The construction industry is increasingly adopting digital technologies to support circular economy (CE) practices; however, the effective integration of these approaches in practice remains unclear. This paper examines digital–circular integration as a pathway dependent process within the construction industry in the United Arab Emirates (UAE). Drawing on semi-structured interviews with nine industry experts, the study employs a qualitative, process-oriented approach to explore how integration evolves throughout the project lifecycle and how organizational and project conditions influence its development. The findings identify three integration pathways: intentional, emergent, and hybrid. Strategic decisions and regulatory requirements drive intentional pathways, emergent pathways arise through learning during project execution, while hybrid pathways combine early planning with adaptive implementation. The results show that integration outcomes are shaped primarily by leadership, timing, governance, and organizational alignment rather than by technological capability alone. By conceptualising integration as a dynamic, pathway dependent process, the paper advances understanding of how digital and circular strategies can be more effectively aligned and provides practical insights for achieving more consistent and scalable implementation.

The built environment contributes substantially to global energy consumption and material waste, creating urgent need for sustainable retrofit strategies. While Digital Twin (DT) technologies and Circular Economy (CE) principles have gained considerable research attention, integrated frameworks tailored to the UAE context remain absent. This systematic literature review synthesized 85 peer-reviewed studies published between 2014 and 2026 using the PRISMA 2020 protocol, achieving strong inter-rater reliability. Six thematic clusters were identified and analyzed across four dimensions: retrofit decision support, circularity assessment, UAE contextualization, and predictive simulation. The review confirmed a persistent four-dimensional capability gap. To address this, a Digital Twin-ready framework is proposed comprising four layers: UAE exposure-context calibration, Circularity Readiness Index (CRI) computation, rule-based decision support, and predictive simulation. The framework provides a rigorous foundation for future validation and operational implementation of circular retrofit decision-support systems in the UAE.

Sustainability has increasingly become a crucial aspect of evaluating the performance of supply chain management in the construction sector and an integral component of sustainable development. The UAE construction sector plays a vital role in the country's economic growth and is expected to grow rapidly in the coming years. Yet, the UAE's sustainable supply chain practices have not adequately addressed this industry. Therefore, there is a need to develop a resilient and extensive indicators’ set to track progress toward sustainable supply chain management in the UAE construction sector. This study aims to present a framework that investigates sustainability in the UAE construction supply chain. After a thorough literature review, 32 sustainability indicators were derived and validated according to the triple bottom line and the requirements of different project stakeholders. The developed framework and the resulting set of key performance indicators serve as a solid foundation for assessing sustainable supply chain performance in the construction industry in the UAE, and provide policymakers, construction industry practitioners, and researchers with a validated reference for benchmarking sustainable performance and promoting sustainability.

Buildings in hot climates are major electricity consumers because cooling dominates energy demand. This study evaluates retrofit strategies for an existing hotel in Abu Dhabi using DesignBuilder simulations and two multi-criteria decision methods: Analytic Hierarchy Process and Quality Function Deployment. Five measures were assessed: airtightness improvement, cooling set point adjustment, chiller performance enhancement, glazing upgrade, and wall insulation. The calibrated model achieved acceptable error values, with Normalized Mean Bias Error of 2.61%t and Coefficient of Variation of Root Mean Square Error of 4.88%. Results show that cooling set point adjustment provides the largest energy saving at 9.28%, followed by chiller improvement at 7.66%. Both decision methods ranked the temperature set point retrofit first, highlighting low-cost HVAC optimization as a practical retrofit priority.