Global demand for sustainable urban development has increased amid the accelerating effects of climate change, underscoring the need for resilient infrastructure and green buildings. This review examines the relationship among digital transformation, climate resilience, and sustainability in the built environment. It combines new developments in smart technologies that improve energy efficiency, resource optimization, and adaptive design, including blockchain, digital twins, building information modeling (BIM), the Internet of Things (IoT), and artificial intelligence (AI). The study looks at how digital innovation helps with disaster preparedness, predictive maintenance, carbon footprint reduction, and climate-responsive architecture. The review identifies new routes toward net-zero, climate-resilient urban ecosystems by examining case studies and international best practices.
Infrastructure Resilience and Vulnerability Analysis
Abstract The integration of Industry 4.0 technologies into supply chains (SCs) such as blockchain, artificial intelligence (AI), robotics, additive manufacturing and the Internet of Things (IoT), has transformed sustainability, operational efficiency and transparency. This enhances green supply chain management’s (GSCM) integrity and resilience which enable the achievement of sustainability objectives in line with the 2030 United Nations Sustainable Development Goals (UNSDGs) agenda. However, the accelerated digital adoption post-COVID-19 in developing countries came with increased SC vulnerabilities which undermine its integrity, resilience and sustainability goals. This study aims to determine the main SC cybersecurity risks and to recognise strategies that can be adopted to counter SC cybersecurity risks in developing countries. A search for literature was done in the Scopus, Google Scholar and ProQuest databases between 2018 and 2025 using a systematic literature review (SLR). The common SC cyber vulnerabilities findings were phishing incidents, breach of confidentiality, SC software attacks owing compromised open-source components and data theft. Consequently, this chapter proposed the use of monitoring and intrusion detection systems, collaborations for risk intelligence sharing, developing standardised cyber security protocols, use of firewalls and data encryption. These cybersecurity measures aim to equip SC managers and practitioners in developing countries with tools to protect data integrity and support sustainable Industry 4.0 operations by seamlessly integrating cybersecurity protocols with sustainability strategies, thereby enhancing resilience against digital disruptions. This chapter ends with proposing areas for further research and conclusion.
Supply Chain Resilience and Risk Management
Digital Transformation in Industry
Infrastructure Resilience and Vulnerability Analysis
Gurkan Akalin, Birsen Karpak, Y. İlker Topçu, Emel Aktaş
Purpose The pandemic, disruptions to transportation networks, geopolitical conflicts and trade restrictions over the past five years have intensified attention to supply chain resilience (SCRes) from both academia and industry. At the same time, rapid digitalisation is transforming traditional supply chains. Although numerous studies have examined digital technologies or SCRes independently, limited attention has been given to the reciprocal interrelationships among digital technologies and SCRes dimensions. Given the interconnected nature of digital technologies and the multidimensional characteristics of SCRes, examining these reciprocal interrelationships is essential for capturing their collective influence. Therefore, this study aims to identify the digital technologies that influence SCRes and examine their interrelationships with the dimensions of SCRes, thereby clarifying the relative roles and influence of both digital technologies and SCRes dimensions in strengthening more resilient and sustainable supply chains. Design/methodology/approach We conducted a structured literature review (SLR) and consulted a hybrid panel of seven academic and industry experts to identify the key dimensions of SCRes and the digital technologies influencing them. We then worked with experts to prioritise these factors using the analytic network process (ANP), an extension of the analytic hierarchy process (AHP) that is well-suited to modelling the strong interdependencies and feedback relationships among digital technologies and SCRes dimensions. Data were collected in both 2023 and 2025 from the same experts to capture the changes in expert judgements over time. Findings We found that collaboration and Internet-of-Things (IoT) have exerted the strongest relative influence on SCRes. In particular, collaboration becomes the highest priority factor overall, whereas IoT is the highest priority digital technology within the proposed decision framework. Visibility and velocity follow as the next most influential resilience dimensions, while AI and blockchain, although lower ranked, exhibit increasing relative influence across the two assessment periods. We also argue that no single digital technology on its own is sufficient to achieve supply chain resilience. Successful adoption and implementation require an understanding of how these technologies mutually interact with SCRes dimensions. By explicitly accounting for these interdependencies, the proposed decision framework prioritises both digital technologies and SCRes dimensions according to their relative influence on supply chain resilience, providing practical guidance for organisations seeking to strengthen resilience. Originality/value This study advances the SCRes literature by proposing an integrated ANP-based framework that models the interdependencies and feedback relationships between digital technologies and SCRes dimensions. Unlike prior studies that examine technologies in isolation or treat resilience dimensions as independent constructs, the present study evaluates both the combined and individual influence of digital technologies within a multidimensional resilience framework. The study further contributes by organising the literature around digital technologies and SCRes dimensions, revealing their interplay through expert judgement and providing a temporal comparison of evolving priorities between 2023 and 2025. The findings further demonstrate that SCRes emerges through reciprocal interdependencies between digital technologies and multiple resilience dimensions rather than through isolated technological effects.
Open access
Supply Chain Resilience and Risk Management
Infrastructure Resilience and Vulnerability Analysis
This study proposes a unified framework integrating AI, Blockchain, IoT, Digital Twins, quantum computing, and FKF spectral analysis for sustainable, transparent, and resilient supply chains. AI enables prediction and optimization; Blockchain ensures trusted traceability; IoT provides real-time sensing; Digital Twins support simulation; and quantum annealing addresses complex logistics optimization. FKF analysis captures temporal shifts, modulation, multiscale dynamics, and lead-time variations for AI-based spectral intelligence. The resulting sensing–analysis–intelligence–simulation–optimization architecture provides an adaptive pathway for efficient and resilient next-generation logistics Keywords— Artificial Intelligence; Sustainable Logistics; Green Supply Chain; Blockchain; Digital Twins; Internet of Things; Quantum Computing; Quantum Annealing; FKF Transform; Supply Chain Resilience.
Open access
Supply Chain Resilience and Risk Management
Digital Transformation in Industry
Infrastructure Resilience and Vulnerability Analysis
The Karhunen–Loève (KL) expansion provides an optimal orthogonal series representation of second-order stochastic processes and random fields. This paper presents a complete mathematical formulation of the KL theory using native Office Math Markup Language (OMML) equations, covering the governing Fredholm integral eigenvalue problem, the expansion and its coefficients, truncation error bounds, and the normalized representation. Building upon this theoretical foundation, we systematically explore practical applications of the KL expansion in contemporary supply-chain research themes: quantum-inspired optimization and uncertainty quantification in logistics networks; construction of resilient and adaptive digital twins for global supply chains; stochastic modelling supporting artificial-intelligence and blockchain integration for transparency, traceability and resilience; and uncertainty-aware modelling in sustainable and green logistics. The KL expansion emerges as a rigorous, computationally tractable tool for dimensionality reduction, random-field generation and risk quantification across these domains, thereby bridging classical stochastic process theory with the emerging requirements of Industry 4.0 and quantum-era logistics systems. Keywords— Karhunen–Loève expansion; stochastic processes; uncertainty quantification; digital twin; supply chain resilience; quantum logistics; green logistics; AI–blockchain integration.
Open access
Supply Chain Resilience and Risk Management
Risk and Portfolio Optimization
Infrastructure Resilience and Vulnerability Analysis
Economic Guarantees of Security (EGS), Internal Resistance Series, Working Paper No. 4 Work in Progress —August, 2026 Affiliation: International Institute of Political Philosophy (Kyiv, Ukraine) Author: Prof. Aleksandr Rozenfeld Contact: aleksrozenfeld2021@gmail.com Abstract This paper is part of the research series Internal Economic Resistance within the broader research program Economic Guarantees of Security (EGS). It develops the concept of business economic resistance as an endogenous constraint on military aggression and examines its role within a two-loop model of deterrence. Unlike conventional approaches that regard business primarily as a passive object of wartime mobilization, this study conceptualizes business as a decentralized network of autonomous economic agents possessing independent objectives, assets, contractual obligations, and decision-making authority. The paper argues that the principal source of business resistance lies not merely in expected financial losses but in the anticipated erosion of entrepreneurial freedom, property rights, contractual stability, market access, and institutional predictability. These institutional threats generate rational behavioral responses, including reduced investment, capital flight, production adjustment, contract restructuring, market reallocation, informal economic activity, and business exit. Although these responses rarely take the form of organized political protest, their diffusion through production, financial, contractual, and logistical networks gradually reduces the fiscal, technological, and organizational capacity of the state. The paper introduces the concept of an economic mobilization limit, defined as the point beyond which additional state pressure no longer increases, but instead diminishes, the effective resources available for military mobilization. Particular attention is devoted to the anticipatory nature of business behavior. Economic resistance frequently begins before the outbreak of war, as firms respond to expected sanctions, mobilization measures, regulatory restrictions, and institutional uncertainty. Consequently, well-designed systems of Economic Guarantees of Security can influence expectations at the decision-making stage, activating endogenous economic constraints before military aggression occurs. The proposed framework extends traditional deterrence theory by integrating external economic measures with internally generated behavioral responses of business. It demonstrates how decentralized economic decisions can complement international sanctions and other preventive mechanisms, thereby strengthening both the prevention of aggression and the conditions for its termination. One of the key conclusions of this work is that military aggression can be not only prevented but even stopped not only by external pressure measures but also by the economic behavior of businesses. The work presents and expands on a two-loop deterrence model that links international pressure measures with the internal disobedience of economic agents.
Open access
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Infrastructure Resilience and Vulnerability Analysis
This study develops and validates an ecological economics framework integrating green logistics practices to enhance supply chain resilience in Southeast Asia's automotive sector. Using mixed-methods analysis of 272 firms across Thailand, Indonesia, and Malaysia, structural equation modelling confirms three hypotheses: green logistics adoption significantly predicts resilience (β=0.38, p 4.0 thresholds flipping green logistics from cost to profit centre. Findings advance dynamic capabilities theory with biophysical limits, resolve triple bottom line tensions, and deliver managerial roadmaps (rail pilots→FCA training→blockchain Scope 3) plus ASEAN policy blueprints (CBAM harmonisation, $500M capacity fund). The framework positions the ASEAN automotive sector for regenerative leadership, converting natural capital from externality to competitive asset amid global decarbonisation pressures. These findings offer actionable insights for managers, investors, and policymakers seeking to align profitability with ecological resilience in emerging economies.
Open access
Supply Chain Resilience and Risk Management
Sustainable Supply Chain Management
Infrastructure Resilience and Vulnerability Analysis