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Large‐scale construction projects pose several challenges for successful completion. There seems to be no general agreement among researchers on what are the critical success factors (CSFs) on construction projects. Success factors vary across various projects, let alone countries. This paper attempts to elicit the perception of construction professionals on CSFs appertaining to large‐scale construction projects in Thailand.

Questionnaire surveys and interviews were conducted with project managers, deputy project managers, and line managers to gather their perception on CSFs.

Results of 76 questionnaire surveys and 35 interviews revealed that factors related to project planning and control, project personnel, and involvement of client were perceived to be critical for the success of large‐scale construction projects in Thailand. Participants also showed their high concern for sufficient resources, adequate communication, mutual understanding of stakeholders on project goals, and award of bids to the “right” designers and contractors.

The study was conducted on a single large‐scale construction project in Thailand, and hence, findings should be interpreted in context of Thai construction industry. The study also did not consider any specific procurement methods under which the project was being developed. Participants were asked about their general perception about CSFs on large‐scale construction projects.

Results from this study can be used as guidelines to ascertain CSFs on other large‐scale projects in Thailand. Project managers can also use this study to evaluate their current project and compare the perceived and real success factors for knowledge management exercises.

The paper captures the perception of construction professionals about CSFs in large‐scale projects in Thailand. It also presents a model for conceptual illustration of CSFs by differentiating the process domain from performance domain.

The purpose of this paper is to present an approach for productivity measurement that considers both construction growth and carbon reduction.

The approach applied is a sequential Malmquist-Luenberger productivity analysis based on a directional distance function and sequential benchmark technology using the data envelopment analysis (DEA) technique. The sequential Malmquist-Luenberger productivity change index is decomposed into pure technical efficiency, scale efficiency, and technological change indices, in order to investigate the driving forces for productivity change.

The construction industries of the Australian states and territories were selected implement the new approach. The results indicate that construction growth and carbon reduction can be achieved simultaneously through the learning of techniques from benchmarks.

Current research on total factor productivity (TFP) in construction generally neglects carbon emissions. This does not accurately depict the nature of construction and therefore yields biased estimation results. TFP measurement should consider carbon reduction, which is beneficial for policymakers to promote sustainable productivity development in the construction industry.

The approach developed here is generic and enhances productivity and DEA research levels in construction. This research can be used to formulate policies for evaluating performance in worldwide construction projects, organizations and industries by considering undesirable outputs and desirable outputs simultaneously, and for promoting sustainable development in construction by identifying competitiveness factors.

The complexities in strait-crossing cable-stayed bridge project are increasing the risks. This study aims to identify and analyze the significant and worth-considered construction risks of the first, biggest and longest spanned strait-crossing bridge project in Indonesia.

As many as 32 risk events were identified and determined as the risks that exist and can be represented in the Suramadu bridge project context. Data was collected through a design-based questionnaire disseminated to experts involved in the project as well as semi-formal interviews. Several quantitative methods were applied to analyze the significant risks, such as relative importance index, Spearman’s rank correlation test and Mann–Whitney U test.

The analyses reveal that “unexpected natural behavior” confirmed by both contractor and consultant parties is the most significant and crucial risk event. Another risk event found to be significant is the “delayed payment.” On the other hand, it is also found that several risks within the legal category are found to be less significant compared to other major risk events.

The results of the present research should be interpreted in the context of several limitations. Given these possible concerns regarding the generalizability of the findings, along with the relatively low rate of participants in the current research, additional studies are needed to provide a more complete picture of stakeholder perceptions who are involved directly in the construction environment as well as to identify more construction risks specifically in the large-scale bridge project.

This study has provided fundamental contributions to the body of knowledge and practical implication to promote and assist decision-makers toward developing a comprehensive risk assessment of a large-scale bridge project.

The analyses of outcomes and discussion, as well as the findings of this research, have shed light on the construction risks understanding, which contributes to delivering a theoretical framework for achieving large-scale bridge project success.

This paper aims to qualify traditional concrete mixtures for large-scale material extrusion in an automated, additive manufacturing process or additive construction.

A robust and viable automated additive construction process must be developed that has the capability to construct full-scale, habitable structures using materials that are readily available near the location of the construction site. Accordingly, the applicability of conventional concrete mixtures for large-scale material extrusion in an additive construction process was investigated. A qualitative test was proposed in which concrete mixtures were forced through a modified clay extruder and evaluated on performance and potential to be suitable for nozzle extrusion typical of additive construction, or 3D printing with concrete. The concrete mixtures were further subjected to the standard drop table test for flow, and the results for the two tests were compared. Finally, the concrete mixtures were tested for setting time, compressive strength and flexural strength as final indicators for usefulness in large-scale construction.

Conventional concrete mixtures, typically with a high percentage of coarse aggregate, were found to be unsuitable for additive construction application due to clogging in the extruder. However, reducing the amount of coarse aggregate provided concrete mixtures that were promising for additive construction while still using materials that are generally available worldwide.

Much of the work performed in additive manufacturing processes on a construction scale using concrete focuses on unconventional concrete mixtures using synthetic aggregates or no coarse aggregate at all. This paper shows that a concrete mixture using conventional materials can be suitable for material extrusion in additive construction. The use of conventional materials will reduce costs and allow for additive construction to be used worldwide.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

The purpose of this paper is to develop a simultaneous measurement of overall performance and its two dimensions of efficiency and effectiveness in the case of Chinese construction industry.

A relational two-stage data envelopment analysis (DEA) method, which builds a relationship between component stages and can effectively identify inefficient stages, is developed and applied in order to measure overall performance, efficiency and effectiveness.

The construction industry of the Eastern region in China demonstrated the best results for overall performance, efficiency and effectiveness. The gaps between regions were primarily reflected in differences of pure technical efficiency. Performance indicators in the whole construction industry improved steadily and but could be improved more effectively. The coefficients of variation became smaller and more well-balanced across the whole industry.

Improving overall performance should focus on promoting construction efficiency at the project level and increasing management effectiveness at the company level. Sustainable development policies, which may include large investment and preferential policies, can narrow performance differences among the regions’ construction industries, and ultimately promote overall performance for the whole industry.

The relational two-stage DEA model is further developed in a variable returns-to-scale condition. The developed approach is generic and can provide a pathway for simultaneously measuring performance, efficiency and effectiveness and to recognise competitive advantages for promoting sustainable development.

Large-scale projects are the typical delivery model in the engineering and construction industry, with their very own characteristics. Even though well established, only 1 in 1,000 large-scale projects is successful (Flyvbjerg, 2011). A lack of effective supply chain risk management (SCRM) has repeatedly been identified as one of the main causes. While the SCRM body of knowledge seems increasingly well established, a lack of effective methods meeting the specific requirements of large-scale projects can be observed.

This paper presents a structured and prioritized view on the supply chain risk portfolio in this sector: first, the authors identified and categorized the key supply chain risks in the recent literature. Next, the authors surveyed large-scale project managers across multiple industries, mainly coming from the domains of supply chain management and project management. Finally, the authors provide a contextualized risk taxonomy for engineering, procurement and construction (EPC) projects.

The identified risk portfolio deviates from generic projects significantly and shows a very high inherent risk exposure of large-scale projects. In particular, behavioral risks are identified as crucial. Additionally, a bias to considerably underestimate risks at project beginning is found.

The contextualized SCRM taxonomy offers a systematic and structured view on the key supply chain risks in EPC large-scale projects. The identified risks are considerably different in their characteristics compared to generic projects or classical SCRM approaches. The authors thus provide a new perspective on SCRM in this specific setting and complement traditional risk and project risk management techniques.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

This paper aims to present the sustainable performance criteria for 3D printing practices, while reporting the primarily computations and lab experimentations. The potential advantages for integrating three-dimensional (3D) printing into house construction are significant in Construction Industry 4.0; these include the capacity for mass customisation of designs and parameters for functional and aesthetic purposes, reduction in construction waste from highly precise material placement and the use of recycled waste products in layer deposition materials. With the ultimate goal of improving construction efficiency and decreasing building costs, applying Strand7 Finite Element Analysis software, a numerical model was designed specifically for 3D printing in a cement mix incorporated with recycled waste product high-density polyethylene (HDPE) and found that construction of an arched truss-like roof was structurally feasible without the need for steel reinforcements.

The research method consists of three key steps: design a prototype of possible structural layouts for the 3DSBP, create 24 laboratory samples using a brittle material to identify operation challenges and analyse the correlation between time and scale size and synthesising the numerical analysis and laboratory observations to develop the evaluation criteria for 3DSBP products. The selected house consists of layouts that resemble existing house such as living room, bed rooms and garages.

Some criteria for sustainable construction using 3DP were developed. The Strand7 model results suggested that under the different load combinations as stated in AS1700, the maximum tensile stress experienced is 1.70 MPa and maximum compressive stress experienced is 3.06 MPa. The cement mix of the house is incorporated with rHDPE, which result in a tensile strength of 3 MPa and compressive strength of 26 MPa. That means the house is structurally feasible without the help of any reinforcements. Investigations had also been performed on comparing a flat and arch and found the maximum tensile stress within a flat roof would cause the concrete to fail. Whereas an arch roof had reduced the maximum tensile stress to an acceptable range for concrete to withstand loadings. Currently, there are a few 3D printing techniques that can be adopted for this purpose, and more advanced technology in the future could eliminate the current limitation on 3D printing and bring forth this idea as a common practice in house construction.

This study provides some novel criteria for evaluating a 3D printing performance and discusses challenges of 3D utilisation from design and managerial perspectives. The criteria are relied on maximum utility and minimum impact pillars which can be used by scholars and practitioners to measure their performance. The criteria and the results of the computation and experimentation can be considered as critical benchmarks for future practices.

The purpose of this study is to identify the factors relating to the integration and compliance of Building Control (Amendment) Regulations 2014 (BC(A)R 2014) in large Irish construction organisations.

To achieve the aim, a mixed method approach is adopted, initially, providing a critique of the literature review, followed by a combination of 7 semi-structured interviews and 30 questionnaires from industry practitioners.

Findings demonstrate that BC(A)R has had a significant positive effect on the industry, eliminating previous bad practice, by increasing the accountability for professionals signing-off on new buildings, and highlights the emphasis on certification in successfully achieving practical completion on projects.

The findings provide further justification on the need for compliance, and integration, of BC(A)R in the Irish construction sector, offering further evidence, where needed, on the benefit of its adoption.

The originality and value of this research lies in the limited number of studies in the area, particularly in the context of large Irish construction projects, which this study aims to fulfil.