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Ken A. Charles

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Open access Aug 2026

Context and policy: Enabling circular construction across diverse global realities (2023–2030)

Purpose: The construction sector generates 2.2 billion tonnes of waste each year, yet recycling rates vary wildly, from 80% in Japan to below 15% in many emerging economies. This article explores how different policy frameworks, regulatory approaches and local realities shape construction waste management outcomes across the globe. Theory: Institutional theory, through its regulatory, normative, and cultural-cognitive pillars, combined with transition management’s multi-level perspective on niches, regimes, and landscape pressures, provides the analytical foundation for this study. These frameworks are applied to explain the varying success or failure of policies across different contexts. Methodology: Using comparative case study analysis, we examined construction waste systems in 12 countries across six continents. Data come from policy documents, government reports, academic research and publications by multilateral organisations, industry bodies and civil society groups. Findings: Five factors consistently separate high-performers from laggards: strong regulatory enforcement, well-designed economic incentives, infrastructure that matches ambition, investment in skills, and genuine stakeholder inclusion. But how these play out depends heavily on context. Importantly, informal waste workers who recover 40% of materials in India and number over 60,000 in South Africa are routinely excluded from formal policy, leading to the kind of conflict seen with Chile’s EPR law. Practical Implications: This article offers policymakers a practical framework for adapting strategies to four different contexts: High- income economies, emerging economies, Resource- rich transforming countries, and Places where informal waste sectors dominate. It also outlines a research agenda to guide future inquiry. Originality/Value: This is the first comparative study of construction waste policy that explicitly uses institutional theory and transition management to explain cross- country differences, with a focus on informal sector integration, just transition principles, and context? sensitive adaptation.

Ken A. Charles · 0 citations
Review Open access Aug 2026

Governing the adaptive organism: A framework for human-AI symbiosis in anticipatory project management

Purpose: The integration of artificial intelligence (AI) into project management is accelerating, yet governance frameworks have failed to keep pace with the transition from tool-based automation to genuine human-AI symbiosis. This article synthesizes literature across four fragmented domains to propose a unified governance model for anticipatory project management. Design/methodology/approach: A systematic, integrative review was conducted covering: AI in project management, Human-AI collaboration, Anticipatory governance, and Complexity theory. The synthesis draws on peer-reviewed literature from 2023-2026, integrating seminal work on human-AI co-agency and adaptive systems. Findings: The review reveals a fundamental tension: technological capability outpaces organisational absorption. To address this, the article introduces the Adaptive Organism Governance (AOG) Framework. This model reconceptualises the project organisation as a complex adaptive system comprising four interdependent dimensions: Cognitive Augmentation, Collaborative Intelligence, Anticipatory Sensing, and Complexity Absorption. The framework is operationalized through six governance principles: subsidiarity, transparency, adaptability, resilience, human-centricity, and continuous learning. Originality/value: This article provides the first comprehensive synthesis linking AI technical capabilities with anticipatory governance theory. The AOG Framework offers a theoretically grounded, actionable pathway for practitioners navigating the digital transformation of project delivery, shifting the focus from controlling machines to cultivating symbiotic ecosystems.

Ken A. Charles · 0 citations