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This paper reports on an integrated prototype expert system, which has been developed to support geotechnical engineers during the initial foundation design phase. Foundation design based on Dutch practice and geotechnical codes as well as construction and project management aspects is programmed. The paper discusses an integrated approach to foundation design of buildings using a case‐demonstration to show the proposed system and its basis. The modelling techniques used offer a sound basis for including these aspects in routine geotechnical design. The example has indicated that the system is capable of integrating geotechnical design aspects with construction related aspects in order to produce better foundation design solutions.

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.

Cost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This study aimed to find possible statistical modelling techniques that could be used to develop cost models to produce more reliable cost estimates.

A bibliographic literature review was conducted using a two-stage selection method to compile the relevant publications from Scopus. Then, Visualisation of Similarities (VOS)-Viewer was used to develop the visualisation maps for co-occurrence keyword analysis and yearly trends in research topics.

The study found seven primary techniques used as cost models in construction projects: regression analysis (RA), artificial neural network (ANN), case-based reasoning (CBR), fuzzy logic, Monte-Carlo simulation (MCS), support vector machine (SVM) and reference class forecasting (RCF). RA, ANN and CBR were the most researched techniques. Furthermore, it was observed that the model's performance could be improved by combining two or more techniques into one model.

The research was limited to the findings from the bibliometric literature review.

The findings provided an assessment of statistical techniques that the industry can adopt to improve the traditional estimation practice of infrastructure projects.

This study mapped the research carried out on cost-modelling techniques and analysed the trends. It also reviewed the performance of the models developed for infrastructure projects. The findings could be used to further research to develop more reliable cost models using statistical modelling techniques with better performance.

A decade after Powell et al.’s (2011) seminal article on behavioral strategy, which called for models to solve real-world problems, the authors revisit the field to ask whether behavioral strategy is coming of age. The purpose of this paper is to explain how behavioral strategy can and has been used in real-world settings.

This study presents a conceptual review with case study examples of the impact of behavioral strategy on real-world problems.

This study illustrates several examples where behavioral strategy debiasing has been effective. Although no causal claims can be made, with the stark contrast between the negative impact of biased strategies and the positive results emerging from debiasing techniques, this study argues that there is evidence of the benefits of a behavioral strategy mindset, and that this should be the mindset of a responsible strategic leader.

This study presents a demonstration of analytical, debate and organizational debiasing techniques and how they are being used in real-world settings, specifically military intelligence, Mergers and acquisitions deal-making, resource allocation and capital projects.

Behavioral strategy has broad application in private and public sectors. It has proven practical value in various settings, for example, the application of reference class forecasting in large infrastructure projects.

A conceptual review of behavioral strategy in the wild.

This study aims to predict the construction cost in China, the authors purposed a fused method.

The authors extracted 22 factors which may influence the cost and performed the correlation analysis with cost. They chose the highest 10 factors to predict cost by the fused method. The method fused the Kalman filter with least squares support vector machine and multiple linear regression.

Ten factors which affect the cost most were found. The construction cost in China can be predicted by the presented method precisely. The statistical filter method could be used in the field of construction cost prediction.

The construction cost and construction interior factors are a business secret in China. So, the authors only collected 24 buildings’ data to perform the experiments.

There is no standard and precise method to predict construction cost in China, so the presented method offers a new way to judge the feasibility of projects and select design schemes of construction.

The authors purposed a new fused method to predict construction cost. It is the first time that the statistical filtering method was used in this field. The effectiveness was verified by the experiments. Ten factors which have a high relationship with construction cost were found.

This paper deals with the process followed to select investment projects within the construction industry with emphasis on the characteristics of infrastructure projects in developing countries. It presents an overview of the current practices in the main areas concerned with the process, namely project evaluation and decision‐making. The research carried out shows a process with a narrow scope and a lack of integration between the different techniques. The methodology described in this paper is developed to overcome such diffi culties and reduce some of the uncertainty that surrounds the selection of engineering projects. The proposed methodology has been tested and validated and results of the testing have been discussed and conclusions are drawn.

Chapter one of this valuable book focuses primarily on the construction industry and emphasises on thematic areas such as industry entities, including its social and economic impact supported by the workforce within the industry. The workforce, which consists of a wide variety of training, semi-skilled and unskilled labourers, is crucial to the building sector. These people are vital to the conception, management and accomplishment of construction projects in various industries. The chapter also highlights the lack of female gender involvement and how the gender gap would be filled.

This paper describes the development and initial use of a management game to teach project planning and control. It covers all aspects of the game including its design, the choice of the project to be modelled, the user interface and how it makes use of the computer power available. The sections on the use of the game describe experience gained in its use as part of an undergraduate course and as a demonstration on a course run for industry. Both the design and the use of the game are critically assessed and suggestions for improvement are made. The game was produced as a result of international collaboration between British and Dutch academics with input, where appropriate from construction companies of both nations.

The purpose of this paper is to help project management (PM) game designers and educators in simulating complexity in PM games and in assessing the effect of simulated project complexity levels on students’ learning experience. To achieve this aim, the authors attempt to design and evaluate two computer-based project crashing games (PCGs) with different complexity levels, namely project crashing game (PCG) and program crashing game (PgCG).

A literature review is conducted to identify serious games design principles. These principles are then manifested in the design of PCG and PgCG. The latter is a more complex version of the first. Students’ reaction after playing both games are then analyzed quantitatively.

The authors discover that students’ learning experience is affected by how complex the simulated project is. The more complex the project is (i.e. as in the PgCG), the more realistic the game is perceived. Nevertheless, the authors also discover that the less complex game (PCG) offers significant value to students, particularly to teach basic PM principles to those with minimum or no practical experience. This game is perceived as better in increasing students’ learning confidence as its content is perceived as more relevant to their existing knowledge.

The authors adopt a project complexity perspective when designing and evaluating the games.

The purpose of this paper is to explore how construction projects should be conceived and how the productivity of the construction industry impacts upon a nation’s wealth.

The approach has been to marshal the extant literature about the construction industry, construction industry productivity and the economic value of the built environment. Whilst there are many lenses that are used to understand the industry, different ways to measure productivity performance and differing practices between nations, it has been determined that construction industry productivity improvement significantly lags behind other industries.

There is a strong argument that construction productivity improvement correlates to advances in a nation’s economy. Nonetheless, it is the decisions about the nature of infrastructure, the standardisation of infrastructure and the effect upon labour productivity that will have the greatest implications for a nation’s economic future. These economic improvements will be inhibited by legacy infrastructure, particularly in densely populated areas. If substantial innovation occurs, the nations currently holding the highest stock of infrastructure might be economically constrained.

The construction industry is highly fragmented and has the uncertainties of a cyclic industry. It is, therefore, necessary for governments to identify standards and facilitate innovation. The implications for short- and long-term economic performance require that the industry is a fundamental at the highest level of government.

Scholars can use the propositions to further analyse construction productivity improvement and the provision of different types of infrastructure with regard to a nation’s economic performance. Hypotheses are offered to support future research.