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Value creation for society from public projects requires that the overall benefits exceed the use of taxpayers' money. At the same time, cost overruns in public projects are a well-documented feature in the literature, but practical guidance on reducing the extent and magnitude of overruns is rare. In 2000, Norway introduced a governance regime that includes mandatory external quality assurance (QA) of cost estimates for major public projects. This paper compares the cost performance of public projects on each side of this QA scheme.

We use an original dataset covering 1,704 projects from 2000 to 2021, reported first-hand from Norwegian public agencies. We apply quantitative methods in the form of descriptive statistics, regression models, and statistical testing of hypotheses to answer our research questions.

The mean cost overrun across projects in our dataset is smaller than several previous international studies have reported. We find no statistical support for different cost performances between QA and non-QA projects. Secondly, cost overruns seem to vary between different public sectors. A third finding is a small development with lower cost overruns over time for the non-QA projects, and we raise the question of whether the QA scheme has contributed to overall learning effects. The fourth finding is that cost deviations are quite independent of project size.

The paper offers novel insights for decision-makers and researchers on the effects of external quality assurance on cost performance in public projects.

This study aimed at developing and empirically testing a system dynamics causal loop (SDCL) model for investigating factors related to the risk of cost overruns, associated with the performance of construction projects in developing countries.

Using data derived from the Ghanaian construction industry (GCI), a conceptual system dynamics model was hypothesised and empirically tested.

Supported by empirical evidence, the study established that the low technical capacity of consultants is the underlying cause of cost overruns in government projects. There is a strong proof of the relationship between the results of the SDCL model and poor contract planning and supervision, change orders, competence of the project team and the lack of effective coordination amongst the contractual parties.

The final SDCL model has revealed key risk components that would require standard mitigation measures in order to achieve “acceptable success” in construction projects.

The study presents an interactive approach for construction practitioners in developing countries to prioritise the causes of cost overruns in order to initiate quick responses.

Risk identification is an integral part of overall risk management framework of projects. The risks associated with projects and their response planning differs according to the country and the sector specific environment in which they are being implemented. In this paper, the study is carried out to identify the critical risk factors causing delay in Kuwait’s building and infrastructure projects. The preparation of a preliminary list of risks and risk factors is outlined, questionnaire development and survey details are explained, and analysis of survey responses for the identification of delay risk factors in Kuwait is presented. A case study analysis with respect to time‐overrun/delay of about 28 building and infrastructure projects executed in Kuwait is also presented to validate the survey results. Survey and case study results show that the frequency of time‐overrun in KuwaitRisk identification is an integral part of overall risk management framework of projects. The risks associated with projects and their response planning differs according to the country and the sector specific environment in which they are being implemented. In this paper, the study is carried out to identify the critical risk factors causing delay in Kuwait’s building and infrastructure projects. The preparation of a preliminary list of risks and risk factors is outlined, questionnaire development and survey details are explained, and analysis of survey responses for the identification of delay risk factors in Kuwait is presented. A case study analysis with respect to time‐overrun/delay of about 28 building and infrastructure projects executed in Kuwait is also presented to validate the survey results. Survey and case study results show that the frequency of time‐overrun in Kuwait’s construction projects is very high. The five most critical time‐overrun factors identified in Kuwait’s infrastructure and building projects are: delay in government approvals/permits, delay in preparation and approval in variation orders, client induced additional work beyond the original scope, changed engineering conditions from the contract document and decreased labor productivity due to extreme climatic conditions. All the above risk factors are rated as moderately critical to very critical in Kuwaits construction projects is very high. The five most critical time‐overrun factors identified in Kuwait’s infrastructure and building projects are: delay in government approvals/permits, delay in preparation and approval in variation orders, client induced additional work beyond the original scope, changed engineering conditions from the contract document and decreased labor productivity due to extreme climatic conditions. All the above risk factors are rated as moderately critical to very critical in Kuwait.

This paper aims to focus on developing a baseline model for time overrun.

Information on 321 completed construction projects used to assess the predictive performance of two statistical techniques, namely, multiple regression and the Bayesian approach.

The eventual results from the Bayesian Markov chain Monte Carlo model were observed to improve the predictive ability of the model compared with multiple linear regression. Besides the unique nuances peculiar with projects executed, the scope factors initial duration, gross floor area and number of storeys have been observed to be stable predictors of time overrun.

This current model contributes to improving the reliability of predicting time overruns.

Cost overrun of construction projects has been a key concern for all stakeholders of projects for many decades now. Many studies have been done in the past and continue to be done currently to understand the underlying causes of construction project cost overruns. However, the empirical evidence of the causes seem not be clear due to the silo approach in understanding the causes of construction project cost overruns. The purpose of this paper is to take the debate a step forward by providing an understanding of the causes of project cost overrun from a system’s perspective, especially from a less researched environment.

Data were collected and analysed from 131 respondents who were mainly involved in construction works in public procurement entities in Ghana. A two-staged approach was employed in collecting data from the respondents. The first stage involved an interview session with key informants in the construction industry in Ghana to ascertain the detailed causes of cost overrun of construction projects. The second stage focussed on the validation of these detailed factors by a wider stakeholder group through questionnaires. Factor analysis was employed to consolidate these detailed factors into major causes of construction project cost overruns.

The results show that there are primarily four major causes of most public sector construction projects cost overruns. These four major causes of cost overruns are poor contract planning and supervision; change orders; weak institutional and economic environment of projects and lack of effective coordination among the contracting parties.

The study provides more insights as to the critical and major factors that underpin public sector construction projects cost overruns and more importantly provides a basis for common treatment of the multiple risk factors engendering public sector construction projects cost overruns.

This paper aims to investigate the statistical validity of geotechnical risk factors in accounting for cost overruns in highway projects. The study hypothesises that “latent pathogens” because of mismanaged geotechnical risk, which lay dormant in organisational practices of highway agencies, trigger cost overruns.

To test this hypothesis, cost and geotechnical data gathered for 61 completed highway projects, executed in the Niger Delta, recording unusually high cost overruns, along with qualitative data from 16 interviews with the project commissioners, were comprehensively analysed via regression modelling, to statistically explain recorded cost variance.

The results provide empirical evidence supporting a cause–effect relationship between the extent of cost overrun and key geotechnical factors. It is suggested that positive changes made in the geotechnical practices of the highway agencies will produce an expected exponential decrease in the level of cost overruns recorded in highway projects.

The study is limited to explaining the propagation of unusually high cost overruns in the geologic setting of the Niger Delta region of Nigeria. As such there is a need to test the generalisability of the theory presented.

The emergent view of geotechnical practice calls for further research, necessary to align geotechnical best practice into highway project delivery in the Niger Delta region.

The study used a robust methodological approach to understanding the propagation of cost overruns in highway projects, based on a characterisation of geotechnical intricacies, which is unprecedented in cost overrun research.

Schedule and cost overrun analysis for a typical research & development (R&D) project is necessary to identify and mitigate the non-feasible alternatives at the design stage. Typically, this should include an analysis of technological and economic factors of R&D project. This paper aims to discuss these issues.

This research proposes an integrated analytic network process (ANP) and reusable system dynamics (SD) model for a quick and strategically consistent decision making. The technological and economic factors of R&D project were first identified and compiled through a systematic literature review. An ANP model was first developed for calculating Risk Priority Index (RPI) for set of technological and economic factors. The computed RPI are considered as an input to SD models. Two SD models (technological and economic) are developed to undertake a detailed investigation on effect of individual factor on schedule and cost overrun. The approach is exemplified for a case of government R&D project in India.

ANP identifies “Testing & qualification facility” and “Raw material availability” as the highest RPI factors. A detailed sensitivity analysis of SD models suggests that technological factors such as “Design Changes,” “Hidden Activities,” and “Lack of Expertise” and economic factors such as “Project delays,” “Unexpected incidents” and “Conflicts” have the highest influence on schedule and cost overrun.

The outcomes of this research can help managers to estimate the severity of various technological and economic factors on cost and schedule overrun and develop an adequate risk mitigation contingency plan.

In case of R&D projects where systems are being developed for the first time, changes are inevitable, and hence schedule and cost management plays a very important role in its success. This paper proposes an integrated reusable approach of ANP and SD for analyzing the influence of technological and economic factors on schedule and cost overrun of R&D project.

The purpose of this paper is to explore the impact that cost overruns and time delays exert on large public construction projects to clarify how past and current research regard factors causing cost overruns and time delays in large public construction projects.

This paper, which is based on an analysis of a literature selection consisting of 40 journal articles, investigates and ranks the occurrence of and the explanations for cost overruns and time delays in large public construction projects. The study makes use of a kiviat diagram/radar chart in order to visualize multivariate data.

Aggregated rankings of important causes of cost overruns and time delays are reported. These show a strong emphasis on the management aspect as a primary cause of cost overruns and delays. Additionally, there seems to be a trend toward deemphasizing the role of financial considerations in explaining cost overruns and delays. It is argued that there needs to be a more rigorous assessment of the impact that each factor has on cost increases and delays based on factual observed data as opposed to retrospective accounts from questionnaire respondents.

Only public construction projects have been considered. The results will not be directly applicable to privately funded construction projects and/or projects of a smaller size.

The use of trend data, as illustrated in a kiviat diagram, showing how different ranking factors causing cost overruns and time delays has changed in importance over time.

We investigate causes for the cost overrun and delay of the railway project Stuttgart 21. Besides, we try to forecast the actual costs and completion date at an early stage.

The results of exploratory research show the causes for the cost overrun and delay of Stuttgart 21; we compare our findings with other railway projects. To estimate the costs at an early stage, the reference class forecasting (RCF) model is applied; to estimate the time, we apply an OLS regression.

We find that the following causes are relevant for the cost overrun and delay of Stuttgart 21: scope changes, geological conditions, high risk-taking propensity, extended implementation, price overshoot, conflict of interests and lack of citizens' participation. The current estimated costs are within our 95% confidence interval based on RCF; our time forecast underestimates or substantially overestimates the duration actually required.

A limitation of our approach is the low number of comparable projects which are available.

The use of hyperbolic function or stepwise exponential discount function can help to give a clearer picture of the costs and benefits. The straightforward use of the RFC for costs and OLS for time should motivate more decision-makers to estimate the actual costs and time which are necessary in the light of the rising demand for democratic participation amongst citizens.

More realistic estimates can help to reduce the significant distortion at the beginning of infrastructure projects.

We are among the first who use the RCF to estimate the costs in Germany. Furthermore, the hyperbolic discounting function is added as a further theoretical explanation for cost underestimation.

Modeling represents the art of translating problems from an application area into tractable mathematical formulations whose theoretical and numerical analysis provides insight, answers and guidance useful for the originating application. The purpose of this paper is to determine the causal causes of schedule overrun and cost escalation of highway projects in Egypt in order to be used as independents variables in mathematical models for predicting the percentages of schedule overrun and cost escalation of such projects in Egypt.

A survey of a randomly selected samples yielded responses from 40 owners, 15 consultants and 56 contractors. The survey includes 38 schedule overrun factors and 26 cost escalation factors. The effectiveness degree of the identified factors has been identified by the triangle fuzzy approach.

The results of the survey show that “contractor’s technical staff is insufficient and ineligible to accomplish the project” is the most important cause of schedule overrun, while the major cause of cost escalation is inadequate preparation of the project concerning planning and execution.

The main contribution of this study is predicting the percentages of schedule overrun and cost escalation of highway projects in Egypt. Through the application of the linear regression analysis method and statistical fuzzy theory, four predictive models have been developed and it has been noted that the linear regression-based model shows prediction accuracy better than statistical fuzzy-based model in predicting percentages of schedule overrun and cost escalation.