Land use changes have been demonstrated to exert a significant influence on urban planning and sustainable development, particularly in regions undergoing rapid urbanization. Tehran Province, as the political and economic capital of Iran, has undergone substantial growth in recent decades. The present study employs sophisticated Geographic Information System (GIS) instruments and the Google Earth Engine (GEE) platform to comprehensively track and analyze land use change over the past two decades. A comprehensive analysis of Landsat images of the Tehran metropolitan area from 2003 to 2023 has yielded significant insights into the patterns of land use change. The methodology encompasses the utilization of GIS, GEE, and TerrSet techniques for image classification, accuracy assessment, and change detection. The Kappa coefficients for the maps obtained for 2016 and 2023 were 0.82 and 0.87 for four classes: built-up, vegetation cover, barren land, and water bodies. The findings suggest that, over the past two decades, Tehran Province has undergone a substantial decline in ecological and vegetative areas, amounting to 2.4% (458.3 km2). Concurrently, the urban area and the barren lands have expanded by 287.5 and 125.5 km2, respectively. The increase in water bodies during this period is likely attributable to the reduction of vegetation cover and dam construction in the region. The present study demonstrates that remote sensing and GIS are excellent tools for monitoring environmental and sustainable urban development in areas experiencing rapid urbanization and land use changes.

The study investigates the impact of artificial intelligence (AI)-powered chatbots on brand dynamics within the banking sector, focusing on the interrelationships between AI implementation and key brand dimensions, including awareness, equity, image, and loyalty. Using structural equation modeling (SEM) analysis on data collected from 520 banking customers, the study tests eight hypotheses to explore the direct and indirect effects of AI-driven interactions on brand development. The findings reveal that AI chatbots significantly enhance brand awareness in banking services, demonstrating moderate positive effects on both brand equity and brand image. Notably, while brand awareness exerts a strong influence on brand image, it does not have a significant direct effect on brand loyalty. Instead, the study shows that brand loyalty is primarily developed through the mediating effects of brand equity and image, with brand image exerting a particularly strong influence on brand equity. For banking practitioners, these insights suggest a need to integrate AI chatbots within a comprehensive brand strategy that merges technological innovation with traditional relationship-building approaches. Limitations of the study and potential directions for future research are also discussed, providing avenues for further exploration of AI’s role in brand management.

This study explores the potential of digital preservation in the documentation of colonial cultural heritage in Egypt. It also explores the stories behind historical wars to revive these sites and attract different segments of visitors. Documentation of these sites should enhance Egyptian colonial cultural heritage sites, which include battlefields, war memorials, commanders’ palaces, assassination and murder spots, cemeteries, and mausoleums. The purpose of this study was fulfilled through field visits supplemented with in-depth interviews with experts on colonial heritage sites in Egypt. The findings showed that technology could play a key role in implementing the storytelling documentation and interpretation of colonial history and its relevant events at the Egyptian sites. However, to date, these sites have not made the best use of technology for digital preservation and documentation due to many challenges. The study recommends that decision-makers should integrate technological innovation, which can revitalize the communities built on the ruins of colonialism and revive the heritage of popular resistance. Technological innovation could be implemented not only in digital preservation and documentation but also in service and marketing of these colonial heritage sites.

Objective: This study synthesizes current evidence on the role of Artificial Intelligence (AI) and, where relevant, Open Science (OS) practices in enhancing Human Resource Management (HRM) performance. It focuses on recruitment processes, ethical considerations, and employee participation. Methodology: A systematic literature review was conducted in Scopus covering the period 2019–2024, following PRISMA guidelines. The initial search yielded 1486 records. After de-duplication and screening using Rayyan, 66 studies (≈ 4.4%) met the inclusion criteria, which targeted peer-reviewed works addressing AI-supported HR decision-making. A combined content and bibliometric analysis was performed in R (Bibliometrix) to identify thematic patterns and conceptual structures. Results: Analysis revealed four thematic clusters: 1) Implementation and employee participation emphasizing human-in-the-loop approaches and effective change management; 2) ethical challenges including algorithmic bias, transparency gaps, and data privacy risks; 3) data-driven decision-making delivering higher accuracy, fewer errors, and personalized recruitment and performance assessment; 4) operational efficiency enabling faster workflows and reduced administrative workloads. AI tools consistently improved selection quality, while OS practices promoted transparency and knowledge sharing. Implications: The successful adoption of AI in HRM requires employee engagement, strong ethical safeguards, and transparent data governance. Future research should address the long-term cultural, organizational, and well-being impacts of AI integration, as well as its sustainability.

New telechelic polymers functionalized with terminal ethyl xanthate or vinyl groups were synthesized via cationic ring-opening polymerization (CROP). The polymerization of 2-ethyl-2-oxazoline (Etoxa) and 2-methoxycarbonylethyl-2-oxazoline (Esteroxa) was initiated by 1,4-trans-dibromobutene in acetonitrile at 78 ℃, with termination using either potassium ethyl xanthate or 4-vinylbenzyl-piperazine. Structural characterization by 1H and 13C NMR and FTIR spectroscopy confirmed the telechelic architecture. 1H NMR analysis revealed degrees of polymerization (DP) of 24–29 for ethyl xanthate-terminated polymers and 22–23 for vinyl-terminated polymers, consistent with theoretical values. The molar compositions of Etoxa and Esteroxa in all telechelic polymers matched the initial monomer feed ratios. End-group functionalization efficiency was quantified as follows: Ethyl xanthate-terminated polymers: 64%–82%, and vinyl-terminated polymers: 69% and 98% (for respective batches).

Objectives: This research aimed to empirically examine the transformative impacts of Artificial Intelligence (AI) adoption on financial reporting quality in Jordanian banking, with internal controls as a hypothesized mediation mechanism. Methodology: Quantitative survey data was collected from 130 bank personnel. Multi-item reflective measures assessed AI adoption, internal controls, and financial reporting quality—structural equation modelling analysis relationships between constructs. Findings: The research tested four hypotheses grounded in agency and contingency theories. Confirmatory factor analysis demonstrated sound measurement models. Structural equation modelling revealed that AI adoption significantly transformed financial reporting quality. The mediating effect of internal controls on the AI-quality relationship was supported. Specifically, the path from AI adoption to quality was significant, indicating a positive impact. Despite internal controls strongly predicting quality, its mediating effect significantly shaped the degree of transformation driven by AI adoption. The indirect effect of AI on quality through internal controls was also significant. Findings imply a growing diffusion of AI applications in core financial reporting systems. Practical implications: Increasing AI applications focus on holistically transforming systems, reflecting committing adoption. Jordanian banks selectively leverage controls to moderate AI-induced transformations. Originality/value: This study provides essential real-world insights into how AI is adopted and impacts the Jordanian banking sector, a key player in a fast-evolving developing economy. By examining the role of internal controls, it deepens our understanding of how AI works in practice and offers practical advice for integrating technology effectively and improving information quality. Its mixed methods, unique context, and focus on AI’s impact on organizations significantly enrich academic literature. Recommendations: Banks should invest in integrated AI architectures, strategically strengthen critical controls to steer transformations, and incrementally translate AI innovations into core processes.