The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

Land suitability analysis using geographic information systems (GIS) is one of the most widely used method today. In this type of studies, GIS and geo-spatial statistical tools are used to evaluate land units and present the results in suitability maps. The present work aims to characterize the suitability of soils in the province of Catamarca for pecan nut production according to the variables: rockiness, salinity, risk of water-logging, depth, texture and drainage described in the Soil Map of Argentina at a scale of 1:500,000 published by the National Institute of Agricultural Technology. A classification of the suitability of the soil cartographic units was made according to crop requirements, applying the methodology proposed by FAO. The standardization of variables made by omega score and the calculation of the spatial classification score were carried out as a result of the synthesis of the spatial distribution of soil suitability. The applied methodology allowed obtaining the soil suitability map resulting in a total of 60,662 km² suitable for pecan nut production, which accounts for 59.8% of the total area of the province.

This paper presents a brief review of risk studies in Geography since the beginning of the 20th century, from approaches focused on physical-natural components or social aspects, to perspectives that incorporate a systemic approach seeking to understand and explain risk issues at a spatial level. The systemic approach considers principles of interaction between multiple variables and a dynamic organization of processes, as part of a new formulation of the scientific vision of the world. From this perspective, the Complex Systems Theory (CST) is presented as the appropriate conceptual-analytical framework for risk studies in Geography. Finally, the analysis and geographic information integration capabilities of Geographic Information Systems (GIS) based on spatial analysis are explained, which position it as a fundamental conceptual and methodological tool in risk analysis from a systemic approach.

HRIS is a crucial tool for HR departments as it provides a digital platform for managing and automating various HR functions. HRIS is a comprehensive solution that integrates HRM functions with IT, enhancing the daily operations of HR professionals. In today’s knowledge-based economy, business success relies heavily on the performance of its human resources, which are essential in a rapidly changing global environment. Businesses continually strive to stay ahead of the curve in the ever-evolving technology landscape to thrive in the market. Some scholars have highlighted the negative impact of Human Resource Information Systems, primarily focusing on the invasion of privacy as the main disadvantage. The study indicates that implementing a Human Resource Information System (HRIS) enhances business performance in the tourism and hospitality industry of the Maldives. It highlights that user satisfaction and ease of use are positively influenced by these systems. The research surveyed 211 professionals and managers from the Maldives tourism and hospitality sector using a Likert Scale questionnaire to assess the impact of the HRIS on business performance. The study used SPSS 22.0 to analyze the impact of the Human Resource Information System (HRIS) on the dependent variable. The findings indicate that managerial personnel and human resource specialists in organisations find a user-friendly and satisfying HRIS motivating and beneficial for enhancing their performance. Organisations implement the HRIS to achieve their goals, identify system shortcomings, and develop strategies to improve business performance in the Maldives’ tourism and hospitality sector.

Through the combination of the geographic information systems (GIS) and the integrated information model, the stability of regional bank slope was comprehensively evaluated. First, a regional bank slope stability evaluation index system was established through studying seven selected factors (slope grade, slope direction, mountain shadow, elevation, stratigraphic lithology, geological structure and river action) that have an impact on the stability of the slope. Then, each factor was rasterized by GIS. According to the integrated information model, the evaluation index distribution map based on rasterized factors was obtained to evaluate the stability of the regional bank slope. Through the analysis of an actual project, it was concluded that the geological structure and stratigraphic lithology have a significant impact on the evaluation results. Most of the research areas were in the relatively low stable areas. The low and the relatively low stable areas accounted for 15.2% and 51.5% of the total study area respectively. The accuracy of slope evaluation results in the study area reached 95.41%.