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Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

The purpose of this paper is to make recommendations for policy makers, promotors and project managers on how to structure and deliver new nuclear build programmes, by drawing on the megaprojects literature and salutary lessons from previous megaprojects.

This paper is underpinned by the extant literature and an analysis of public domain data from three proposed new nuclear power plants in the UK. It identifies the main challenges facing new nuclear build projects and subsequently proposes lessons that can be learnt from megaprojects, in order to plan, structure and deliver new nuclear build programmes successfully.

The paper argues that megaprojects are simultaneously trait-making, rather than trait-taking, possess a temporality and timescale in excess of typical infrastructure projects, suffer from high levels of uncertainty and ambiguity, are organisationally complex, costly and are highly likely to destroy rather than create value. Second, it argues that the challenges facing new nuclear build are not merely technological but also institutional, political and societal in nature. The nature of these challenges is exemplified using three proposed new nuclear build projects in the UK.

This is the first paper to draw on both extant megaproject theory and on an analysis of the public domain data from three proposed new nuclear power plants in the UK. It makes contributions to megaprojects theory and practice, and specifically to nuclear new build projects. Importantly, it proffers recommendations for how new nuclear build programmes around the world might be structured, planned and delivered to minimise the risks of failure.

This research aspires to contribute in the area of exploration of the psychological traits evolving by practitioners within the project management profession. Specifically, it investigates whether there is any difference in optimism levels among experienced project management practitioners and newcomers in the profession.

The research used the life orientation test-revised (LOTR) (Scheier et al., 1994) to calculate respondents’ optimism scores. With these scores at hand, the researchers could then apply inferential statistics in order to deduce any differences observed among optimism score and the respondents’ characteristics (age, years of experience etc.).

Based on the results of this research, several demographic variables were shown to be statistically significant with optimism. These were (1) the number of years of experience the respondent had in managing projects, (2) working in a government organisation and (3) possessing specific project management certifications, all of which were found to adversely affect the respondent’s optimism score.

This research was unique in applying a well-known psychological test instrument (LOTR) to provide insight into the psychological impacts of a career as an information technology (IT) project manager. It is also highly likely that this correlation between the length of time working as a project manager and the adverse impact on their optimism would also apply to not just IT project managers but all experienced project managers.

The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs).

The earned value management (EVM) method based on the IGN has been developed.

The EVM method based on the IGN has been verified by a numerical example that can be applied to construction projects.

The EVM method, based on the gray numbers, reduces the budget and time shortage risk. Also, using this method, the managers would not be restricted to provide very exact values in their progress reports in the non-deterministic conditions.

One notable and significant point in all projects during the execution process is to estimate the project completion time and cost. However, non-deterministic conditions for both planned and actual physical completion percentage of projects have not been considered for predicting the project completion time and cost in the literature. Therefore, the novelty of this paper is the prediction of project completion time and cost under non-deterministic conditions using IGN.

The purpose of the paper is 1) to address the importance of contingency at the right level when defining project control baseline, including cost reserves / “room to manoeuvre” and 2) present proactive uncertainty management as a regime to ensure cost effective management of project reserves and contribute to project success.

The paper is a combination of literature study and quantitative research on how contingency develops during the lifetime of a case project. The investigation into the case project includes document study into quantitative material from the case project. The combination of empirical material and theory makes the discussion robust.

Unrealistic low cost uncertainty will lead to unrealistic low contingency. The case study from a Norwegian mega project shows a contingency of 15 per cent in addition to expected costs. The case study shows that by continuous opportunity management and risk reduction, the needs for management reserves are systematically reduced and the contingency is controlled.

This research is limited to one case study. A higher number of cases are necessary to generalise the findings. However, the authors would claim that the systematic mapping of need for management reserve towards the project contingency, and a continuous uncertainty management system will help to obtain cost effective management. The findings from the case study could be applied on similar cases.

The case study shows a way of setting contingencies and managing contingencies through systematic uncertainty management.

Improved management of project provisions will increase the value of future projects.

Project complexity has been researched much. The majority of publication is searching for law-like relations or development of descriptive frameworks. More prescriptive knowledge is needed to guide the project managers in navigating the project complexity in project managers' pursuit of success. Identifying the complexities of a given project is a real-world problem for project managers (Mikkelsen et al., 2021). The purpose of the paper is to investigate the research of prescriptive knowledge on the management of project complexity.

Based on a longitudinally case study, this paper uses Action Design Research (Sein et al., 2011) (ADR) to research the management of project stakeholder complexity. ADR is a variation of action research (AR) with inspiration from design science (Hevner et al., 2004) where an artifact is designed to solve a real-world problem. In this case study, an information system was configured in collaboration with the project managers of the recipient organization.

The findings from the research project are presented using the affordance theory (Gibson, 1977) as a framing concept and give special attention the affordance perception (Pozzi et al., 2014). Among the project managers, who were very engaged in the co-design, the majority refrained from activating the information system and got the outside view from the stakeholders. Interviews afterward identified “fear of bad project ratings from the stakeholder” as the main course of resistance to deploy the surveying information system.

The paper contributes on two levels. The paper presents a novel approach to researching project complexity based on engaging the stakeholder in generating a common perception of the ongoing state of the projects. The paper also contributes insights into reasons for reluctance on the part of the participants (the project managers) of the recipient organization and hereby adds to the understanding of the organizational change aspect of AR in the research of project management. The paper concludes with the identified benefits of using ADR in research on project complexity management and gives recommendations for future research.

In the current economic scenario characterized by turbulence, innovation is a requisite for company's growth. The innovation activities are implemented through the realization of innovative project. This paper aims to prospect the promising opportunities coming from the application of Machine Learning (ML) algorithms to project risk management for organizational innovation, where a large amount of data supports the decision-making process within the companies and the organizations.

Moving from a structured literature review (SLR), a final sample of 42 papers has been analyzed through a descriptive, content and bibliographic analysis. Moreover, metrics for measuring the impact of the citation index approach and the CPY (Citations per year) have been defined. The descriptive and cluster analysis has been realized with VOSviewer, a tool for constructing and visualizing bibliometric networks and clusters.

Prospective future developments and forthcoming challenges of ML applications for managing risks in projects have been identified in the following research context: software development projects; construction industry projects; climate and environmental issues and Health and Safety projects. Insights about the impact of ML for improving organizational innovation through the project risks management are defined.

The study have some limitations regarding the choice of keywords and as well the database chosen for selecting the final sample. Another limitation regards the number of the analyzed papers.

The analysis demonstrated how much the use of ML techniques for project risk management is still new and has many unexplored areas, given the increasing trend in annual scientific publications. This evidence represents an opportunities for supporting the organizational innovation in companies engaged into complex projects whose risk management become strategic.