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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.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

The purpose of this paper is to rank critical risks and determine major categories of risks to be considered by public–private partnerships (PPPs) investors when investing in “smart” transportation infrastructure. Such investment is sorely needed in many mega cities around the world currently suffering from serious impacts of traffic congestion, pollution and lack of usability of transport systems.

The study used literature review focused upon smart transportation infrastructure projects financed by PPP arrangements to create a questionnaire which was refined by subject matter experts and then completed by 126 experienced respondents. Exploratory factor analysis was used to create major categories emerging from the collected data. Interviews with ten experts were used to validate the findings.

The most highly major ranked risks shared by these participants were lack of expertise in complex project implementation, political interference, lack of PPP project data and lack of a collaboration mechanism between government and private sectors. Factor analysis showed that in terms of risk likelihood, stakeholder engagement, implementation process issues, the natural environment, data-sharing and technology complexity emerged. In terms of risk impact, major factors were stakeholder engagement, trust versus resistance issues, the natural environment and factors concerning uncertainty.

This paper addresses a somewhat unexplored area, the risks involved in investing in PPP smart transportation infrastructure. Such infrastructure projects are embedded in their environments, and approaches using a complexity lens can emerge overriding risk concerns for investors when undertaking such projects.

Contractors of different scales, operating in different construction industries of varying institutional and economic settings, have different considerations when making bid or no-bid and mark-up decisions. Focusing on the large and medium-sized contractors in the Jilin province, China, the purpose of this study is to examine important factors affecting their decision to bid (d2b) and mark-up decisions and investigate differences between large and medium-sized contractors in evaluating the importance of the various factors affecting their d2b and mark-up decisions.

This study used a survey design for timely data collection from a large population. Contractors’ bidding attitudes was collected using an online survey questionnaire with a list of 40 key factors. Statistical analytical methods were applied for comparing the two groups of contractors.

The results of this study indicate that factors related to client conditions are most critical for both large and medium-sized contractors in their d2b and mark-up decisions. The results also show statistically significant differences between the two groups of contractors on a subset of factors affecting their d2b and mark-up decisions. The large contractors have placed more emphasis on projects' potential financial and strategic benefits. Another notable finding is that both groups of contractors have placed great emphasise on “government legislations” in their d2b and mark-up decisions.

These findings should be interpreted in consideration of several limitations. Firstly, the sample size is relatively small, and the focus was on a single province in the China construction industry. Next, this study only explores differences between large and medium-sized contractors in evaluating the importance of the various factors affecting their d2b and mark-up decisions.

Contractors could refer list of critical factors in competing for jobs in Jilin province or other provinces of similar institutional and economic settings. Construction clients, on the other hand, should consider the list of critical factors in the formulation of their competitive tendering procedures, thus enhancing the efficiency in their procurement of construction services.

Research on contractors’ bidding decision-making in the context of Chinese construction industry remains scarce; the research findings have implications for the industry stakeholders.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

Urban rail projects are typically large-scale transport infrastructure projects (megaprojects) which have many potential risks that can influence the strategic goals of owners. However, there is a paucity of studies which explore the impact of risks on both “urban rail” project time and cost together considering quantitative assessments. Therefore, this paper focuses on investigating critical risks and quantifying such risk impacts on urban railway project schedule and cost in practice.

A combination of qualitative and quantitative research methods comprising semi-interviews with five experts and a questionnaire survey of 132 professional respondents is used. The data were modeled using Monte Carlo Simulation to predict the probability of project schedule and cost.

The results show that 30 risk variables are categorized into seven main groups which have significant impacts on both project time and cost. Outstanding five risk variables were highlighted as follows: (1) project site clearance and land compensation; (2) design changes; (3) physical project resources; (4) contractors’ competencies and (5) project finance. Such findings were supported by Monte Carlo simulation which predicted in the worst case that the project may suffer 11.03 months’ delays and have cost overrun with a contingency of US$287.68 million.

This study expands our knowledge about time and cost contingency of urban metro railway implementation across developing economies and particularly within the context of Vietnam. Policymakers will not only gain an understanding about risk structure but will also recognize the significant impacts of critical risk through risk impact modeling and simulation. Such an approach provides insights into risk treatment priorities for planners so that they can proactively establish suitable strategies for risk mitigation in practice.

The purpose of this study is to propose an improved framework for managing Private Participation in Infrastructure ICT (PPI-ICT) projects in the context of developing countries as the requirements to manage them are different in several aspects.

The framework has been proposed based on an exhaustive literature review and statistical analysis of the PPI-ICT projects’ data set using logistic regression, F-test and student’s t-test. The proposed framework was also applied to the PPI-ICT projects.

The framework is an extension to NTCP (novelty, technology, complexity and pace) approach by including extrinsic factors such as income of the country, climate risk, religious diversity, political stability, regularity quality and control of corruption. The proposed framework was used to analyze project characteristics and their external conditions in the context of developing countries. Based on the analyses, the authors have presented a detailed set of recommendations for project managers, practitioners and governments to improve the success rate of these projects.

The major contribution of this study is the framework, which encompasses the NTCP model as well as extrinsic characteristics of PPI-ICT projects. The proposed framework is meant to assist the project managers to comprehend the project characteristics and its external environment to identify an adequate approach for managing projects successfully.

Despite the widespread study and application of public-private partnerships (PPPs) since the 1980s, the field lacks a universally accepted definition that captures the concept's complexity. This study aims to offer a definition and foster a more substantive and comprehensive discourse on PPPs to improve communication and understanding between academics and practitioners from diverse disciplines and legislative backgrounds.

Grounded in the family-resemblance concept proposed by German philosopher Ludwig Wittgenstein, this study conducts a comprehensive literature review to identify core and non-core elements frequently cited in PPP descriptions. The authors used these findings to develop the PPP sunflower model as a structured framework for defining PPPs.

The analysis elucidates six core elements consistently present in PPP descriptions: clarity of roles and responsibilities, appropriate risk allocation and sharing, injection of expertise and resources, cooperation and teamwork, a bundle of services, and long-term contracts. Coupled with identified non-core elements, these core components comprise the PPP sunflower model, a structured framework for defining PPPs that accommodates their multi-faceted nature.

The PPP sunflower model distinguishes itself as a unique contribution to the PPP literature. It offers a rigorous theoretical framework that can elucidate the complexity of PPPs for various stakeholders. The model serves as a practical tool for evaluating the authenticity and viability of PPP projects. The study's novelty lies in its adoption of the family-resemblance concept, thereby providing a comprehensive, multi-dimensional framework that enhances the understanding of PPPs across different disciplines and legislative contexts.

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.

The increasingly uncertain and unstable factors in the internal and external environments of megaprojects lead to more potential crises and challenges, hence increasing the importance of improving organizational resilience. This study aimed to explore the effects of transformational leadership and employee self-efficacy on organizational resilience from a leader–employee perspective.

By combining the perspectives of leaders and employees, this study constructed a development mechanism of the organizational resilience of megaprojects. Organizational climate and organizational learning were selected as two organizational resources to study the mediating roles of leaders and employees. A partial least-squares structural equation model was used to test the hypotheses based on data collected from 243 respondents.

Results show that transformational leadership and employee self-efficacy positively affect organizational resilience and organizational resources. Organizational learning positively mediates the effects of leader–employee factors on organizational resilience, whereas organizational climate does not.

This study verifies the positive role of transformational leadership and employee self-efficacy in organizational resilience and reveals the development mechanism of using organizational resources to build organizational resilience. This paper enlightens project managers and employees on how to well respond to the uncertainty and complexity of megaprojects.