Armenian State University of Economics

The increasing complexity of contemporary urban systems necessitates decision-making frameworks capable of systematically integrating multidimensional sustainability considerations into policy evaluation processes. While existing urban sustainability assessment approaches predominantly focus on isolated environmental or socio-economic indicators, they often lack methodological coherence and direct applicability to operational decision-making. This study proposes a multi-layer sustainability indicator framework explicitly designed to support evidence-based urban decision-making under conditions of uncertainty, institutional constraints, and competing policy objectives. The framework integrates environmental, economic, social, and institutional dimensions of sustainability into a structured decision-support architecture. Methodologically, the study employs a two-stage approach combining expert-based weighting techniques (Analytic Hierarchy Process and Best–Worst Method) with multi-criteria decision-making methods (TOPSIS and VIKOR) to evaluate and rank alternative urban policy scenarios. The proposed framework is empirically validated through an urban case study, demonstrating its capacity to translate abstract sustainability indicators into comparable decision outcomes and policy priorities. The results indicate that the integration of multi-layer indicator systems with formal decision-analysis tools enhances transparency, internal consistency, and strategic coherence in urban governance processes. By bridging the gap between sustainability measurement and decision implementation, the study contributes to the advancement of urban governance scholarship and provides a replicable analytical model applicable to cities facing complex sustainability trade-offs.

The global alcoholic beverage industry represents a sophisticated intersection of agricultural supply chains and long-cycle manufacturing, where high-intensity branding meets unique asset structures. This study evaluates the financial sustainability of Diageo PLC from 2014 to 2025, moving beyond descriptive accounting to analyze the "Permanent Debtor" model inherent in the spirits industry. Utilizing a structured methodology of three indicator groups (Capital Structure, Asset Security, and Operational Servicing), the research finds that while Diageo’s leverage ratios (G1.1 > 2.0) appear high by conventional standards, they are fundamentally secured by the appreciation of maturing inventory. The study’s key contribution is the identification of a "safety margin" where the retail value appreciation of aged spirits outpaces the cost of debt, providing a strategic blueprint for debt management in asset-heavy industries. The analysis also introduces the Times Burden Covered (TBC) ratio to provide a more rigorous assessment of solvency than standard interest coverage ratios.

Purpose This study aims to clarify and systematize the conceptual, theoretical and methodological foundations of three key consumer behaviors, namely pro-environmental behavior (PEB), sustainable consumption behavior (SCB) and circular behavior (CB), which are critical for advancing sustainability transitions. Design/methodology/approach A scoping literature review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol across three major databases (Scopus, Web of Science and Google Scholar), and the final sample included 258 academic papers published from 2019 to 2025. The selected literature was analyzed through the theory–context–characteristics–methods (TCCM) framework to identify conceptual definitions, theoretical models, behavioral determinants and methodological approaches. Findings The main findings indicate that while PEB, SCB and CB share a common characteristic such as the consumer's conscious intention to reduce environmental impact, there are differences in scope and emphasis. PEB includes activism and public engagement, SCB focuses on consumption and its social dimensions and CB emphasizes consumer acceptance of circular innovations. Research limitations/implications Future research should expand the scope of analysis to include grey literature, adopt longitudinal and experimental designs to validate behavioral models and systematically examine the role of artificial intelligence in shaping sustainability behaviors. Originality/value This is the first study to conduct a comparative scoping review of PEB, SCB and CB using the TCCM framework. It offers a structured synthesis that resolves terminological ambiguities, maps theoretical evolution and identifies gaps in measurement and intervention research.

The integration of artificial intelligence (AI) into the financial system, especially in the banking sector, has become one of the most important directions of technological progress. The aim of the article is to reveal the specifics of the application of AI in banking services, emphasizing the role of chatbots and virtual assistants in the customer-centric services and risk management system. The article presents the theoretical foundations and main directions of application of AI in the banking system. Four main directions are analyzed: customer-centric solutions, process optimization, banking services market management, and improvement of regulatory mechanisms. The experience of international banks (Bank of America, HSBC, DBS, Armenians banks, and others) indicates that the use of AI contributes to reducing operating costs and accelerating and personalizing customer service. However, the integration of AI also raises challenges related to data privacy, cybersecurity, legislative regulations, and the transformation of professional skills. Special attention is paid to the field of credit scoring, where machine learning methods allow for a more accurate assessment of borrower behavior and reduce financial risks. The relevance of the research is due to the fact that AI is no longer an additional technology for banks but a necessary tool for maintaining competitiveness and sustainable development. Received: 21 September 2025 | Revised: 5 January 2026 | Accepted: 10 March 2026 Conflicts of InterestThe authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in PES at https://doi.org/10.24874/PES06.02.023, reference number [31], in ASPUR at https://doi.org/10.61552/JAI.2024.01.004, reference number [32], in International Accountancy Training Centre at https://doi.org/10.59503/29538009-2024.2.14-121, reference number [33]. Author Contribution Statement Suren H. Parsyan: Conceptualization, Methodology, Investigation, Resources, Writing – original draft, Writing – review & editing, Supervision, Project administration. Frida F. Baharyan: Conceptualization, Investigation, Resources, Data curation, Writing – original draft. Gayane A. Avagyan: Conceptualization, Methodology, Validation, Formal analysis, Resources, Writing – original draft, Writing – review & editing. Sergo A. Episkoposian: Methodology, Validation, Visualization. Vardan S. Aleksanyan: Software, Investigation, Supervision. Ararat Kostanian: Writing – review & editing, Visualization. Lilik M. Beglaryan: Methodology, Visualization, Writing – review & editing.

The global financial system is subject to constantly evolving threats. With the ever-expanding diversity of information technologies, blockchain systems, and artificial intelligence tools, the mechanisms for committing financial and economic crimes through anonymous or shell companies are also evolving. In general, anonymous companies are not simply passive legal structures but active facilitators of complex financial crimes. Their strongest and most direct links lie in the realm of corruption and money laundering, where they serve as key tools for concealing, facilitating transactions, and integrating illicitly acquired wealth into the global financial system.