Monitoring systems in asset-intensive organisations depend on more than sensors, dashboards, and technical integration. Construction fleet telematics, smart-city platforms, and IoT-based operational systems require consent, coordination, and review from external stakeholders who control data access, public permissions, vendor interfaces, and compliance rules. Despite the rapid growth of the fleet telematics market — projected to expand from approximately USD 20 billion in 2025 to nearly USD 47 billion by 2034 — the organisational literature has not produced a structured model linking external stakeholder engagement to the specific decision sequence that monitoring-system projects follow. This review addresses that gap. It uses source analysis, comparative review, typologization, and conceptual synthesis to examine eighteen recent publications on public-sector digital transformation, smart-city data governance, construction digitalisation, collaborative governance, fleet telematics, stakeholder engagement frameworks, and data-privacy regulation. The review identifies three engagement models — centralised authorisation, distributed operational coordination, and hybrid governance — and proposes a five-gate implementation sequence connecting stakeholder classification, pilot perimeter design, data governance, operational escalation, and scale-up review. The article contributes a management-oriented implementation logic for large companies and public-facing operations where bureaucratic approval, city authority involvement, vendor dependency, and regulatory compliance shape the practical value of monitoring systems.

This article examines approaches to peak load management in the operational activities of international logistics operators under conditions of high demand volatility, digitalization, and increasing supply chain complexity. The study is conducted as a systematic review and analytical synthesis of scientific publications focused on demand forecasting, resource allocation, supply chain integration, and the application of digital technologies in logistics. Particular attention is given to interpreting peak loads as a systemic state arising from misalignment between demand, resources, and capacity, as well as to analyzing the relationship between digital controllability and network coordination. A comparative analysis of various load management approaches is carried out, including forecasting, optimization, and integration models, along with an assessment of their impact on the resilience of logistics systems. It is established that the isolated application of individual tools does not ensure effective overload prevention without their integration into a coordinated management loop and supply chain interaction framework. An original adaptive model for peak load management is proposed, reflecting the transition from imbalance detection to structural reconfiguration of flows and system stabilization. The findings make it possible to conceptualize the resilience of a logistics system as a systemic property determined by the level of coordination, integration, and dynamic adaptability. The article may be of interest to researchers in logistics and supply chain management, as well as practitioners engaged in the digital transformation of operational activities.

This article analyzes the challenges of supply chain management under conditions of geopolitical instability in the global economy and proposes a new conceptual approach to address them. While existing research primarily focuses on disruption forecasting and risk identification, the capabilities for autonomous decision-making remain insufficiently developed. In this study, an "Autonomous Self-Healing Supply Chain" model is developed, integrating big data analytics, causal modeling, and network-based approaches into a unified system. The results demonstrate that the proposed model not only enables early detection of disruptions but also allows for their automatic mitigation. This significantly enhances the resilience and adaptability of supply chains in a rapidly changing global environment.

This study conducts a systematic theoretical-bibliographic review of the fundamental barriers and conceptual problems confronting the integration of Natural Capital Accounting (NCA) into the System of National Accounts (SNA). It critically examines why conventional macroeconomic indicators fail to capture ecological degradation under conditions of non-linear dynamics, and proposes institutional solutions grounded in the existing literature. A systematic review of peer-reviewed literature from Scopus and Web of Science was conducted, complemented by analysis of key policy documents (SEEA CF, SEEA EA, Dasgupta Review). Sources were selected using targeted keyword combinations and snowball searching. The review synthesizes foundational and contemporary works on national accounting, natural capital measurement, non-linear ecological dynamics, and institutional reform. No primary statistical datasets were employed. Three categories of fundamental barriers are identified: measurement barriers, conceptual barriers, and institutional barriers. The paper demonstrates that ecological tipping points, regime shifts, and threshold effects render the SNA's implicit linearity assumption untenable. A five-tier conceptual framework linking natural capital stocks through non-linear degradation dynamics to adjusted macroeconomic indicators and sustainability indices is developed.