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Circular economy (CE) is an emerging concept in the construction industry that focuses on maintaining materials in a continuous cycle to maximize their value. Although previous studies have explored CE in different contexts, there is a lack of studies investigating the relationship between CE barriers and drivers in developing countries. To address this gap, this study aims to identify a list of barriers and drivers of CE adoption and investigate their relationship. The literature review classifies 21 barriers into four constructs, including market policy and technology-related, legal and institutional, supply chain-related, and product design and waste management barriers. Through a questionnaire-based survey with respondents mainly from the Ghanaian construction industry, the research uncovers the most critical barriers within each construct and identifies 13 out of 16 drivers to be critical for CE implementation. The relationship between CE barriers and drivers is found to be significant and substantial, as demonstrated by the path coefficient (β = 0.723) and the p-value (< 0.05). This study's outcomes offer both theoretical and practical implications for academic and industry practitioners, empowering them to craft evidence-based strategies that facilitate successful CE adoption in developing nations. • Comprehensive understandings of the critical barriers and drivers are outlined. • Relationships between barriers and drivers are found to be significant. • Insights may inform data-driven strategies for CE adoption. • Focus on GCI study reveals CE adoption awareness in emerging economies. [ABSTRACT FROM AUTHOR]

• The DT Implementation barriers are categorized under six categories. • The PLS-SEM technique was developed to prioritize DT implementation barriers. • There is a strong relationship between overcoming DT implementation barriers and OSS. • Overcoming DT implementation barriers can enhance construction sustainability by 23 %. A Digital Twin (DT) is a digital copy of a real-world object or process. Although DT has gained traction in construction, its relationship with sustainable success remains insufficiently studied. This research addresses this gap by investigating barriers to implementing DT in sustainable construction. The study employs a hybrid approach involving literature review, expert interviews, and modeling techniques, with data collected from 108 construction experts based on a number of criteria, including the experience, degree, and familiarity of the experts about the Hong Kong building and construction sector Hong Kong. The findings reveal 45 barriers categorized into six clusters, including notable obstacles such as "legacy systems," "data uncertainties," and "connectivity." The key clusters identified are "performance" and "security," while the "social" aspect of sustainable success is least supported. Recognizing these challenges assists decision-makers in navigating obstacles and utilizing DT for environmentally conscious construction, streamlined processes, and positive societal impacts. Future research could delve into integrating sustainability throughout the project lifecycle using technology adoption theories. [ABSTRACT FROM AUTHOR]

Ranking and prioritizing pavement infrastructure for maintenance and rehabilitation have become major undertakings for several departments of transportation around the globe. This is a complex decision-making problem because multiple and conflicting criteria can contribute to the assessment. Multi-criteria decision analysis (MCDA) techniques evaluate the trade-off between several quantitative and qualitative criteria and facilitate complex decision-making. This research introduces a framework based on MCDA to support pavement management decision making, while quantifying emerging sustainability-related factors such as safety, noise, and pollution in the decision-making process. The framework features include 1) identifying pavement management main decision elements: objectives, criteria, and attributes by detailing the problem with a five-level hierarchy structure; 2) employing combined analytic hierarchy process and multi-attribute utility theory to develop representative set of utility functions; and 3) ranking and prioritizing large networks of pavement sections while incorporating sustainability-related criteria. Data used to assess the decision criteria and develop the utility functions is extracted by means of a questionnaire survey completed by professionals working in the field of pavement management. The proposed method is applied to a case study consisting of ten pavement sections extracted from the long-term pavement performance database, wherein the sections are ranked based on their attributes. Sensitivity analysis is performed to evaluate the impact of the different criteria on the ranking process. The proposed method has shown potential in ranking pavement networks based on the identified criteria. Future work can test the performance of the proposed methodology with a full-scale pavement network and apply it to other civil infrastructure assets to evaluate its performance with different types of projects. • Pavement management decision elements (objectives, criteria and attributes) are analyzed. • Integrated AHP-MAUT decision support framework for pavement management is developed. • An intuitive procedure to assess utility is implemented to develop the needed utility functions. • Data extracted from LTPP database is used to demonstrate the application of the proposed framework. • Sensitivity analysis is conducted to assess robustness of the developed method. [ABSTRACT FROM AUTHOR]

Multimodal logistics (ML), which involves multiple transportation modes, has been increasingly used in many Modular integrated Construction (MiC) projects. However, the literature lacks decision support systems (DSS) to simulate, analyze, and optimize ML in MiC (ML-MiC). This paper fills this gap by achieving the following objectives: 1) simulate the internal operations of ML-MiC stakeholders (e.g., manufacturers, logistics service providers, contractors) and their interactions; 2) identify the significant decisions that impact the key performance measures (KPMs) of ML-MiC; and 3) obtain the near-optimum decisions that improve the sustainability of ML-MiC. These objectives are achieved by developing a holistic modelling approach that integrates three methods. First, hybrid multi-agent simulation models the communications between ML-MiC stakeholders and their internal operations. Second, design of experiments (DOE) reveals the main and interaction effects between logistics and construction decisions that significantly affect KPMs, such as the project duration, total costs, and carbon emissions. Third, metamodeling finds the near-optimum logistics and construction decisions (e.g., trucks' number, their dispatching time, ship capacity, inventory, resource planning) that enhance KPMs. The developed approach is applied to a real case study. The DOE analysis indicates that some logistics decisions significantly influence construction KPMs (e.g., project duration, construction costs, construction emissions) and vice versa, calling for more collaboration between stakeholders. Also, the optimized solutions reduce the project duration, total costs, and emissions by 28%, 50%, and 17%, respectively. This paper contributes by integrating three methods to model ML-MiC and enable its stakeholders to discern the impact of their decisions on multiple KPMs and optimize them toward more sustainable MiC. Given this paper's findings, future researchers are urged to investigate the success factors and barriers to applying ML in MiC. Also, the paper emphasizes the need to develop DSS that achieve a win-win collaboration and enhance communication between ML-MiC stakeholders. • Multimodal logistics (ML) are used to import modular units from overseas factories. • The literature lacks models to assess, analyze and optimize ML-related decisions. • A developed multi-agent model evaluates multiple project performance measures (PMs). • A diagnostic analysis reveals the significant ML decisions that impact each of PMs. • Metamodeling finds the optimum ML decisions to improve PMs of modular construction. [ABSTRACT FROM AUTHOR]

Developing a sustainable community is mainly contingent upon energy infrastructure driven by energy alternatives. It has been attempted to accomplish energy sustainability by just ranking energy alternatives. In the current work, an integrated decision support tool (IDST) and multi-level hierarchical structure (MLHS) are developed to instigate new notions for energy alternatives. The developed IDST is unique in dealing with two-dimensional assessment information and can also concurrently analyze hybrid information. The MLHS comprises eighteen attributes grouped into five sustainability aspects (operational, economic, technological, environmental, and social) to assess energy alternatives, including gas, coal, nuclear, solar, hydro, wind, and biomass. Firstly, the importance of attributes is calculated using the optimal weighting approach. Then, the ranking of alternatives is determined and validated. Lastly, the multi-facet performance of alternatives is assessed in terms of distributed performance and indexing using the probabilistic evidential reasoning algorithm, and the acceptability of alternatives is classified. The results revealed hydro is the most favorable energy alternative for achieving sustainability, followed by solar and wind, with a 'very good' index overall. The developed framework is useful for designing sustainable hybrid energy infrastructures and for intergovernmental organizations to draft long- and short-term policies for achieving the energy sustainability targets of SDG-7. • Constructed critical success factors for energy system quantitatively. • Evidential reasoning driven integrated multi-attribute decision tool is used. • Two-dimensional and hybrid assessment information of factors is used concurrently. • Sustainability is evaluated using some new notions in energy domain. • Long- and short-term policy recommendations for energy sustainability in Pakistan. [ABSTRACT FROM AUTHOR]

One of the main components of smart and sustainable urban management is well-performed sewer networks. Therefore, maintaining and enhancing the functionality of sewer projects at an affordable cost are major challenges for decision-makers. However, the embracement of the Value Engineering (VE) concept to assess new sewer designs has not yet been fully embraced especially in developing countries. Thus, this study introduces a systematic VE approach for major sewer projects. A computer model based on six phases of VE methodology was developed, and named "Value Engineering Model" (VEM). To show its efficacy, it was applied to a real-life case study, leading to the following major contributions to the body of relevant knowledge: (1) unraveling the logical relations between the project functions, (2) a detailed life cycle cost analysis (LCCA), (3) a weighted evaluation matrix towards facilitating the decision-making procedure and (4) achieving an approximate 36% reduction in the sewer's project cost as compared to the common VE analysis technique. The developed model serves as a guide for design engineers and decision-makers in sewer projects. It will enable achieving the embracement of smart and sustainable drainage systems within cities at a greater pace. The results of this study will be a guide for decision-makers to reduce costs and improve sustainability by introducing VEs in the Egyptian sewer industry. • A new inclusive value engineering model for major sewer projects is developed. • The logical relations between the project functions are unravelled. • A detailed life cycle cost analysis (LCCA) of sewer projects is provided. • A weighted evaluation matrix towards facilitating the decision-making procedure is developed. • An approximate 36% reduction in the sewer's project cost is achieved. [ABSTRACT FROM AUTHOR]

Modular Integrated Construction (MiC) has recently grabbed the attention of numerous researchers and practitioners across the globe, even though their adoption on construction sites has led to some critical safety hazards that differ from those of common construction projects. In this regard, cranes are the most widely utilized equipment used in MiC projects; however, there have not been any studies carried out on the safety issues of cranes in such projects. Lack of such consideration not only leads to overshadowing the greater adoption of MiC-based technologies, but also worsens the safety and health of related workers. Considering this, a Crane Safety Index (CSI) is developed in this study to improve the Occupational Health and Safety (OHS) of such projects, which is based on experts' interviews together with the exploitation of the analytical hierarchy process. To validate the efficacy of the proposed CSI, its application to the case of three MiC-constructed projects was considered. Applying the CSI developed to the selected projects, the following contributions are noted: (1) identification of safety factors playing role in the safety of crane operations that are peculiar to the MiC projects, (2) obtaining a specific safety score for crane operations in MiC projects, and (3) determination of fruitful technologies improving the OHS of related operations. The outcomes of this study provide the related safety decision-makers with an inclusive plan for promoting the embracement of sustainability at a greater pace by improving the well-being of workers. • A crane safety index related to the MiC projects is developed for the first time in the relevant literature. • All the factors that are peculiar to the safety of crane operations in MiC projects are identified. • The identified factors are analyzed using Analytical Hierarchy Process. • Bunch of fruitful recommendations to improve the respective OHS operations are put forward. • The suitability of the developed safety index is shown through its application to case studies. [ABSTRACT FROM AUTHOR]

Off-site construction (OSC) is an innovative and sustainable construction method. One of its critical success factors is the proper management of its supply chain (SC). Recently, significant research attention has been focused on the modelling of OSC-SC to improve its performance and sustainability. However, the literature still lacks a comprehensive review of the modelling studies on off-site construction -supply chain management (OSC-SCM). Therefore, this research contributes by providing a comprehensive and up-to-date mapping and clustering of 309 journal articles on the modelling of OSC-SC to identify its trends and gaps, and hence, highlight future research opportunities. To achieve these objectives, a mixed review method, consisting of scientometric and systematic reviews, is used. The scientometric review identifies the most prolific journals, researchers, co-occurrence network of keywords, and their citation bursts. On the other hand, the systematic review classifies the articles based on OSC type and supply chain (SC) stage. At each SC stage, the articles are further classified based on problem settings and solution methods. The results show that production problems have received the most attention (i.e., by 28% of the included articles), followed by on-site construction (19%), design (13%), and logistics (7%) problems. However, researchers are more inclined to address problems at multiple SC stages (33%) due to the interrelationship between these stages. Besides, the systematic analysis shows that OSC-SC problems have been solved frequently by a variety of solution methods such as optimization (25%), simulation (13%) and building information modelling (BIM) (9.5%). However, researchers tend more to integrate multiple solution methods (35%) to address the complexities of OSC-SC problems. Finally, the included studies are classified based on the three sustainability dimensions. The results show that economic, environmental, and social sustainability dimensions have been considered in previous studies by 72%, 24%, and 4%, respectively. Therefore, the study identifies research gaps at each SC stage of each OSC type to incentivize future studies to consider more environmental and social sustainability factors in OSC-SC models. Since modular integrated construction (MiC) has the highest prefabrication level, this study provides future research directions for sustainable supply chain management (SCM) in MiC. The present research is an important reference guide that helps researchers and practitioners to understand different problem settings and their solution methods in OSC-SCM. [Display omitted] • Modeling of off-site construction supply chain management (OSC-SCM) is surveyed. • A scientometric review shows trendy and hot research topics in the modelling of OSC-SCM. • Studies are summarized and classified based on problem settings and solution methods. • Most of OSC-SCM models focused on the economic sustainability. • Future research directions to include other sustainability dimensions are provided. [ABSTRACT FROM AUTHOR]

Sustainability principles should be implemented during all the phases of the decision-making process of constructing residential buildings to achieve maximum gains without compromising the function of such projects. This study identified and examined the critical success factors (CSFs) required for implementing value management (VM) in residential building projects. With a view to the sustainability of such the projects. The CSFs for VM were identified from previous studies, which were then contextually adjusted using both semi-structured interviews and a pilot study via the Exploratory Factor Analysis (EFA) technique. The EFA results showed that the VM CSFs could be categorized into four constructs: stakeholders and knowledge, culture and environment, workshop dynamics, and standardization. Questionnaires were then administered to 214 building stakeholders within the Egyptian building industry. Partial least square structural equation modelling (PLS-SEM) was used to develop the CSFs model. Despite that Egyptian professionals with limited practice experiences were quite knowledgeable about VM, results showed that stakeholders and knowledge were crucial CSFs for implementing VM. The results of this study will be a guide for decision-makers to reduce costs and improve sustainability by introducing VMs in the Egyptian construction industry. • Partial least squares-structural equation models (PLS-SEM) for predicting the impact of critical success factors (CSFs) for value management (VM) were validated. • The VM knowledge and awareness among Egyptian residential building practitioners are in a moderate to a high level. • Established that most Egyptian residential building practitioners did not practice VM in their projects. • Stakeholders and knowledge, culture and environment, workshop dynamics, and standardization identified as CSFs for VM. • The proposed PLS-SEM model priorities the VM CSFs and Offering VM implementation "road map" for sustainable residential building success. [ABSTRACT FROM AUTHOR]