Timely approvals and payments to the project participants are crucial for successful completion of construction projects. However, the construction industry faces persistent delays and non-payments to contractors. Despite the desirable benefits of automated payments and enhanced access to digitized data progress, most payment applications rely on centralized control mechanisms; inefficient procedures; and documentation that takes time to prepare, review, and approve. As such, there is a need for a reliable payment automation system that guarantees timely execution of payments upon the detection of completed works. Therefore, this study used a cutting-edge approach to automate construction payments by integrating blockchain-enabled smart contracts and scan-to-Building Information Modeling (BIM). In this approach, scan-to-BIM provides accurate, real-time building progress data, which serve as the source of verifiable off-chain data. A chain-link is then used to securely relay these data to the blockchain system. Blockchain-enabled smart contracts automate the execution of payments upon meeting contract conditions. The proposed approach was implemented on a real case study project. The actual site scan was captured using a photogrammetry 360° camera, which uses a combination of structured light and infrared depth sensing technology to capture 3D data and create detailed 3D models of spaces. This study leveraged accurate, real-time building progress data to automate payments using blockchain-enabled smart contracts upon work completion, thus reducing payment disputes by tying payments to verifiable construction progress, leading to faster release of payments. The findings show that this approach provides a transparent basis for payment, enhancing trust and allowing precise project progress tracking.

Green buildings are playing a pivotal role in sustainable urban development around the world, including Saudi Arabia. Green buildings subject to various sources of risk that influence the potential outcomes of the investments or services added in their design. The present study developed a structured framework to examine various risks that may lead to green buildings’ value destruction in Saudi Arabia. The framework initiates with identification of 66 potential risk factors from reported literature. A questionnaire compiling a list of identified risk factors was hand-delivered to 300 practitioners (managers, engineers, and architects) having knowledge of value engineering in the construction industry, and an overall response rate of 29.7% was achieved. Subsequently, descriptive statistics ranked the risk factors based on scores given by the respondents. The principal component analysis extracted 16 components, based on the likelihood of risk factors impacting the value created by green building design. Finally, the factor analysis grouped the 35 most significant risk factors in 5 clusters—i.e., 8 in functional risk, 13 in financial risk, 3 in operational risk, 3 in environmental risk, and 8 in management risk cluster. The study enhances the understanding of the importance of the risk factors’ impact on value creation. Based on the results, the value management (or engineering) teams and the top-level management can identify, manage, and control the risk factors that have a significant impact on the project value created by green building design.

The production of cement, which is the key ingredient of concrete, leads to environmental pollution by releasing massive amounts of CO₂ and using significant natural resources. Therefore, shifting towards sustainable and greener materials is essential for mitigating these challenges. In this study, recycled concrete powder (RCP) was used as a cement replacement (0%, 5.0%, 10%, and 15%), solving the waste dumps issue and promoting sustainability. Furthermore, the concrete is also reinforced with steel fibers which were obtained from waste rubber tires to improve concrete tensile strength. The concrete properties were evaluated through slump cone test, compressive strength, failure patterns, tensile strength, scanning electronic microscopy, and FTIR analysis. The results indicate that the concrete strength properties improved with the substitution of RCP. The compressive and tensile strength of the optimum mix (10% RCP and 2.0% addition of steel fibers) are 15.8% and 23% more than those of reference concrete. However, the concrete flow is adversely impacted due to RCP angular particle shapes. Failure patterns indicate that RCP and steel fibers improved concrete ductility. SEM and FTIR analysis indicate microstructural improvement with RCP and steel fibers. Finally, the analysis concluded that the developed concrete showed better performance, solved waste dumps issues, and promoted sustainability.

The sustainability of green buildings has been widely recognized around the world in the recent past. Evaluating the investment on such buildings, with higher complexity than the conventional buildings, involves multiple and diverse stakeholders, such as consultants, contractors, general public, governmental institutions, etc. The selection of useful value creation drivers is a difficult task while accommodating the opinion of a group of stakeholders with varying perceptions and experiences regarding the value creation in green building design and the associated costs. In this research, a framework is proposed to develop a set of the most important value creation drivers (VCDs) for green buildings. Five primary VCDs were developed to cover the financial, functional, operational, environmental, and management aspects of a green building. Ninety-eight (98) performance value drivers (PVDs) were identified through the literature for assessing the performance of these value creation drivers. The identified PVDs were evaluated through a hand-delivered questionnaire survey, followed by detailed statistical analysis of the collected data while using Statistical Package for Social Sciences (SPSS) and Microsoft Excel software. Factor analyses were performed to eliminate the PVDs with least importance based on the responses obtained from 89 experienced managers (45%), engineers (38%), and architects (17%) working in the field of value management of construction industry in Saudi Arabia. Finally, 51 most important PVDs were grouped into two clusters for each value creation driver; for instance, control and planning clusters to assess the performance of management’s VCD. The final outcome of the research in the form of five top level VCDs, 10 clusters, and 51 PVDs will facilitate the designers for enhancing the performance efficiency and value from investment for green buildings in Saudi Arabia, Gulf, and elsewhere.

Green buildings are predestined for the sustainability of arid regions. Presently, professionals working on building construction projects have no assessment tool that integrates value creation and associated risks in the development phase to enhance the value created by green buildings. The present study developed and tested a value creation assessment tool to evaluate the total added value and associated risks that can impact the created value by green building design. The tool consisting of 51 performance value drivers and 35 risk factors was tested on three different buildings in Saudi Arabia. Using a questionnaire survey, each of these projects was scored by its value engineering team and weighted mean scores (Wms) as percentages were calculated. The study revealed that the environmental driver was given less importance in the design process with Wms of less than 60% for all three types of buildings, while the functional driver was given higher importance with Wms of 80% or more. All the buildings showed moderate financial risks ranging between 40 and 50% and a higher potential of management risks with scores around 60% or higher. A wide variation between 20 and 60% was observed for operational risks. The study also found that large‐scale buildings are less threatened by financial risks. The developed tool will facilitate the stakeholders and designers in identifying project development contextual issues and provide opportunities to optimise the design and operations to enhance performance efficiency and obtain more value from investment in GB assets during the early stages of development in Saudi Arabia and elsewhere.

An assessment of construction activities related to pollution needs to be conducted during the planning of a given project. Such an assessment is essential to ensure that the resulting pollution does not surpass the environmental threshold limits. This research provides an optimized pollution-based scheduling model in construction projects by applying Genetic Algorithms (GAs). The suggested approach figures out the pollution produced by gasses, noise, and dust for each activity in the project. Then, the whole project’s duration is minimized by optimizing the project schedule using GAs while keeping the different pollutants under threshold limits. In the developed model, each pollutant is handled as a dummy resource and is incorporated into the schedule of construction projects. When the emitted pollutants surpass the allowable limits, as per the given regulations, GAs re-schedule the project tasks so that the pollution levels are reduced and redistributed. The proposed framework is presented as being practically applicable through an actual case study. The results show that the proposed GA model improves the pollution leveling process more efficiently than the standard resource leveling technique in Microsoft Project, producing fewer pollution histogram moments of the X and Y axes with 9.4% and 2.2%, respectively. Sensitivity analysis reveals that the best solutions for this case study are obtained when population size, offspring generation, crossover rate, and mutation rate equal 100, 50, 0.95, and 0.05, respectively. The model can aid in reducing construction projects’ environmental impact during the project planning and construction stages, which benefits decision-makers and project planners.