The financial inclusion program in Asia has begun to be carried out intensively, focusing on increasing public access, especially for people who have yet to enjoy banking services. This makes financial inclusion one of the development focuses in the financial sector in various countries, especially in the Asian region. This study compares the financial inclusion level and socioeconomic variables’ influence on financial inclusion in Asian countries in 2010–2022. To compare the level of financial inclusion in several Asian countries, the Index of Financial Inclusion (IFI) analysis method was used, while to examine the relationship between socioeconomic variables on financial inclusion, the Ordinary Least Square (OLS) method was used with an estimation technique, in the Fixed Effects Model approach. The results of this study indicate that, in general, financial inclusion in several Asian countries is mainly influenced by the usability dimension. In addition, only the variable GDP per capita is partially influential. While other variables, namely, the unemployment rate and population in rural areas, significantly influence the financial inclusion index.

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

The Hungarian tourism and hospitality industry has faced serious challenges in recent years. The tourism and hospitality sector has been confronted with severe challenges in recent years. Even after the end of the pandemic, the industry has not seen the expected recovery, as rising inflation, declining discretionary income and a lack of foreign tourists have further hampered the industry. The hotel market in Budapest in particular has been significantly affected by these developments. Despite the difficulties, investors continue to see opportunities in the market. One example is the purchase by a group of real estate investors of an under-utilised leisure centre in District VII, which they intend to convert into a hotel. Our study is part of this project and its primary objective is to define the parameters of the future hotel and analyse the market opportunities and challenges. Our research focuses on the hotel market in Budapest and uses methods such as benchmarking, STEEP and SWOT analyses, as well as four in-depth interviews with key players in the market. The benchmarking examined the operations of hotels in the capital, while the in-depth interviews provided practical experience and insider perspectives. On the basis of the interviews and analyses, the study identifies possible directions for improvement and factors for competitive advantage.

Banana (Musa spp.) productivity is limited by sodic soils, which impairs root growth and nutrient uptake. Analyzing root traits under stress conditions can aid in identifying tolerant genotypes. This study investigates the root morphological traits of banana cultivars under sodic soil stress conditions using Rhizovision software. The pot culture experiment was laid out in a Completely Randomized Design (CRD) under open field conditions, with treatments comprising the following varieties: Poovan (AAB), Udhayam (ABB), Karpooravalli (ABB), CO 3 (ABB), Kaveri Saba (ABB), Kaveri Kalki (ABB), Kaveri Haritha (ABB), Monthan (ABB), Nendran (AAB), and Rasthali (AAB), each replicated thrice. Parameters such as the number of roots, root tips, diameter, surface area, perimeter, and volume were assessed to evaluate the performance of different cultivars. The findings reveal that Karpooravali and Udhayam cultivars exhibited superior performance in terms of root morphology compared to other cultivars under sodic soil stress. These cultivars displayed increased root proliferation, elongation, and surface area, indicating their resilience to sodic soil stress. The utilization of Rhizovision software facilitated precise measurement and analysis of root traits, providing valuable insights into the adaptation mechanisms of banana cultivars to adverse soil conditions.

This study investigates the impact of toll road construction on 59 micro, small, and medium enterprises in Kampar, Pekanbaru, and Dumai cities. The research aims to analyze the economic and environmental effects of infrastructure expansion on businesses’ profitability and sustainability, providing insights for policymakers and stakeholders to develop mitigation strategies to support MSMEs amidst ongoing infrastructure development. Structural equation modeling, spatial environmental impact analysis, and qualitative data analysis using five-level qualitative data analysis (FL-QDA) were all used together in a mixed-methods approach. Data collection involved observations, interviews, questionnaires, and geospatial analysis, including the use of a Geo-Information System (GIS) supported by drone reconnaissance to map affected areas. The study revealed that the toll roads significantly enhanced connectivity and economic growth but also negatively impacted local economies (β = 0.32, R² = 0.60, P-value ≤ 0.05). and the environment (β = 0.34, P-value ≤ 0.05), as 49% of respondents experienced a 50% decrease in profitability. To mitigate the risk of impact, policymakers should prioritize the principle of prudence to evaluate the significance of mitigation policy implementation (β = 0.144, P-value ≥ 0.05). In a nutshell, toll road construction significantly impacts MSMEs’ business continuity, necessitating an innovative strategy involving monitoring and participatory approaches to mitigate risk.