This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.

This study unveils the mediating mechanism and explores the role of organizational trust in the link between organizational justice and turnover intention among female employees in the banking industry. For this purpose, we gathered data from 336 female workers employed at a Tunisian prominent bank, encompassing both head office and branch locations dispersed throughout the country. Our study analyzed the data using AMOS statistical software version 25 and confirmed our research hypotheses. Our findings showed that procedural justice and interactional justice positively influence organizational trust, while they both have a negative impact on turnover intention among female employees. Furthermore, organizational trust significantly and negatively influences female employees’ turnover intention. Ultimately, we have demonstrated that organizational trust completely mediates the link between procedural and interactional justice and female employees’ turnover intention. This highlights the significance of organizational trust in conditioning the relationships linking procedural and interactional justice to turnover intention among female employees. Hence, top management should put more emphasis on building organisational trust among their female employees to ensure positive attitude and behaviour. Other implications for practitioners and researchers are elaborated.

In recent years, an ‘international’ unanimity has been reached as to the importance of collective collaboration to avoid the negative effects of climate change. This requires rethinking the old or traditional development model based on economic growth as the exclusive indicator of wealth. Thus, humanity has an urgent need to adopt a new, more humane and fairer economic model that constitutes an alternative to the models of exponential growth that have dominated in the last two centuries. To do so, humanity is looking to the Degrowth model as a potential concept that aims to reduce wealth from pollutants, seeks more justice (as equity), and the improvement of the capabilities of those who are poor and disadvantaged (in the sense of Amartya Sen and Martha Nussbaum). The purpose of this article is to question this model and whether it actually does improve environmental quality. Additionally, if the response is positive, another question arises: How to finance degrowth especially when we seek other less polluting energy sources whose costs seem to be very high?

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.

Social Services are vital for addressing adversity and safeguarding vulnerable individuals, presenting professionals with complex challenges that demand resilience, recovery, and continual learning. This study investigates Organizational Resilience within Community Social Services, focusing on strategic planning, adaptive capacity, and user perspectives. A cross-sectional study involved 534 professionals and service users from Community Social Services Centers in Spain. Centers were selected based on the characteristics of their population and the representativeness of their geographic location. The study utilized the Benchmark Resilience Tool (BRT) to evaluate Organizational Resilience and the SERVPERF questionnaire to gauge user-perceived service quality. The results demonstrate satisfactory levels of Organizational Resilience and user satisfaction, while also highlighting key areas for enhancing resilient strategies: reinforcement of personnel for thinking outside the box or in the resources available to the organization to face unexpected changes. These findings suggest the need to develop and optimize measures that improve the organization’s ability to adapt to and recover from adverse situations, ensuring a positive user experience. Emphasizing the importance of resilience in Social Services as a quality predictor, future research should explore innovative strategies to bolster Organizational Resilience. The findings emphasize the need to strengthen resilience in Social Services, enhancing practice, policy, and adaptability to support vulnerable populations.

The study is devoted to the problem of processing the organic waste that is generated as a result of paper, textiles and other industries production as well as food waste. The growth of economic activity in Kazakhstan has resulted in a significant challenge with regard to industrial waste management. The accumulation of waste on the territory of the country has reached 31.72 billion tonnes, comprising approximately 2.5 billion tonnes of hazardous waste, 50 million tonnes of phosphorus-containing waste, over 2.5 million tonnes of lead-zinc waste and more than 120 million tonnes of solid domestic waste. The study object was the Shymkent-Kokys polygons. According to the research carried out, it was determined that the titer of microorganisms of the studied groups is 1–10 CFU/g in the soils selected around the garbage in the area of the Shymkent landfill. The titer of microorganisms in the soil horizons was high at a depth of 20–30 cm and the titer were 10⁹ cells/mL. The structure of the soil microbiome obtained around the Shymkent Waste Landfill consists of actinomycetes, micromycetes, heterotrophic bacteria, nitrifying, nitrogen-fixing bacteria, enterobacteria, as well as algae and protozoa. It was found that strains KPA1, KPA2 Pseudomonas sp. strains KPA3, KPA4, KPA5 Bacillus sp. isolated from the soils of the Shymkent-Kokys landfill are able to recycle domestic waste with a high content of cellulose and organic substances up to 95%–97%. The findings can be used to develop more effective organic cellulosic waste management strategies and improve the environmental sustainability of various industries.