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The purpose of this study was to prioritize the appropriate generic contractor selection criteria for Engineering–Procurement–Construction (EPC) projects in the construction industry.

Proceeding from a review of previous studies and validation by a small group of experts, a preliminary set of 16 criteria was first identified. This was followed by three rounds of Delphi surveys: firstly, with 64 experienced participants confirming the relevance of the 16 criteria; secondly, with a reduced subgroup of 47 more experienced participants scoring the importance of each; and finally, providing the opportunity for these 47 to revise their scores in the light of knowing the aggregated results of the previous round.

The results show the consensus view, of which the most important criteria are ranked as past performance, project understanding, technical attributes, key personnel, health and safety, past experience, time, management, financial, contractual and legal, quality, cost, relationships, environmental and sustainability, organizational and industrial relations, and geographic location.

The findings are useful for both practitioners and academics in making a significant contribution to the body of knowledge of the EPC process. This will assist in providing a better understanding of criteria importance and pave the way to developing an EPC contractor selection model involving the criteria most needed to objectively identify potential contractors and evaluate tenders.

This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize factors in a framework. Thematic analysis subsequently revealed 18 selective codes under three groups of drivers, barriers, and outcomes. These three groups were explained by four key aspects including organization, stakeholders, infrastructure, and business environment that set a framework for the digitalization of construction. The study finally concluded digitalization strategies with a focus on support mechanisms, government incentives, regulations, the transition from manual labor to technicians, organizational technology culture, methodology development, and innovation processes. Such strategies provide insight into prioritizing resources towards smooth digital transformation in construction businesses.

A two-stage methodology is adopted by undertaking a systematic literature review followed by thematic content analysis. This work concludes with an analysis of remaining research gaps and suggestions for potential future research.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize variables in a framework. Thematic analysis subsequently revealed a set of variables and factors describing construction digitalization under three groups of success factors, barriers, and outcomes. A critical content analysis of the representative studies was conducted to identify five future research trends as well as associated research gaps and directions on the topic.

This study contributes to practice by providing directions concerning the key strategies and priorities associated with the digitalization of construction businesses.

This ground-breaking research brings to light a classified set of factors that are important for the digitalization of construction businesses. The elicited framework contributes to the current body of knowledge by offering a unique conceptualization of both driving and adverse aspects for the seamless digital transformation of construction.

The paper covers mega infrastructure construction supply chain (MICSC) in Engineering-Procurement-Construction (EPC) projects, where the frequent occurrence of risk incidents has greatly affected human life. The research aims to establish a risk evaluation index system for MICSC in EPC projects, exploring what risk factors lead to risk incidents and measure the importance and causality of all these risk factors.

The research applies a combination of quantitative and qualitative analysis methodology to process data sequentially. In the first place, risk factors for MICSC in EPC projects are extracted and identified from literature survey and expert interviews. In the second place, an integration model fuzzy Analytic Hierarchy Process (f-AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (f-DEMATEL) is constructed to comprehensively analyze all these risk factors.

12 primary risk factors and 36 secondary risk factors comprise the risk evaluation index system for MICSC in EPC projects from 178 literature and 5 professionals. The results indicate that Political Situation (F1), Social Security (F2) and Management Mode (F8) are critical risk factors, where F1 and F2 are cause factors and F8 is an effect factor.

There are three main contributions of this paper. First and foremost, from the perspective of the research content, no other study has been able to assess risk factors for MICSC in EPC projects, while embedding nine phases of the whole project life cycle and six subjects of stakeholders into a risk evaluation index system. Additionally, from the perspective of research method, a combined model incorporating f-AHP and f-DEMATEL is constructed to avoid the one-sidedness of a single model. Last but not least, from the perspective of practical significance, focusing on the critical risk factors, a series of effective measures are formulated to make appropriate management decisions for nodal enterprises of MICSC, which can improve their risk management capabilities.

This study aims to introduce and evaluate the COPULA framework, a construction project monitoring solution based on blockchain designed to address the inherent challenges of construction project monitoring and management. This research aims to enhance efficiency, transparency and trust within the dynamic and collaborative environment of the construction industry by leveraging the decentralized, secure and immutable nature of blockchain technology.

This paper employs a comprehensive approach encompassing the formulation of the COPULA model, the development of a digital solution using the ethereum blockchain and extensive testing to assess performance in terms of execution cost, time, integrity, immutability and security. A case analysis is conducted to demonstrate the practical application and benefits of blockchain technology in real-world construction project monitoring scenarios.

The findings reveal that the COPULA framework effectively addresses critical issues such as centralization, privacy and security vulnerabilities in construction project management. It facilitates seamless data exchange among stakeholders, ensuring real-time transparency and the creation of a tamper-proof communication channel. The framework demonstrates the potential to significantly enhance project efficiency and foster trust among all parties involved.

While the study provides promising insights into the application of blockchain technology in construction project monitoring, future research could explore the integration of COPULA with existing project management methodologies to broaden its applicability and impact. Further investigations into the solution’s scalability and adaptation to various construction project types and sizes are also suggested.

This research offers a comprehensive blockchain solution specifically tailored for the construction industry. Unlike prior studies focusing on theoretical aspects, this paper presents a practical, end-to-end solution encompassing model formulation, digital implementation, proof-of-concept testing and validation analysis. The COPULA framework marks a significant advancement in the digital transformation of construction project monitoring, providing a novel approach to overcoming longstanding industry challenges.

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

The existing literature has been mainly focused on local problems but without an overall framework for studying the top-level planning of intelligent construction from a systematic perspective. The purpose of this paper is to fill this gap.

This research adopts a deductive research approach.

This research proposes a reference architecture and related business scenario framework for intelligent construction based on the existing theory and industrial practice.

The main contribution of this research is to provide a useful reference to the Chinese government and industry for formulating digital transformation strategies, as well as suggests meaningful future research directions in the construction industry.

Offsite construction (OC) is an efficient method to reduce waste in the construction industry from a circular economy perspective. Yet, its uptake is subdued by the ambiguities around its supply chain. Hence, the purpose of this study is twofold: to identify the OC project delivery models, the limitations in their procurement approach to facilitate the resilience of the supply chain and interventions to promote supply chain resilience (SCR) and to identify the gaps in the existing procurement process and propose further research areas that implement strategies to improve SCR.

The study was conducted as a systematic literature review. In total, 41 peer-reviewed research papers published between 2013 and 2023 were shortlisted through the preferred reporting items for systematic reviews and meta-analysis guidelines. A descriptive analysis was conducted, followed by a thematic analysis.

The descriptive analysis reveals that the emphasis on digitising OC has shifted to transforming the business model, procurement and supply chain with a human-centric view. In thematic analysis, the predictability of the SC partners and the probabilities of evaluating the prospects are revealed as arbitrary characteristics in the current procurement strategies. Rewarding collaborative relationships among SC partners and incorporating provisions to postpone the module delivery are some interventions to promote flexibility. Drafting comprehensive and effective contracts that address transparency issues and facilitating the need for continuous development of capabilities through procurement are among the further research avenues proposed.

This study is a precursor demonstrating the potential of the procurement process to implement the decrees of SCR for better goal congruence of the OC supply chain.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

The purpose of this study is to ascertain and list the most effective management strategies in efficiently handling the project complexities to enhance the performance of the project.

To fulfill the aim of this study, a comprehensive literature review was conducted, and the qualitative Delphi technique in two rounds was applied. Participants of the Delphi technique consisted of 12 subject matter experts (SMEs) with cumulative experience of 250 years in working in construction projects. In the first round of the Delphi technique, SMEs were asked to provide complexity management strategies to address the complexities due to 37 complexity indicators (CIs) under 11 complexity categories. In the second round of the Delphi technique, SMEs identified the top three management strategies for each of the 37 CIs.

This study collected the outcome of the two-round Delphi technique and based on the output developed the list of strategies to manage complexities related to each indicator. For example, establishing a well-informed governance team, assigning a Project Manager (PM) when the number of projects is more than one in an organization, and assigning a PM efficient enough to communicate with higher authority effectively will help in managing complexity that arises due to faulty assessment of the influence of a project on the organization’s overall success.

This study will help practitioners in effectively managing the project complexities, and thus will reduce the monetary loss associated with project complexities.