Large Construction Projects Research Articles

Configurational Path to Collaborative Innovation in Large and Complex Construction Projects

Collaborative innovation contributes to sustainable development in many industries. Although there is a growing literature on collaborative innovation, it is still unclear whether and how configurations of drivers affect collaborative innovation in large and complex construction projects (hereafter megaprojects). This research adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore multiple conjunctural causations of collaborative innovation in megaprojects. The findings show that four equifinal solutions can influence collaborative innovation in megaprojects, i.e.: “system innovation-oriented” (configuration 1), “radical innovation-oriented” (configuration 2), “second-tier supplier oriented” (configuration 3), and “modular or architectural innovation-oriented” (configuration 4). This study contributes to explaining the mechanisms regarding how configurations of drivers contribute to collaborative innovation in megaprojects. It also contributes to the development of collaborative innovation research in a construction project context. The research findings provide construction project managers with four useful suggestions for promoting collaborative innovation in megaprojects.

Performance Evaluation of Concealed Beams in Reinforced Concrete Slabs: A Focus on Load-Carrying Capacity and Deflection

The utilization of hidden beams in large span reinforced concrete slab construction has gained attention as a potential solution to mitigate excessive deflection. However, the absence of explicit mention in standard civil engineering literature, codes, and standards raises questions regarding its effectiveness. This paper presents a performance-based analysis of two different cases of slab arrangements involving hidden beams, employing REVIT and ROBOT Structure software. The analysis considers dead and live load combinations in accordance with the design guidelines specified in BS8110. The results of the performance-based analysis demonstrate a significant 10% reduction in the span moment for slabs incorporating hidden beams, indicating their potential to reduce deflection. However, the differences observed in terms of support moment, deflection, and stress patterns within the slabs are not significant. These findings suggest that the presence of hidden beams yields only a slight but meaningful impact on reducing deflection. Considering the observed benefits, it is recommended to cautiously consider the use of hidden beams in large slab construction projects. However, additional research and analysis are necessary to assess other factors such as specific project requirements, cost implications, structural integrity, and construction feasibility. Further investigations should encompass a broader range of parameters, including different load combinations, variations in hidden beam width, and comprehensive cost analysis. By conducting thorough evaluations, a more comprehensive understanding of the effectiveness and feasibility of hidden beams in reducing deflection in large slab construction can be obtained, facilitating informed decision-making regarding their utilization.

Оптимизация безопасности на стройплощадках с использованием искусственного интеллекта для распознавания строительной техники

The paper explores the application of artificial intelligence (AI) to identify construction equipment using CCTV cameras on construction sites. The main goal is to increase safety levels, optimize construction processes and increase productivity. The research covers the analysis of world and Russian experience in creating neural networks, collecting data on construction equipment and developing an AI model for recognizing and classifying machines based on their visual characteristics. The system was also tested to evaluate its accuracy and efficiency. The article discusses various approaches to training neural networks, including supervised and unsupervised learning, reinforcement learning, transfer learning, generative adversarial networks, convolutional and recurrent neural networks, autoencoders, and hybrid models. Particular attention is paid to integrating AI with other aspects of construction site safety, including alarm systems, emergency response and personnel training. This research proposes a multi-layered approach to construction site safety, ensuring not only accident prevention but also improved work processes. Ultimately, the application of AI on construction sites helps create a safer, more organized and controlled work environment, which is critical for large construction projects.

Occupational safety risk analysis in construction sites based on fuzzy analytic hierarchy process: A case study in a large construction project.

Construction projects are one of the most critical occupational sectors that experienced many challenges in occupational accidents and safety performance. This study was designed to assess safety risk in construction projects based on fuzzy analytic hierarchy process. This study was conducted with 12 construction and occupational safety experts in one of the largest construction projects in Tehran-Iran in 2020. The process of this study included (1) risk identification, (2) measurement of risk parameters and sub-parameters, and (3) risk assessment based on a fuzzy analytic hierarchy process. Risk-forming parameters in this study included the probability and severity of the event. The probability of occurrence was estimated based on four sub-parameters of technical inspection, accident experience, detection probability, and human reliability. Sub-parameters of severity included human injury, cost imposition, tarnishing the organization's esteem, and impact on project timing and work stoppage. Twenty-eight identified hazards were examined in the studied construction project, including falling from a height (9-hazard), falling objects (2-hazard), electric shock (6-hazard), falling crane or load (6-hazard), elevator crashes (2-hazard), and soil fall (3-hazard). Safety risk assessment revealed that 27 risk sources were at the tolerable level and one risk source was unacceptable. This study demonstrated that the risk levels in the studied construction project were tolerable and unacceptable. The obtained model in this study demonstrated that using parameters that determine the probability and severity of risk according to the nature of the working environments can be a practical step in risk evaluating and implementing control measures.

Developing a model of work duration under the influence of risk events in the implementation of life cycle contracts for large energy construction projects

Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.

Forecasting project success in the construction industry using adaptive neuro-fuzzy inference system

Project managers often find it a challenge to successfully manage construction projects. As a result, understanding, evaluating, and achieving project success are critical for sponsors to control projects. In practice, determining key success factors and criteria to assess the performance of construction projects and forecast the success of new projects is difficult. To address these concerns, our objective is to go beyond the efficiency-oriented project success criteria by considering both efficiency- and effectiveness-oriented measures to evaluate project success. This paper contributes to existing knowledge by identifying a holistic and multidimensional set of project success factors and criteria using a two-round Delphi technique. We developed a decision support system using the Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast the success of mid- and large-sized construction projects. We gathered data from 142 project managers in Australia and New Zealand to implement the developed ANFIS. We then validated the constructed ANFIS using the K-fold cross-validation procedure and a real case study of a large construction project in Western Australia. The forecasting accuracy measures R2=0.97461, MAPE = 2.57912%, MAE = 1.88425, RMSE = 2.3610, RRMSE = 0.03149, and PI = 0.01589 suggest that the developed ANFIS is a very good predictor of project success.

An analysis of safety practices for small, medium, and large construction projects: A resilience engineering perspective

The varied nature of the construction industry, involving projects of different sizes, poses significant challenges to improving its Occupational Health and Safety (OHS) performance. The existing literature identifying strategies for improving the performance of small construction projects has focused on a deterministic and reactive view of safety. However, recent theoretical advancements in safety criticize this view. Alternatively, a Resilience Engineering (RE)-based perspective is deemed suitable for construction projects to be adaptive in managing safety. However, none of the previous studies analyzed the prevalence of RE-based attributes within the construction industry and across projects of different sizes. This study has adapted a RE-based questionnaire to which 180 survey responses from site professionals were obtained. A concurrent triangulation mixed method was used to analyze this data, supplemented with 16 interviews and field observations from 27 building construction projects in India. The 'contract value' was used as a metric to aggregate the responses for three project types, i.e., 'small', 'medium', and 'large'. The study results indicate that most practices promoting RE-based attributes, such as Monitoring, Learning, and Anticipating, are neither prevalent in the industry nor are significantly different among projects of various sizes. The findings show that small and medium-sized projects may exceed larger projects in several RE-based safety practices, suggesting that pathways to improve safety for smaller projects may not necessarily be limited to emulating larger projects, as typically recommended in the literature. The study advances the understanding of RE-based safety practices and supports safety initiatives in all construction sites.

Dynamic Optimization of Construction Time-Cost for Deep and Large Foundation Pit Based on BIM Technology and Genetic Algorithm

With the increasingly fierce market competition, optimizing the construction time-cost of deep and large foundation pit construction projects has become one of the key factors for construction enterprises to remain invincible. By dynamically optimizing the time-cost, the optimal time corresponding to the lowest engineering cost can be found. Based on a comprehensive transportation hub project, considering the time value of capital and the reward and punishment of construction time, a time-cost dynamic optimization model is constructed. Relying on BIM technology, the feasibility of construction plan is analyzed from both qualitative and quantitative perspectives, and the project parameters and resource information is obtained accurately and quickly. Using the MATLAB program, time-cost optimization based on genetic algorithm is carried out, and the static and dynamic optimization results are compared. The results show that the dynamic optimization scheme reduces the total cost by 1.68% while reducing the total construction time by 8.47%. The dynamic optimization scheme extends the construction period by 2 days while reducing the total cost by 89,500 yuan compared to static optimization. The peak value of the fund demand curve before and after optimization has decreased from 128,000 yuan to 127,000 yuan. The time-cost dynamic optimization, considering the time value of capital is more in line with engineering reality, and the optimization results are more reliable and accurate. BIM technology can accurately and quickly obtain project parameters and resource information, solving problems such as complex processes in super deep excavation and huge engineering data statistics. The genetic algorithm can efficiently and accurately search for the optimal solution within the global domain. This study combines BIM technology with the genetic algorithm to solve the dynamic optimization problem of construction period cost for deep and large foundation pits. The research results of this study provide a theoretical reference for the optimization of schedule cost for similar projects.

Cost Forecasting for Building Materials under Conditions of Uncertainty: Methodology and Practice

Most large construction projects face the problem of cost overruns and failures to meet deadlines mainly due to changes in the cost of building materials. A lot of studies proved the high importance of the cost of building materials for the project budget and highlighted a number of factors that determine the cost of materials. However, modern unstable economic dynamics lead to the need not only to observe sufficient accuracy of quantity and cost calculations regarding primary building materials but also to carefully predict the cost, taking into account uncertainty factors (changes in the geopolitical situation, the impact of the pandemic, changes in the technological structure, etc.). This article proposes the use of a calculation and expert methodology for forecasting the cost of building materials on the example of building bars for two regions of the Russian Federation. This study includes a review of literature, which showed the dependence of the dynamics of the cost of construction on the prices of building materials, confirmed the impact of economic and noneconomic factors of the dynamics of prices of building materials and the impact of risk and uncertainty. Based on the literature review, it is also concluded that it is necessary to expertly adjust the results of the economic and mathematical modeling of the building materials’ price trend line under the influence of noneconomic factors of uncertainty. The statistics of the prices of building materials in Russia were analyzed, and the main causes of price dynamics (economic and noneconomic) were identified. The ARIMA model was selected to build a series of dynamics of prices of reinforcement steel, an expert adjustment of the forecast was made taking into account uncertainty factors. The method of calculation and expert forecasting of prices of building materials was proposed, and the forecast of prices of steel reinforcement in the regions of Russia was calculated on its basis. In conclusion, this study demonstrates the algorithm and practical results of forecasting the cost of building materials under the conditions of uncertainty, as well as recommendations for the implementation of predictive analytics tools in construction practice.

Solution of discrete time–cost trade-off problem with adaptive search domain

PurposeExact solution of time–cost trade-off problem (TCTP) by the state-of-the-art meta-heuristic algorithms can be obtained for small- and medium-scale problems, while satisfactory results cannot be obtained for large construction projects. In this study, a hybrid heuristic meta-heuristic algorithm that adapts the search domain is developed to solve the large-scale discrete TCTP more efficiently.Design/methodology/approachMinimum cost slope–based heuristic network analysis algorithm (NAA), which eliminates the unfeasible search domain, is embedded into differential evolution meta-heuristic algorithm. Heuristic NAA narrows the search domain at the initial phase of the optimization. Moreover, activities with float durations higher than the predetermined threshold value are eliminated and then the meta-heuristic algorithm starts and searches the global optimum through the narrowed search space. However, narrowing the search space may increase the probability of obtaining a local optimum. Therefore, adaptive search domain approach is employed to make reintroduction of the eliminated activities to the design variable set possible, which reduces the possibility of converging into local minima.FindingsThe developed algorithm is compared with plain meta-heuristic algorithm with two separate analyses. In the first analysis, both algorithms have the same computational demand, and in the latter analysis, the meta-heuristic algorithm has fivefold computational demand. The tests on case study problems reveal that the developed algorithm presents lower total project costs according to the dependent t-test for paired samples with α = 0.0005.Research limitations/implicationsIn this study, TCTP is solved without considering quality or restrictions on the resources.Originality/valueThe proposed method enables to adapt the number of parameters, that is, the search domain and provides the opportunity of obtaining significant improvements on the meta-heuristic algorithms for other engineering optimization problems, which is the theoretical contribution of this study. The proposed approach reduces the total construction cost of the large-scale projects, which can be the practical benefit of this study.

Risks and destruction of coastal archaeological sites in Algeria – the case of the coast of El Hamdania

Abstract The Algerian coast is rich in cultural heritage. Many major historical cities and archaeological remains are scattered along its coastline. This cultural heritage is increasingly threatened by the rapid urbanisation that Algeria has experienced in recent years. In 2018 the area of El Hamdania (Cherchell region) was selected as the site of a new commercial mega port. This large construction project will affect a number of archaeological sites located in this region. This paper aims to highlight the archaeological importance of the El Hamdania region and assesses the risks of such a construction to the heritage of the region. The archaeological evidence discussed is based on survey work carried out by members of the Laboratoire d’Études Historiques et Archéologiques (LEHA), an institution that carries out research projects on coastal and maritime archaeology in Algeria.

Multiple stakeholders’ critical success factors scale for success on large construction projects

Multiple stakeholders’ critical success factors scale for success on large construction projects

Assessing the Degradation of Safety Management Performance in Large Construction Projects: An Investigation and Decision Model Based on Complex Network Modeling

Modern safety control theory suggests that the accumulation of safety management defects at the organizational level can lead to a degradation in the overall safety management performance. This problem is exacerbated by the increasing complexity of safety management in large construction projects. The theoretical frameworks proposed by existing studies can provide generalized guidance for identifying safety management defects, but they are not flexible enough to address the complexity of a safety management system (SMS) in specific large construction projects. This study proposed an investigation and decision model based on a complex network model of SMSs. The main purpose was to accurately assess the degradation of safety management performance through the comprehensive identification of safety management defects for large construction projects. The functional components and their interactions in SMSs were graphically represented in a complex network using the fuzzy DEMATEL technique. Based on this, deep-seated safety management defects were identified by tracing the path of influence between the functional components and their roots. Furthermore, the results of this identification were used to support the assessment of the degradation of the safety performance of the overall SMS. The proposed model was verified with a large-scale wastewater treatment plant construction project in Lanzhou City, China. The degradation of the functional components could be presented in a complex visual network map to facilitate an understanding of the weak points or risk-sensitive areas throughout the SMS. Especially in the case of false safety perceptions, deep-seated safety management defects can be identified in time to prevent a sudden collapse of the SMS through early warnings. In addition, it also facilitates timely short-term improvement strategies and systematic long-term improvement strategies for long-term sustainability and increased resilience.

River definitions reciprocally define us

AbstractThis article explores different definitions of river, and in doing so, considers how our efforts to define rivers illuminate aspects of the human condition. Through an exploration of our definitions of river, through the human imagination, in poetry, music, and human's actions, this article considers how our nature is reflected back by rivers—how we in turn are defined by rivers—such as their role in determining borders, movement, escape, the locations of cities, trade, communication, and in the shaping of cultures and societies. This article specifically highlights three definitions of river using examples predominately from North America. River as boundary, exploring how in the reaches of some river basins, rivers act not only as a border, or boundary between two nations or cultures, but also as a line of demarcation between the known and unknown landscapes and the tamed and untamed lands. The definition of river as pathway includes exploration of how the Mississippi River served as a natural highway for people escaping slavery to travel North and reach Underground Railroad routes toward freedom, while also forcibly moving hundreds of thousands of enslaved people in the United States from the Upper South to the Lower South as they were “sold down the river.” Third, this article examines how rivers have been defined as a resource through examples, such as the US government and Bonneville Power Administration's (BPA) efforts, to encourage support of large dam construction and water development projects by hiring Woody Guthrie in 1941 to write songs that would prompt public support for the water projects. Through this discussion of three river definitions, the article considers how rivers have been conceptualized over time and how those different knowledges inform our understanding and treatment of rivers. The article argues that it is vital to include knowledge from across scales, time, boundaries, and ways of knowing in order to improve the protection of rivers and their ecosystems. If we do not, we will continue to lose freshwater biodiversity, wetland and riverine habitat, and their immeasurable qualities that inspire life and imagination at a staggering rate.

Fluctuation in the richness of social wasps throughout a large construction project

Since some social wasp species are sensitive to environmental changes and can be used as bioindicators, the objective of the present study was to analyze the variation in the fauna of social wasps during the phases: before, during, and after completion, as well as to validate the use of wasps as a tool for monitoring the impacts generated by the implantation of the Botanical Garden of the Federal University of Juiz de Fora. Social wasps were sampled through active searching methods, searching for nests and attractive traps in the years 2011 and 2012 (before the construction), 2013, 2014, and 2016 (during the construction), and 2019 (after the construction and opening of the Botanical Garden). The richness and similarity of the species varied over the years, and it was possible to identify resistant and sensitive species to the impact caused by the implantation of the Botanical Garden. Studies with social wasp fauna conducted over many years in the same area can be an efficient tool in monitoring impacts; in addition, it is necessary to have a partnership between researchers and the management of the enterprises to mitigate the effects caused by guidelines and environmental education.

The client's essential stakeholder collaboration activities at the front-end phase of a hospital construction project

PurposeThe research problem in this study is how a client (as a project owner) should organise early stakeholder involvement and integration in the front-end phase of a project. This study aims to create normative managerial statements as propositions from the client's perspective and to combine them into a set of activities enabling efficient organisation in the front-end phase of a hospital construction project.Design/methodology/approachAction design research (ADR) was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the other authors acted as “outside researchers”.FindingsThe authors created seven normative managerial propositions that were verified by the case project stakeholders and developed a managerial framework describing the client's essential stakeholder involvement and integration activities in the front-end phase of a hospital construction project based on these propositions. The authors have also depicted the subphases of the front-end phase: value definition phase in the client permanent organisation, value proposition phase in the client Programme Management Office (PMO) and finally development phase in the alliance organisation ending on the final investment decision.Practical implicationsThe collaborative contract delivery model enables the early involvement and integration of stakeholders. It has been somewhat surprising to note the extent to which collaborative contracts change the client role in the project front-end. The results offer practical activities for how clients can manage front-end activities in collaborative contracts.Originality/valueThe case project offered a platform to analyse how the collaborative contract delivery model changes the emphasis of activities in the front-end of a project. One of the key benefits of collaborative contracts is that development, design and delivery occur partially in parallel, thereby enabling contributions from production to be included in the design and development. The benefit of having a real-life case under study provides the possibility to triangulate and analyse rich data, however limited by the qualitative case method.

Abolish, Accept, Apply: Coping With Ignorance in Project Ecologies

This article seeks to advance the current debate on the role of ignorance in the management of large projects by mobilizing insights from recent literature on the interplay between temporary projects and permanent contexts. Instead of examining how ignorance shapes the success or failure of isolated projects, we intend to examine how ignorance is addressed and framed within these projects and their wider environment and how this framing shapes the practices of planning and managing projects. The usefulness of the proposed framework is gauged with two empirical vignettes that elucidate different perspectives on ignorance in recent, German, large construction projects.

Effects of Different Pre-Heating Welding Methods on the Temperature Field, Residual Stress and Deformation of a Q345C Steel Butt-Welded Joint

Heavy plate welding has been widely used in the construction of large projects and structures, in which the residual stress and deformation caused by the welding process are the key problems to address to reduce the stability and safety of the whole structure. Strengthening before welding is an important method to reduce the temperature gradient, control the residual stress and reduce the deformation of welds. Based on the ABAQUS software, the thermal elastoplastic finite element method (FEM) was used to simulate the welding thermal cycle, residual stress and deformation of low-alloy, high-strength steel joints. Based on the finite element simulation, the influences of flame heating and ceramic heating on the temperature field, residual stress distribution and deformation of a Q345C steel butt-welded joint were studied. The results showed that the thermal cycle of the ceramic sheet before welding had little influence on the whole weldment, but had great influence on the residual stress of the weldment. The results show that the maximum temperature and residual stress of the welded parts are obviously weakened under the heating of ceramic pieces, and the residual stress of the selected feature points is reduced by 5.88%, and the maximum temperature of the thermal cycle curve is reduced by 22.67%. At the same time, it was concluded that the weld shapes of the two were basically the same, but the weld seams heated by ceramic pieces had a better weld quality and microstructures through comparing the macro- and micro-structures between the welded parts heated by ceramic pieces and the simulated weld. Heating before welding, therefore, is an effective method to obtain a high weld quality with less residual stress and deformation.

On possibilities of improving labor safety by improving forms and methods of managing labor behavior (on the example of large investment construction projects)

The current possibilities of improving the labor safety of employees in the industrial and transport sectors by improving methods for managing the labor behavior were analyzed. Russian and foreign theories of managing the influence of the human factor on the labor process and result were described. The “resources processes values” system of the concept of organization management was analyzed. Using this system, possibilities of applying a value-oriented approach to improving the efficiency of the applied methods and practices were determined. On the example of managing a large investment construction project, the main value constants of employees were identified; the relationship of values and needs were investigated; the most widely used formats of development of common values of employees changing their labor behavior were systematized; their effectiveness was assessed. Directions for further research on improving the effectiveness of methods for managing the influence of the human factor on the process and result of production activities were determined. The ideological foundations for creating labor safety culture were provided.

Assessment of the Significance of Identified Attributes Affecting the Rebar-Fixing Productivity Using Multiple Regression

Reinforced concrete structures are an inherent part of the construction sector. Every in situ reinforced concrete structure cardinally involves rebar-fixing works, which entails activities like transporting, marking, laying, and tying the rebar for the components under construction. Rebar-fixing absorbs a significant number of man-hours during the operation. Therefore, productivity of rebar fixers is a critical concern in construction. Several attributes influence rebar-fixing productivity. Former studies have investigated the impact of the attributes separately and predominantly using qualitative data. A few studies have assessed rebar productivity quantitatively but ignored the effects of some crucial parameters, such as congestion, crew composition, and construction delays. Moreover, studies are limited to account for all time proportions like productive, semiproductive, and nonproductive while assessing rebar productivity. Therefore, this study addresses the aforementioned research gaps by assessing the impact of diverse attributes using direct measures of rebar-fixing productivity and its attributes. Initially, hypotheses were developed to determine the influence of eight attributes identified in this study on rebar-fixing productivity. Next, the data were recorded from one large construction project in Gujarat, India. The work sampling approach was adopted for the productivity assessment of rebar fixers at the project site to evaluate each time proportion. Furthermore, the stepwise regression analysis was performed on the data set to examine the hypotheses. Results indicate that attributes such as quantity of reinforcement, characteristic rebar diameter, and congestion have a significant positive impact on rebar-fixing productivity, whereas work duration has a significant negative impact on it. The outcomes of this research can aid the site management, structural engineers, and construction planners in decision-making to enhance the productivity of rebar fixers, thereby adhering to the budget and schedule constraints of the project.