Search Results (54)

Digitalisation is transforming organisational practices, making digital readiness essential for strategic planning. However, customised digital maturity tools for the Irish Architecture, Engineering, Construction, and Operations (AECO) sector remain limited. This paper presents the development and validation of a Digital Maturity Gap Analysis Toolkit (DMGAT) for the Irish AECO sector. The toolkit assesses digital maturity across three dimensions—people, process and culture; technology; and policy and governance—covering 16 sub-dimensions and 69 assessment questions. Unlike existing tools such as the BIM Maturity Matrix, VDC BIM Scorecard, and Maturity Scan, the DMGAT uniquely integrates ISO 19650 maturity stages with a comprehensive maturity level matrix across three key dimensions, offering a customised, industry-specific assessment for the Irish AECO sector that combines structured benchmarking with actionable gap analysis. The toolkit supports gap analysis by comparing an organisation’s current maturity profile with the detailed descriptors of higher maturity levels (maturity level matrix), thereby enabling prioritised and context-specific improvement planning rather than pursuit of a uniform maximum level. The study uses a mixed-methods approach within a Design Science Research (DSR) framework, developing the tool across six phases: literature review, defining dimensions and key performance indicators (KPIs), prototype development, testing, refining and finalisation, and deployment for practical application and empirical evaluation within real organisational contexts in the Irish AECO sector, demonstrating its use as an operational diagnostic and learning tool. Alpha testing by the organisational research team refined structural enhancements including maturity stages, KPIs, and maturity matrix. Beta testing with 20 Irish AECO organisations confirmed the toolkit’s relevance, scope, and coverage. Participants highlighted its clarity and industry alignment, while suggesting minor improvements in wording, visuals, and support materials. This study concludes that DMGAT is a useful resource for informed decision-making and digital innovation in the Irish AECO sector. Full article

The implementation of digital twin (DTw) in infrastructure management is becoming increasingly important. Although digitalization in the Architecture, Engineering, Construction, and Operations (AECO) sector is progressing slowly, enabling technologies such as Building Information Modelling (BIM), Geographic Information Systems (GIS), Internet of Things (IoT) and data management allow for more informed and efficient management of ageing and highly complex assets. With the aim of improving the operation and maintenance (O&M) of transport infrastructure, the use of an integrated BIM–GIS model is proposed as the basis for a future DTw for an existing highway, the M-30 urban ring road in Madrid. This study develops an as-built digital model based on real GIS data, point clouds and BIM (LOD 300), adapting it to existing management systems using a relational database with unique identifiers. The infrastructure is modelled in a segmented and georeferenced manner, incorporating roads, tunnels, bridges and equipment as independent entities. Access to the model is guaranteed through 3D GIS scenes, interactive panels and BIM viewers geared towards management. In addition, a cost–benefit analysis is carried out using a Return On Investment (ROI) that evaluates the implementation of BIM in the management of this infrastructure. Full article

Digital construction implementation has not yet realized its promised potential after three decades. Across the entire project lifecycle, adoption has encountered difficulties from high-level standard guidance, a lack of strategies, fragmented delivery approaches, and insufficient digital delivery competency. Establishing digital workflows tailored to organizations’ contexts is an essential linkage of the information layer to synthesize the business and technology layers to address these challenges within the ISO 19650 framework. The uneven implementation of building information modelling (BIM) in the Architecture, Engineering, Construction, and Operation (AECO) industry provides a holistic perspective to consider the digitalization workflow dynamics. This report performs a case study through a parallel approach to examining multiple projects’ digital construction implementation of an organization in the Forest City development. Applying an observation research method and real-world data of project records, it analyses its workflows’ digitalization and process digitization, combining with its organization’s structure and overall project strategy. Moreover, it highlights bespoke digital construction ecosystems and relevant stakeholders to streamline workflows. The digital construction implementation results and project benefits as project context indicators verify that fundamental digital workflows of design quality checking, project optimization, asset data collection, and defect management have significant applicability compared with the advanced workflows of integrated 5D cost management and precast design and production. Their adoptability keeps consistency with those of applicability using the extra cost, application complexity, and disruption level indicators from the technology–organization–environment (TOE) framework to measure. These multiple project studies reveal the feasibility for organizations to achieve lifecycle digital construction implementation competency. The feasibility is underpinned by introducing an in-house digital engineering team to organization structure, cultivating applicable digital delivery capabilities through workflows digitalization and process digitization, and synthesizing ISO 19650 with workflows to enable more contextualized digital construction implementation. Full article

Globally, the architecture, engineering, construction, and operations (AECO) industry faces rapid urbanization and environmental urgency. However, developing economies often lack the strategic capacity to utilize BIM for sustainable development. This study addresses this gap by developing a strategic, evidence-based BIM adoption framework tailored to the Mongolian context. Originating in the health sector, the ADAPTE process is a systematic method that enables the cost-effective adaptation of existing high-quality guidelines to new target contexts. The research applies a framework adaptation methodology, based on the adaptation phase of the ADAPTE process, to recontextualize benchmark international strategies for the specific environment of Mongolia. In the result, our work proposes a national BIM adoption framework which follows a three-phase implementation timeline (2027, 2030, and 2035) as per ISO 19650 maturity stages. Additionally, it has a three-point action plan of policy/legal systems, common resources, and promotion in the sphere of industry, people, and technology. The result offers a practical framework for Mongolia to advance the adaptation of BIM practices, positioning digital transformation as a catalyst for sustainable development. Furthermore, the methodological framework developed in this work serves as a scalable blueprint for other developing economies to systematically craft their own context-specific strategies. Full article

As noted in recent blockchain review articles, several blockchain studies have attracted attention to the architecture, engineering, construction, and operation (AECO) industry. The reason is that blockchain offers opportunities to revolutionize the AECO industry owing to its transparency, traceability, and immutability. However, these benefits cannot be realized without blockchain “oracles”. Oracles are intermediary agents that connect blockchain systems to real-world applications. They function by collecting and verifying off-chain data, which is then fed into the blockchain for use by smart contracts. To investigate this uncharted territory, this paper adopts a hybrid research method of descriptive, bibliometric and content analysis; cross-mapping; and gap analysis to identify the trend; key topics; current status; future directions; and governance, ethical, legal, and social implications (GELSI) framework of blockchain oracles. This paper contributes to the body of knowledge by synthesizing trends, current status, key topics, and GELSI of blockchain oracles, promoting areas of improvement, and bridging knowledge gaps on blockchain oracles in the AECO industry. Full article

The construction industry faces persistent productivity challenges despite the widespread adoption of advanced digital technologies. This systematic review examines how digital technologies contribute to improving on-site labor productivity within the Architecture, Engineering, Construction, and Operations (AECOs) sector. Following the PRISMA methodology, 431 records were initially identified, with 28 high-quality articles ultimately selected for analysis through rigorous screening and snowballing techniques. The reviewed technologies include Building Information Modeling (BIM), photogrammetry, LiDAR, augmented reality (AR), global navigation satellite systems (GNSSs), radio frequency identification (RFID), and unmanned aerial vehicles (UAVs), which were categorized into three key areas: factors affecting productivity, modeling and evaluation, and productivity improvement methods. Findings highlight that these technologies collectively enhance resource allocation, reduce labor costs, and improve project scheduling through better coordination. Whilst digital technologies demonstrate substantial impact on construction productivity, further research is needed to quantify long-term benefits and address scalability challenges across different project contexts and organizational structures. Ultimately, the review concludes that digital technologies play a crucial role in enhancing construction productivity, highlighting the need for further research to assess long-term advantages and scalability across diverse construction environments. These technological advancements are essential for modernizing the industry and supporting sustainable growth in the digital transition era. Full article

The architectural, engineering, construction, and operation (AECO) sector is one of the main contributors to energy consumption and greenhouse gas emissions in Europe, making the renovation of the existing building stock a priority. However, defining effective and economically sustainable interventions remains a challenge, partly due to the variability of building characteristics and the lack of digital tools to support data-driven decision making. This research aims to identify the main factors influencing the energy consumption of buildings by analyzing a large database of building characteristics using machine learning algorithms. Based on the parameters that the analysis shows to have the greatest impact, the average cost of energy retrofitting measures will be used to elaborate a cost–benefit analysis model and the economic payback time for each measure, individually or in combination. The expected result is the creation of a tool that will allow the operator to evaluate the choice of interventions based on the energy efficiency that can be achieved and/or the economic sustainability. The proposed methodology aims to provide a digital approach that is replicable and adaptable to different territorial realities and useful for strategic planning of energy transformation in the building sector. Full article

The integrative and transformative potential of Building Information Modeling (BIM) has significantly expanded employment opportunities in the construction sector. This study investigates the consistency between BIM-related job market demands and the UNI 11337-7 role definitions in Italy, contributing to the broader dialogue on the alignment between employment, policy, and education. A dataset of 261 BIM-related job advertisements collected from LinkedIn in the Italian context was analyzed using a term frequency-based methodology. Reference keyword sets derived from the UNI 11337-7 standard were established for the BIM Specialist, BIM Coordinator, BIM Manager, and CDE Manager roles. The analysis reveals a significant misalignment: only 30% of the advertisements clearly reflect the competencies defined by the standard, while 70% appear vague or inconsistent. These findings suggest limited awareness or uneven application of BIM role definitions within the industry. This study offers a quantitative assessment of the alignment between employment demand and professional standards and proposes a replicable method for benchmarking job market data. It also highlights the need for clearer communication and stronger implementation of standardized professional roles to effectively support the digital transformation of the construction sector. Full article

Generative artificial intelligence (GenAI) is a tool that can be applied to virtually all aspects of business and life, including the construction industry. However, the adoption of GenAI in the construction industry, as with other innovations, is slow, and many of its applications thus far have been rather simplistic or failed to deliver a useful, credible output. There is a limited understanding of how GenAI is adopted in current practice and its potential to improve future practice in architecture, engineering, construction, and operations (AECO). Using a systematic literature review approach, this study aims to map the current issues in applying GenAI. The literature review initially identified 1013 peer-reviewed articles from ProQuest, Scopus, and Web of Science. The articles were further filtered based on specific criteria, resulting in 28 articles being retained for thematic analysis. The findings show a cluster of patterns in which GenAI is being adopted and shows promise. The core themes identified are as follows: (1) project brief, (2) architectural design, (3) building information modelling, (4) structural design, (5) construction and demolition, (6) operations, and (7) urban governance. A typical trend noted in the AECO industry has been training AI models that achieve quicker results, improve quality, and use fewer resources. Full article

The AECO (Architecture, Engineering, Construction, and Operation) sector is highly complex, involving multidisciplinary collaboration, extensive data management, and significant financial investments. Decisions in early phases significantly impact operational and maintenance costs, as well as the environmental and economic sustainability of a project over its lifecycle. Cost efficiency and sustainability are critical and interconnected goals across the sector, spanning all phases of a building’s lifecycle. Ontologies, as formal and structured representations of knowledge within a particular domain, have the potential to enhance cost efficiency by improving decision-making, reducing redundancies, and optimizing resource allocation. Despite their relevance, cost ontologies are still lacking in the AECO sector. This paper addresses this gap by presenting both a methodological and conceptual contribution: it outlines a structured and iterative methodology for developing a cost ontology, and it defines the core concepts required to semantically represent construction cost information. The methodology emphasizes stakeholder engagement and refinement cycles, while the ontological structure ensures machine-readability and interoperability. The approach involves a preliminary analysis of the necessary cost parameters for defining the ontology and a subsequent validation of a practical case study. The results show the development of a heterogeneous and standardized data structure designed to define a cost ontology, aimed at improving the updatability, transparency, and sustainability-oriented interpretation of construction cost data by both humans and machines. Full article

As projects in the architecture, engineering, construction, and operations (AECO) industry grow in complexity and scale, there is an urgent need for more effective information management and intelligent decision-making. This study investigates the potential of large language models (LLMs) to address these challenges by systematically reviewing their core technologies, application scenarios, and integration approaches in AECO. Using a literature-based review methodology, this paper examines how LLMs—built on Transformer architecture and powered by deep learning and natural language processing—can process complex unstructured data and support a wide range of tasks, including contract analysis, construction scheduling, risk assessment, and operations and maintenance. This study finds that while LLMs offer substantial promise for enhancing productivity and automation in AECO workflows, several obstacles remain, such as data quality issues, computational demands, limited adaptability, integration barriers, and ethical concerns. The paper concludes that future research should focus on improving model efficiency, enabling multimodal data fusion, and enhancing compatibility with existing industry tools to realize the full potential of LLMs and support the digital transformation of the AECO sector. Full article

Building information modeling (BIM) has revolutionized integrated planning by optimizing costs, schedule, and material use. However, building energy modeling (BEM) remains underutilized in early design stages due to interoperability challenges between BIM and BEM tools. This study addresses these challenges by exploring standardized exchange requirements and introducing a novel toolchain that bridges BIM and BEM workflows. In the BIM2IndiLight project, over 400 standardized properties for daylighting, artificial lighting, and façade systems were validated, revealing the advantages and limitations of parameter standardization. Building on these insights, the BIM2BEM-Flow project developed a three-step toolchain that efficiently manages project- and company-specific properties, defines mapping rules, and integrates parameters via a BIM plugin for validated IFC export. The results demonstrate that combining standardized properties with a flexible, workflow-driven toolchain significantly enhances data exchange and interoperability between BIM and BEM. This integrated approach supports early-stage energy performance optimization and offers a promising pathway toward more efficient design processes in the AECO industry. Full article

The AECO industry is currently undergoing a digital transformation, and leadership and trust are considered important factors in the successful use of digital work systems within organizations. There are indications that certain leadership qualities can promote trustful use of digital work systems; however, there is limited research on what these specific characteristics are. Therefore, it is of interest to investigate which aspects of leadership specifically promote the trustful use of digital technologies. The purpose of this study was to investigate which aspects of leadership are associated with trustful use of digital work systems. Various aspects of leadership in digital transformation were investigated in a way that has not been carried out before in the construction industry. An online survey was completed by 314 experts from various fields of expertise at Sweden’s largest infrastructure owner. The main findings showed that the most important factors for the trustful use of digital work systems were role clarity and digital literacy of the management team. It is recommended that the construction industry educate management teams about the implications of digital transformation in terms of new technologies and changing work practices and roles. This will help managers support employees by clarifying their roles and responsibilities in a complex organization. Full article

The growing focus on operational energy efficiency in the building sector has revealed a critical gap in addressing embodied impacts—carbon emissions and energy demands associated with the production, construction, use, and end-of-life stages of buildings. This research addresses this gap by introducing an integrated framework encouraging collaboration across academia, industry, and policymakers. Based on a systematic analysis of current research, the study identifies trends and provides actionable recommendations to enhance embodied impacts assessments. The findings reveal limited representation in key areas like Building Information Modeling (BIM) and policy frameworks, alongside a strong geographical imbalance in research, with 60% of the investigations originating from only five countries. Life cycle stages beyond “cradle-to-gate” remain marginally explored, with only 39% concerning end-of-life or reuse phases. Moreover, 65% of stakeholder engagement is confined to LCA specialists and building designers, highlighting the need for broader participation. This study proposes a comprehensive framework promoting a holistic approach to embodied impacts, advocating their integration into academic curricula and urging industry professionals to adopt collaborative and sustainable practices. By clarifying sectoral gaps and outlining targeted pathways for integration, this study provides a foundation for translating embodied impact research into practical application and regulatory frameworks. Full article

This study evaluates the carbon footprint of three bio-concrete families—wood (WBC), bamboo (BBC), and rice husk (RHBC)—and their application in wall components (as blocks and as boards). A cradle-to-grave, carbon-focused Life Cycle Assessment (LCA) was used to compare these bio-concretes to conventional masonry and industrialized light-framing solutions. Each bio-concrete family incorporated biomass volumetric fractions of 40%, 45%, and 50%, using a ternary cementitious matrix of cement, rice husk ash, and fly ash (0.45:0.25:0.30). Sensitivity analyses examined the impacts of transport distances and the parameters affecting biogenic carbon storage, such as carbon retention periods in the built environment. The carbon footprint results demonstrated a significantly low or negative balance of emissions: WBC ranged from −109 to 31 kgCO₂-eq./m³, BBC from −113 to 28 kgCO₂-eq./m³, and RHBC from 57 to 165 kgCO₂-eq./m³. The findings emphasized the importance of ensuring bio-concrete durability to maximize biogenic carbon storage and highlighted the environmental advantages of bio-concrete wall systems compared to conventional solutions. For instance, BBC boards replacing fiber cement boards in light-framing systems achieved a 62 kgCO₂-eq./m² reduction, primarily due to the production (A1–A3) and replacement (B4) stages. This research outlines the emission profiles of innovative materials with the potential to mitigate global warming through circular construction, offering a sustainable portfolio for designers, builders, and AECO professionals seeking non-conventional solutions aligned with circular economy principles. Full article