Using the United Nations’ Online Services Indicator (OSI) as a benchmark, the study analyzes Jordan’s e-government performance trends from 2008 to 2022, revealing temporal variations and areas of discontent. The research incorporates diverse testing strategies, considering technological, organizational, and environmental factors, and aligns with global frameworks emphasizing usability, accessibility, and security. The proposed model unfolds in three stages: data collection, performing data operations, and target selection using the Generalized Linear Model (GLM). Leveraging web crawling techniques, the data collection process extracts structured information from the Jordanian e-government portal. Results demonstrate the model’s efficacy in assessing accessibility and predicting web crawler behavior, providing valuable insights for policymakers and officials. This model serves as a practical tool for the enhancement of e-government services, addressing citizen concerns and improving overall service quality in Jordan and beyond.

Creating products and services that satisfy individual and community needs is impossible without raw materials. This study takes a novel approach by integrating the economic dynamics and raw material consumption indicators of the European Union (EU). The study uses different econometric methods to analyze the relationship between GDP (gross domestic product) and the EU’s raw material consumption (RMC) from 2014–2023. Among the results, the panel data analysis model shows that the resource productivity of the EU improved during the period under review, whereas the material intensity decreased significantly. These trends significantly contributed to the relative decoupling of material consumption from GDP in the last decade. The results of the K-means cluster analysis highlight the regional economic differences within the EU. According to the results of the correlation analysis, EU member countries differ significantly in the efficiency of raw material use. Nevertheless, five member countries are robustly vulnerable to large-scale raw material use. The divergence calculation results show that while some countries use raw materials extremely efficiently to produce GDP, others achieve low efficiency. This unique approach and the resulting findings provide a new perspective on the complex relationship between economic growth and raw material use in the EU.

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.

The global agreement on environmentally friendly policies puts pressure on businesses to implement good practices to increase legitimacy in a competitive environment. This research aims to examine business dynamic capabilities and value creation processes through the concept of green dynamic marketing capabilities. This concept addresses the ability of businesses to absorb, manage information and accumulate new knowledge that fuels innovative endeavors. The dynamic capability view and customer value theory are integrated to theoretically explain the value creation process of market-orientated innovative products. A total of 58 global companies in Clean200 were sampled. A quantitative approach was conducted to measure the effect of organizational learning (environment management team, environment management training, environment supply chain management) on green innovation (environmental innovation score, eco design product). The results showed that the contribution of Model-1 (0.473 or 47.3%) explained the effect of organizational learning on environmental innovation score, respectively on the variables of environment management team (2.859/0.005), environment management training (−2.971/0.003), and environment supply chain management (7.786/0.000). The contribution of Model-2 (0.448/44.8%) explains the effect of organizational learning on eco-design product, respectively on the variables of environment management team (4.280/0.000), environment management training (−6.401/0.000), and environment supply chain management (7.910/0.000). Model-3 tested the structural association variables in organizational learning and green innovation. A significant influence can be seen with a probability value smaller than 0.05. This research shows that the concept of green dynamic marketing capabilities can be used to explain the ability of businesses in response to the pressure of green global norms through the development of organizational learning towards creation of green innovation product that has impact on market performance. The implication of this research is the creation of new mindset in which green global norms challenge becomes an opportunity for businesses to improve competitiveness.

This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.

The effective drainage radius of coal seam is an important basis for the spacing of pre-drainage gas boreholes. To quickly and accurately determine the effective drainage radius, a new method was proposed. For the coal face where the desorbable gas content before mining has met the standard, the compliance of mine gas drainage rate was used as the basis to determine the effective drainage radius. The fluid-structure interaction model was constructed, numerical simulation of coal seam gas drainage was carried out by using COMSOL software, and the model was validated by combining the field test results. The results show that the new method has the advantage of short cycle. With the extension of drainage time, the increase of effective drainage radius gradually decreases, and finally reaches a relatively stable limit value, which conforms to the Langmuir function. The average error between numerical simulation and field test values of effective drainage radius is 4.9%, which proves that the model is reliable. This model can accurately predict the effective drainage radius under different coal seam gas contents and drainage times. The research results provide a new mean for determining the effective drainage radius of coal seam and the layout of gas drainage boreholes.