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The abandonment of governmental development projects either after completion or midway completion at the taxpayer’s expense in Ghana could be attributed to lack of effective community engagement (CE). Thus, this study aims to assess CE in development projects by comparing government-sponsored projects to private-sponsored projects.

A qualitative approach was adopted where a multiple case study design was used as a research strategy. Data was collected from selected districts in the Central Region of Ghana by using a semi-structured interview guide and analyzed using the thematic and comparative analysis techniques.

The results reveal that CE in government-funded projects was low, while CE in projects funded by private organizations was high. Three levels of engagement (consultation, participation in decision-making and consent) were also identified. Furthermore, the roles of public participation, including knowledge sharing, collective sense of ownership, among others, were ascertained. Finally, resources constraints, competing interests, lack of information flow, public attitudes toward change and central government/political interference are challenges of CE in development projects.

This study has provided an empirical basis for government and other development agents to draft a policy on CE to serve as a guide, spell out the role of CE, mitigate the challenges of CE and ensure strict compliance to the three levels of engagement.

Construction project stakeholders can have a major effect on delivering projects on time. However, little attempt has been made to address the influence of internal stakeholders on delaying project delivery. This research aims to propose the internal stakeholders' influence as a solution to improving project delivery performance (PDP) in order to boost the value of investment in the construction industry's projects.

In Yemen, a structured questionnaire was distributed to owners, consultants and contractors, 283 of which were found usable after the data screening. A purposeful sampling technique was used and structural equation modelling (SEM) was adopted for analysis. The structural model was drawn up, based on seven categories of influencing factors: labour, supplier, designer, contractor, consultant, sub-contractor and owner.

The results of the structural model suggest that of these seven categories, designers, owners, suppliers and subcontractors have a significant p-value and impact on PDP, while the labour and consultant's impact was not substantiated. The findings support the proposal that internal stakeholders' influence contributes directly to construction PDP.

The influence of stakeholders on PDP is important. Nonetheless, few studies have focussed on their effectiveness, especially in developing countries. This paper's contribution is evaluating the cause–effect relationship between stakeholders' influence and construction PDP through analysis of moment structures (AMOS) analysis. The policy implications of the research are to encourage governments in general and construction companies in particular to take responsibility for improving PDP, as slow execution of construction projects leads to increased costs, failure and abandoning projects.

This study aims to examine the association between community engagement, community commitment and sustainability of public–private partnership (PPP) projects in Uganda.

This study adopted a cross-sectional and quantitative approach. Data were collected using a questionnaire from 42 PPP projects in Uganda.

The study found that community engagement and commitment are all positively and significantly associated with the sustainability of PPP projects in Uganda. Results also show that community commitment mediates community engagement and project sustainability.

The study results imply that for sustainability to be achieved, communities must be engaged in project activities such as planning, design and implementation to boost their commitment to project sustainability.

The sustainability of PPP projects is an emerging phenomenon. This paper contributes to scanty literature on ensuring the sustainability of PPP projects from a developing country’s perspective.

This study aims to develop an interrelation model between critical parameters for assessing the construction readiness (CR) of abandoned housing projects, using Malaysia as a case study. To achieve that aim, the study objectives are to (1) identify critical parameters for assessing the CR of abandoned housing projects; (2) develop underlying constructs to categorize interrelated critical parameters and (3) assess the influence of the underlying constructs on the CR of abandoned housing projects.

This study identifies potential parameters for assessing the CR of abandoned housing projects by reviewing existing literature and interviewing industry professionals. Then, the list was used to develop a questionnaire survey. The collected survey data were analyzed using normalized mean analysis to identify the critical parameters. Exploratory factor analysis (EFA) was used to develop underlying constructs to categorize interrelated critical parameters. Finally, the influence of the underlying constructs on the CR of abandoned housing projects was examined through partial least squares structural equation modeling (PLS-SEM).

The analyses suggest that 21 critical parameters are affecting the CR of abandoned housing projects. The critical parameters can be categorized into four underlying constructs: construction site evaluation, management verification, uncertainties mitigation and document approval. Finally, the analyses confirmed that all four constructs affect the CR of abandoned housing projects.

This study is a pioneering effort to quantitatively analyze the parameters for assessing the CR of abandoned housing projects. The findings significantly benefit researchers and industry professionals by providing a list of critical parameters associated with the CR of abandoned housing projects.

This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain.

This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach.

Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase.

Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize.

This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.

The construction industry is beset with unethical behaviours. Although several studies have investigated the effects of unethical behaviours on project performance, research in the Ghanaian construction industry (GCI) remains scant. Consequently, this research assesses the interactive effects of ethical and unethical behaviours of construction professionals on project performance in the GCI.

A quantitative research approach was used to obtain primary data from 68 construction professionals, viz, quantity surveyors, architects, civil engineers, clerk of works and project managers, via a closed-ended questionnaire survey. Data collected were analysed using one-sample t-test and Kruskal–Wallis test statistics, after which two hypotheses were tested and validated using regression analysis.

Reduction of project risks, avoidance of legal problems and maximisation project quality performance were critical effects of ethical behaviours observed on project performance, whereas the effects of unethical behaviours such as cost overrun, abandonment and time overrun were severe on project performance in the GCI. Ethical behaviour was seen to relate to project performance positively, and unethical behaviour was proved to have dire consequences on project performance.

Construction project performance is greatly influenced by professionals' ethical and unethical behaviours. Emergent findings emanating from this research will assist emerging economies in developing and implementing counter policies and systems that mitigate the unethical behaviours of construction professionals.

The study highlights the effects of ethical and unethical behaviours on project performance to reorient individuals' perceptions that unethical behaviours are less critical in the construction industry. Supporting evidence encourages individuals to adhere to ethical behaviours in a project environment.

The inability to obtain data across the entire geographical spread of Ghana is acknowledged as a major limitation of the study and affects the generalisation of the results.

This study constitutes a first attempt to establish the interactive effects of ethical and unethical behaviours of construction professionals on project performance within the GCI. A significant addition to the body of knowledge is that ethical and unethical behaviours impact project performance positively or negatively, respectively.

It is widely accepted that one criterion for determining if a construction project is successful is whether it is completed within the expected budget. There have been advancements in the management of building projects throughout time but cost overruns remain a key concern in the construction sector internationally, particularly in emerging economies such as Ghana. This study aims to answer the question, “What are the critical success factors (CSFs) that can assist reduce cost overruns in public sector infrastructure projects in the Ghanaian construction industry?”

This study used a quantitative survey method. The questionnaire was pre-tested by interviewing 15 contractors to ascertain the validity of the content. Factor analysis and multiple regression were adopted to analyze the data.

This study discovered that the critical factors that can reduce cost overruns in construction projects in Ghana are directly linked to five themes: early contractor involvement in the project planning stage, adequate funding, good project team relations, competent managers/supervisors and project participant incentives/bonuses. This study identifies indestructible, empirically measurable important success criteria for reducing cost overruns in public building projects in Ghana.

When well thought through from the project initiation stage to completion, these critical successes can also be used to deal with damaging economic effects such as allocative inefficiency of scarce resources, further delays, contractual disputes, claims and litigation, project failure and total abandonment.

The uniqueness of this research resides in the fact that it is, to the best of the authors’ knowledge, a first-of-its-kind investigation of the CSFs for reducing cost overruns in public building projects in developing countries.

Claims are increasingly becoming a norm in construction projects and thus an area that is attracting interventions through researches. This paper aims to establish causes–effects relationship of claims in construction projects.

This is correlation study type of study that attempts to establish causes–effects relationship of claims in construction projects. Significant causes and effects of construction claims were determined using one-sample t-test. To establish the relationship, the significant causes and effects of construction claims were correlated using bivariate correlation analysis.

Among the significant causes, variations, change of scope of the project and delay in completion of works have high level of significant positive relationship with five to six other causes and positive relationship with multiple effects ranging from five to six. Besides, among significant effects, delay in completion and delivering of construction projects, poor contractual relationship among parties and extension of time have significant positive relationship with multiple causes.

The findings of this study are limited to causes-causes relationship and causes–effects relationship of claims in construction projects. This means effects–effects relationship was not covered that could be an important area to investigate as some of causes and effects are at times termed interchangeably.

With reference to previous studies which have focused on determining the causes and effects of construction claims, the findings of the current study have specific contribution on claims management as it divulges the causes of constructions claims that have multiplier effects to the project as a result of their linkage.

The paper unveils causes of claims with multiplier effects to construction projects for project participants to devise strategies to minimize and consequently eliminate them.

This paper aims to measure the severity, frequency and importance of the factors causing delays in the United Arab Emirates (UAE) construction industry following the Covid-19 pandemic onset. The study also measures the likelihood of the effects caused by these delays.

A mixed approach of both qualitative and quantitative. Literature review was conducted to extract 40 factors of delays and 10 effects of delays. A survey was then administered to construction professionals in the UAE to collect the perceptions on the severity and frequency of factors of the causes of delays using a Likert Scale of 1–5 where 1 represented very low and 5 represented very high. Similarly, the respondents were also asked to rate the likelihood of the occurrence of the effects of the delays based on a Likert scale of 1–5 as well. Furthermore, Spearman’s rank correlation was also conducted to compute the level of agreement between the different parties; owner, consultants and contractors.

The results revealed that the top five factors of delays include: award the project for the lowest bidder, delay in progress payment, change orders by the owner, poor subcontractor performance and inadequate planning and scheduling by the contractor. The findings of this study emphasize the financial challenges and economic crisis brought upon the construction industry due to the pandemic. Furthermore, the pandemic also shifted the perceptions of construction professionals, who are now more aware of the delays caused by awarding the project to the lowest bidder who would not have the required qualifications to conduct efficient planning and scheduling that are relevant in the case of extraordinary events such as Covid-19. Moreover, a high level of agreement between the consultants and contractors was observed, with a Spearman’s rank correlation of 0.804. Additionally, the most likely effects of delays concluded from this study were time overrun/extension and poor quality of work.

Literature review is very rich in the field of construction projects delays. However, there is very limited research on the impact of Covid-19 in the context of construction projects delays, and insights from construction professionals regarding this matter are particularly lacking in literature. Therefore, this paper bridges the gap in literature by providing perceptions of construction professionals on the impact of Covid-19 on the factors causing delays in the UAE construction industry. The findings of this research are expected to be an invaluable resource for future to help the construction industry heal faster when encountering similar epidemics or extraordinary events.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.