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This study aims to develop an ex-post impact evaluation method for public-private partnership projects (PPP) that addresses one of its main difficulties: the multiplicity of perspectives and stakeholders that exist in these projects.

This study first developed a conceptual evaluation framework called ‘Project Success Evaluation Pyramid Model’ (PSEPM) that was designed using a Design Science approach. Second, an impact evaluation method was designed based on the PSEPM. This evaluation method was tested and refined using three PPP projects. This article presents the refined conceptual model PSEPM, the evaluation method and one of the three tests: the PPP toll road.

The impact evaluation method describes how to evaluate the impact of an existing mega project from the perspective of multiple stakeholders and isolate the impact of the procurement method. Its application in practice is demonstrated with a PPP toll road project in Chile, in which 11 stakeholders were identified. Issues such as city segregation, deficient business model, the relevance of infrastructure availability, and deficient service-fee strategy were identified in the project. The evaluation method provides a judgement about the use of the PPP procurement method and about the overall impact of the project, reconciling the stakeholder perspectives.

The use of this approach could give greater clarity and legitimacy to the discussion over the use of PPPs by evaluating existing projects beyond the use of traditional time and cost measurements. Its originality is the systematic recognition and identification of stakeholder motives, purposes, and judgements over a project.

Delay and disruption claims involve a complex process that often result in disputes, unnecessary expenses and time loss on construction projects. This study aims to review and synthesize the contributions of previous research undertaken in this area and propose future directions for improving the process of delay and disruption claims.

This study adopted a holistic systematic review of literature following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A total of 230 articles were shortlisted related to delay and disruption claims in construction using Scopus and Web of Science databases.

Six research themes were identified and critically reviewed including delay analysis, disruption analysis, claim management, contract administration, dispute resolution and delay and disruption information and records. The systematic review showed that there is a dearth of research on managing the wide-ranging information required for delay and disruption claims, ensuring the transparency and uniformity in delay and disruption claims’ information and adopting an end-user’s centred research approach for resolving the problems in the process of delay and disruption claims.

Complexities in delay and disruption claims are real-world problems faced by industry practitioners. The findings will help the research community and industry practitioners to prioritize their energies toward information management of delay and disruption claims.

This study contributes to the body of knowledge in delay and disruption claims by identifying the need for conducting more research on its information requirements and management. Subsequently, it provides an insight on the use of modern technologies such as drones, building information modeling, radio frequency identifiers, blockchain, Bigdata and machine learning, as tools for more structured and efficient attainment of required information in a transparent and consistent manner. It also recommends greater use of design science research approach for delay and disruption claims. This will help to ensure delay and disruption claims are the least complex and less dispute-prone process.

The purpose of this paper is to study the nature of request for information (RFIs) on construction projects by using data analytics to understand the frequency of RFIs, when they occur on projects, and the relationship between project characteristics and frequency of RFIs and between project characteristics and RFI turnaround time.

A data-analytic approach using RStudio and Minitab software on 168 construction project cases in Australia and New Zealand involving 1,032,949 correspondences and 53,042 RFI event records made available by Aconex, one of the world largest cloud-based project management platform.

Large and complex projects tend to have significantly larger number of RFI events per day and longer RFI turnaround when compared with smaller and less complex projects. Projects with fewer users per organisation recorded a higher RFI turnaround time when compared with projects with more users per organisation – users mean persons involved in managing the project using the online platform (an index of project complexity). RFIs occur early on less complex projects and occur later on more complex projects.

Benchmarks of RFI incidences and turnaround time have been developed for various project characteristics and, practitioners can use them to monitor the RFI performance of projects. Organisations need to pay greater attention to staffing levels needed to handle RFIs to reduce RFI turnaround time.

A data-analytic study of RFI yielded insights for managing RFIs. The findings of previous studies on RFIs are difficult to generalise because they are based on single project case study. The influence of project characteristics on RFI frequency and RFI turnaround time is not yet known.

While the general trends in green building (GB) research are known, there is not yet a detailed review of studies on project delivery attributes (PDAs) influencing GB project outcomes. The purpose of this paper is to review the literature to understand the contributions of existing research in this area and to identify the challenges, gaps, and lessons for the future research relating GB project delivery.

For the systematic review, specially developed coding based on Boolean operators is used to search for relevant studies in major databases, i.e. Web of Science and Scopus. The studies from the initial search (443) are subjected to two rounds of scrutiny for shortlisting only relevant publications. Using a qualitative review of the shortlisted studies (20), the research objectives and findings of the studies are synthesized and critically analyzed. The contributions and challenges facing research in this area are identified. Future research directions are proposed.

Studies in the area have established association between PDAs and various GB project success criteria. In the literature, some PDAs such as project delivery method have been given greater attention than others. Challenges facing PDA research in GB include: the limited number of GB project cases and the complexity of GB project delivery process involving an overwhelmingly large number of variables, thereby limiting scientific rigor and creating some gaps in knowledge. The interaction among PDAs and their cumulative effect on various project performance outcomes/metrics have not been studied, limiting the validity of the existing studies. Scope exists to apply a combination of non-linear, dynamic, probabilistic, explicit, and implicit modeling as well as inductive and deductive approaches to research in this area.

Existing research findings have limited application in practice. Non-linear, dynamic, probabilistic, deductive, and inductive research techniques and approaches can substantially advance knowledge and lead to plausible findings that can be applied in practice.

Considering the critical role of PDAs in the successful delivery of GBs, the review provides clear directions for future research.

The purpose of this paper is to explore, in literature and practice, the use of ex post impact evaluations within the public–private partnership (PPP) context and understand the major considerations for developing a PPP ex post impact evaluation method.

This paper applies exploratory research through expert interviews from Chile and Australia to describe: the relevance of this kind of evaluation, and the challenges of designing and conducting a PPP ex post evaluation.

The study confirms the lack of a formal method for evaluating the impact of a PPP project. Experts agree on the relevance of performing ex post evaluations to PPP projects and that in practice there is no formal procedure to follow. Among other challenges, experts discussed four general ex post evaluation aims: transparency and accountability, PPP legitimization, industry learning and government agency learning.

This study confirms the gap in knowledge and contributes to the developments of approaches to perform ex post impact evaluation of PPP projects. It also provides several suggestions that need to be addressed when attempting to evaluate PPPs beyond the financial and contractual parameters.

The topic is not fully addressed in the literature, and this study contributes to the initial discussion and development of this evaluation method, which is considered significant for the development of public infrastructure.

The purpose of this paper is to develop an analytical decision-support model and a procedure that will help project management team to measure project scope definition, for completeness. The procedure is different from previous studies because the measurement of scope definition completeness accounts for differences in stakeholders’ interest and importance on project.

Data collection and analysis was based on semi-structured interviews in three steps with a total of 46 respondents. The first step identified stakeholders with an interest in public building projects while the second step identified the scope elements that serve as input to defining the project scope as well as elements that each stakeholder should be involved when measuring project scope definition, for completeness. In the third step, AHP was used to identify and prioritise the contributions required from various stakeholders when measuring scope definition completeness for 42 scope elements.

An evaluation framework to measure project scope definition completeness for public building projects in Saudi Arabia based on the input of stakeholders in accordance to their importance weights.

The prioritised weights of stakeholders’ importance in each element can be used by project managers and decision makers to reduce inefficiency and waste of time in the project scope definition process when evaluating scope definition for completeness.

The study reported in this paper proposed the use of artificial neural networks (ANN) as viable alternative to regression for predicting the cost of building services elements at the early stage of design. The purpose of this paper is to develop, test and validate ANN models for predicting the costs of electrical services components.

The research is based on data mining of over 200 building projects in the office of a medium size electrical contractor. Of the over 200 projects examined, 71 usable data were found and used for the ANN modeling. Regression models were also explored using IBM Statistical Package for Social Sciences Statistics Software 21, for the purpose of comparison with the ANN models.

The findings show that the cost forecasting models based on ANN algorithm are more viable alternative to regression models for predicting the costs of light wiring, power wiring and cable pathways. The ANN prediction errors achieved are 6.4, 4.5 and 4.5 per cent for the three models developed whereas the regression models were insignificant. They did not fit any of the known regression distributions.

The validated ANN models were converted to a desktop application (user interface) package – “Intelligent Estimator.” The application is important because it can be used by construction professionals to reliably and quickly forecast the costs of power wiring, light wiring and cable pathways using building variables that are readily available or measurable during design stage, i.e. fully enclosed covered area, unenclosed covered area, internal perimeter length and number of floors.

Previous studies have concluded that the methods of estimating the budget for building structure and fabric work are inappropriate for use with mechanical and electrical services. Thus, this study is unique because it applied the ANN modeling technique, for the first time, to cost modeling of electrical services components for building using real world data. The analysis shows that ANN is a better alternative to regression models for predicting cost of services elements because the relationship between cost and the cost drivers are non-linear and distribution types are unknown.