As urbanisation increases, questions arise about the desirability of further urban growth, as it was not accompanied by corresponding economic growth, and social and environmental problems began to grow in the largest cities in the world. The objective of the article is to substantiate the limits of urbanization growth in Kazakhstan based on the study of theoretical views on this process, analysis of the dependence of social and economic parameters of 134 countries on the urbanisation level and calculation of the urbanisation level that contributes most to economic growth and social well-being. To achieve the goal, the following tasks have been set and solved: theoretical views on the process of urbanization have been generalized; a hypothesis has been put forward about the emergence of an “urbanization trap” in which the growth of large cities is not accompanied by economic growth and improvement of social well-being; an analysis of the dependence of socio-economic indicators on the level of urbanization has been carried out on the example of 134 countries of the world; the level of urbanization that maximizes economic growth and social well-being is calculated; the necessity of the development of small towns in Kazakhstan is substantiated. To solve the problems, the methods of logical analysis, analogies and generalizations, economic statistics, index, graphical, Pearson correlation analysis, Spearman and Kendall rank regression based on models in SPSS were used. As a result, the following conclusions are made: the hypothesis of a possible deterioration of socio-economic indicators in large cities is confirmed; the best positive result is demonstrated by the level of urbanization of 50%–59%. The recommendations are justified: in Kazakhstan, it is necessary to adhere to the level of urbanization no higher than 59%; the growth of urbanization should be ensured through the development of small towns; it is necessary to improve the methods of managing the process of urbanization and develop individual city plans.

The structure and diversity of tree species in a temperate forest in northwestern Mexico was characterized. Nine sampling sites of 50 × 50 m (2,500 m²) were established, and a census of all tree species was carried out. Each individual was measured for total height and diameter at breast height. The importance value index (IVI) was obtained, calculated from the variable abundance, dominance and frequency. The diversity and richness indices were also calculated. A total of 12 species, four genera and four families were recorded. The forest has a density of 575.11 individuals and a basal area of 23.54/m². The species of Pinus cooperi had the highest IVI (79.05%), and the Shannon index of 1.74.

Although dykes are a predominant and widely distributed phenomenon in S-Algeria, N-Mali and N-Niger, a systematic, standardized inventory of dykes covering these areas has not been published so far. Remote sensing and geo information system (GIS) tools offer an opportunity for such an inventory. This inventory is not only of interest for the mining industry as many dykes are related to mineral occurrence of economic value, but also for hydrogeologic investigations (dykes can form barriers for groundwater flow). Surface-near dykes, major fault zones, volcanic and structural features were digitized based on Landsat 8 and 9, Sentinel 2, Sentinel 1 and ALOS PALSAR data. High resolution images of World Imagery files/ESRI and Bing Maps Aerial/Microsoft were included into the evaluations. More than 14,000 dykes were digitized and analyzed. The evaluations of satellite images allow a geomorphologic differentiation of types of dykes and the description of their characteristics such as dyke swarms or ring dykes. Dykes are tracing zones of weakness like faults and zones with higher geomechanically strain. Dyke density calculations were carried out in ArcGIS to support the detection of dyke concentrations as stress indicator. Thus, when occurring concentrated, they might indicate stressed areas where further magmatic and earthquake activity might potentially happen in future.

Purpose: The aim of the study is to apply policy analysis matrix (PAM) to identify international competitiveness of marketing channels and policy impacts of government on each marketing channels. Methodology: Policy analysis matrix is employed to evaluate influences of macroeconomic policy on the Tuong-mango value chain. The study investigated 213 sampling observation of eight main actors in chain. Findings: The findings indicate that although domestic channel 4 exhibits competitiveness (Private cost ratio (PRC) < 1), channels 1, 2, and 3 possess both comparative and competitive advantages (PRC < 1, Domestic Resource Cost (DRC) < 1, and social benefit-cost (SBC) > 1). The government’s strategy on production protection, referred to as Nominal protection coefficient on tradable output (NPCO) 0.16, together with the plan for enhancing added value, denoted as Effective protection coefficient (EPC) 0.14 and Subsidy ratio to producers (SRP) −0.18, place a significant emphasis on the first export channel. The government’s subsidy plan grants preferential treatment to Channel 4 in terms of the pricing of commercially available products, with a Nominal protection coefficient on tradable input (NPCI) value of 0.75. A value-added strategy is implemented for export channels 2 and 3, which have EPCs of 0.76 and 0.85, respectively. Policy implications: If the tradable cost is modified by 20%, there will be a change in the ratio of DRC, SBC, EPC, and SRP. While the EPC does not see a 20% reduction in domestic prices, the DRC and SBC do benefit from this cost reduction. A reduction of 20% in the local cost, coupled with a corresponding rise of 20% in the Free on Board (FOB) price, would result in a significant elevation of the SRP for export channels 1, 2, and 3. Conclusion: This is as evidence for the combination of quantitative is a dynamic tool in the policymaking process to ensure targets, constrictions, and consistent policies for agricultural fields. This permits policies to be changed in steps with an alteration in the economy and priorities set up for the tropical fruits and vegetables field.

In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.

Countries employ various strategies to strengthen their soft power through education, public campaigns, mandatory service, and community involvement, essential for building a well-informed, prepared, and resilient citizenry. In Indonesia, the Civic Awareness for State Defence (CASD) program is designed to instil state defence awareness among citizens. This study introduces the Indonesia State Defence Index (SDI), a novel metric grounded in theoretical constructs such as national identity, nationalism, patriotism, and national pride. Differentiating from previous indices, our SDI employs advanced methodologies including Principal Component Analysis (PCA) and Structural Equation Modeling (SEM) to enhance measurement accuracy. Unlike earlier approaches that used traditional aggregation methods, our use of PCA ensures the reduction of dimensions for each state defence indicator, thereby guaranteeing that only the intended dimensions are measured. Utilising data from the State Defence Survey conducted by the Indonesian Ministry of Defence from 1 March to 26 June 2024, we aim to measure and benchmark SDI values across Indonesian regions, thereby elucidating the civic awareness profile in the context of state defence. The refined SDI provides critical insights for policymakers, highlighting regions that require focused interventions to bolster state defence preparedness.