foreign direct investment inflows from the World Bank databases. The results indicate the existence of Cointegration between foreign direct investment (FDI) inflows and the Saudi exports in the period (1990–2023), as for the causal relationship between the two variables, the results showed the causal relation between exports and FDI inflows from the direction of exports only, which means that Saudi exports cause FDI inflows in Saudi Arabia, and the study recommends giving more incentives to attract foreign investors in different sector rather than oil sector, besides improving the logistical services which is vital to any investment attraction strategy.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.