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The delay in real estate projects in India is pervasive. Organization and management (O&M) and project management (PM)-related challenges are argued to contribute to project delays. This study examined the O&M and PM factors that cause delays, the level of implementation of various O&M and PM aspects in real estate projects and how the challenges can be alleviated.

Perception surveys among the consumers and relevant stakeholders engaged in real estate projects in the Bhubaneswar and Cuttack regions of India were conducted to collect data on the factors of delay and implementation of the O&M and PM aspects. Relevant statistical methods and structural equation modeling (SEM) were used for data analysis.

Findings suggest that from the O&M point of view, poor decision-making, mishandling of finance, concurrent execution of many projects, diversion and misuse of finance for unrelated activities, lack of PM personnel and poor management contribute to the delay. Further, although the project initiation is satisfactorily done, most of the PM principles are not largely used, thus leading to delay.

The study does have limitations, including its reliance on a perception survey of consumers and stakeholders, a limited sample size and a restricted number of projects. Nevertheless, the study highlights the need to address poor O&M and the insufficient application of PM principles to combat project delays in the Indian real estate sector.

Proper O&M and adequate application of PM will enable professional management of the projects and avoid delay.

Proper O&M and the application of adequate PM would reduce delays in real estate projects. Consequently, conflicts between the companies and consumers might be reduced and housing and infrastructure demands might be met.

The study manifested that the lack of adequate implementation of O&M and PM aspects leads to delays. So, it is theorized that O&M and PM play critical roles in the success of real estate projects. Appropriate implementation of the principles and best practices linked to these aspects might alleviate the challenges of delay in real estate projects in India.

In Bangladesh (BD), delays in infrastructure are common. Many previous studies have explored the causes of infrastructure delays. However, this study investigated the causes of delays by taking responses from the stakeholders who are responsible for planning, design, funding, approval and implementation. There are few studies that have related infrastructure project delays to heterogeneity in stakeholders’ perceptions.

A structural equation (SE) model is developed with 350 normally distributed data points to understand the heterogeneity in stakeholders’ perceptions regarding delays in infrastructure projects in BD. Additionally, the relative importance index (RII) approach is used to assess the responses, validating the SE model.

The study finds that among the three latent variables, “Project itself related delay” has more influence on delays in infrastructure projects. Among the observed variables under the “project itself related delay” latent variable, “DPP approval process” has the most significance. From the heterogeneity analysis, the study found differences in responses among the stakeholders from “the Engineering Department,” “the Planning Office” and “the Construction Firm/Industry.” An important class of stakeholders believes that their stage is not being delayed and that other stages require attention.

The data sample is 350. More data can improve the accuracy of the findings. Most of the respondents are civil engineers (74%) and represent the owner of the project. Sample data from more stakeholders’ will enhance the accuracy of the result.

This study addresses the requirements of Bangladeshi project stakeholders and how their interactions cause delays in projects. Furthermore, the opinions of other stakeholders are taken into consideration when determining the specific factors of individual stakeholders that are causing delays. Practically, the distance between stakeholders should be reduced. A project manager can play a role in this regard. Initiatives should be taken on how to complete the project quickly by eliminating the requirements discussed among the stakeholders and bureaucratic complications. Instead of placing blame on one another, stakeholders should take the initiative to figure out how to work together to finish the project on schedule. The Planning Commission’s approval of the Development Project Proposal (DPP) and Revised Development Project Proposal (RDPP) should be obtained as soon as possible by owner stakeholders. In order to avoid frequently changing the DPP, owners should also exercise greater caution when choosing contractors. Contractor stakeholders should use efficient and proper manpower and equipment so that unexpected delays are not created during the execution of work. Since the role of the contractor stakeholder is the most important among the three types of stakeholders, the contractor should raise awareness and urge the owners to get the RDPP approved quickly.

The findings from the study can help mitigate delays in infrastructure projects in BD, taking into account the perceptions of various stakeholders.

Construction delay always causes massive damage to the advancing construction industries, which is no different in the case of Bangladeshi construction industries. This paper aims to investigate the major delay factors causing construction delays in public-funded, mixed and private-funded construction projects of Bangladesh. Also, it offers preventive suggestions from expert stakeholders to reduce the recurrence of delays.

At first, an extensive literature review was conducted to identify the thirty-seven major delay factors categorized under seven groups. A questionnaire was then developed for survey at ongoing construction projects at a different division of Bangladesh. Next, data from 110 respondents were collected, and the delay factors were ranked based on the Relative Importance Index (RII); lastly, probable solutions were suggested for top-ranked delay factors based on opinions from expert stakeholders in the construction sector of Bangladesh.

The overall RII ranking of the 37 delay factors showed “Construction mistakes and defective work,” “Contract modifications by the client” and “Adverse weather condition” as the top three factors causing the delay. For public-funded projects, “Construction mistakes and defective work” and “Slow decision making by a consultant” are the top delay factors. For mixed projects, “Slow decision making of the client” and “Construction mistakes and defective work ranked top, and for private-funded projects, “Financial problems and payment delay of the client” and “Adverse weather condition” ranked top. These nuances of ranking in individual project types ascertain that the causes of delay vary in terms of project features.

The outcome of this project will help identify the significant delay factors based on their severity of effectiveness associated with public-funded, mixed and private-funded projects in Bangladesh. The suggestions regarding preventing these delay factors obtained through the opinions of expert stakeholders can help reduce the effect of these delays in the context of Bangladesh and in countries where the similarity in construction environment prevails.

Previously, studies on construction delays in Bangladesh focused mainly on identifying the delays using qualitative analysis techniques. This study is based on a unique methodology of integrating quantitative research on delay factor identification and qualitative research on preventive measures following the opinions gathered from expert stakeholders in the construction sector.

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.

Delays in utility shifting during road construction have broad ramifications. These delays not only lengthen the project's timeline but also raise expenses and cause problems with resource allocation. Thus, this study investigates the influence of delay in utility shifting for extension of time claims in road construction projects (RCPs) in Sri Lanka.

The study used a quantitative approach with three rounds of Delphi surveys to gather empirical data. Further, the probability impact assessment was used to carefully analyse the data and appraise the information gathered.

The findings initially revealed 33 causes of delays in utility shifting for extension of time claims in RCPs in Sri Lanka. Ultimately, 11 severe causes were identified based on their high probability and impact, concluding with 45 strategies that were assigned to overcoming those most severe causes of delay.

This study will contribute to the industry and theory by providing solutions to handle utility-shifting delays with the linkage of preventing time extension claims for RCPs in Sri Lanka. Further, there is a dearth of literature in the research area, both locally and globally. Thus, the findings of this research will provide a benchmark for further detailed studies in other countries as well.

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

The phenomenon of delayed payment to contractors, particularly in the construction industry, is a vital one and has implications for the health of economies of both developing and developed countries. However, the knowledge of this phenomenon seems patchy and scattered. This paper aims to provide a comprehensive overview of the knowledge on the subject matter with directions for future research.

A systematic literature review coupled with a scientometric analysis was used to identify the main strands of delayed payment to contractor research as a basis for qualitative analysis and directions for future investigations.

Current trends of delayed payment to contractor research are categorised into five broad themes, namely: causes, effects, mitigation measures, ethical and law and regulatory issues. On the basis of these themes, directions for future research are proffered.

To the best of the authors knowledge, this is the first attempt at providing a comprehensive and an integrated knowledge on delayed payment to contractor research with pointers for further investigation and policy directions.

Construction projects commonly encounter complicated delay problems. Over the past few decades, numerous delay analysis methods (DAMs) have been developed. There is no consensus on whether existing DAMs effectively resolve delays, particularly in the case of complex concurrent delays. Thus, the primary objective of this study is to undertake a comprehensive and systematic literature review on concurrent delays, aiming to answer the following research question: Do existing delay analysis techniques deal with concurrent delays well?

This study conducts a comprehensive review of concurrent delays by both bibliometric and systematic analysis of research publications published between 1982 and 2022 in the Web of Science (WoS) and Scopus databases. For quantitative analysis, a bibliometric mapping tool, the VOSviewer, was employed to analyze 68 selected publications to explore the co-occurrence of keywords, co-authorship and direct citation. Additionally, we conducted a qualitative analysis to answer the targeted research question, identify academic knowledge gaps and explore potential research directions for solving the theoretical and practical problems of concurrent delays.

Concurrent delays are a critical aspect of delay claims. Despite DAMs developed by a limited number of research teams to tackle issues like concurrence, float consumption and the critical path in concurrent delay resolution, practitioners continue to face significant challenges. This study has successfully identified knowledge gaps in defining, identifying, analyzing and allocating liability for concurrent delays while offering promising directions for further research. These findings reveal the incompleteness of available DAMs for solving concurrent delays.

The outcomes of this study are highly beneficial for practitioners and researchers. For practitioners, the discussions on the resolution process of concurrent delays in terms of identification, analysis and apportionment enable them to proactively address concurrent delays and lay the groundwork for preventing and resolving such issues in their construction projects. For researchers, five research directions, including advanced DAMs capable of solving concurrent delays, are proposed for reference.

Existing research on DAMs lacks comprehensive coverage of concurrent delays. Through a scientometric review, it is evident that current DAMs do not deal with concurrent delays well. This review identifies critical knowledge gaps and offers insights into potential directions for future research.

This study aims to review earned value management (EVM)-relative methods, including the original EVM, earned schedule method (ESM) and earned duration management (EDM(t)). This study then proposes a general implementation procedure and some basic principles for the selection of EVM-relative methods.

After completing an intensive literature review, this study conducts a case study to examine the forecasting performance of project duration using the EVM, ESM and EDM(t) methods.

When the project is expected to finish on time, ESM with a performance factor equal to 1 is the recommended method. EDM(t) would be the most reliable method during a project's entire lifetime if EDM(t) is expected to be delayed based on past experience.

As this research conducts a case study with only one building construction project, the results might not hold true for all types of construction projects.

EVM, ESM and EDM(t) are simple and data-accessible methods. With the help of a general implementation procedure, applying all three methods would be better. The power of the three methods is definitely larger than that of choosing only one for complex construction projects.

Previous studies have discussed the advantages and disadvantages of EVM, ESM and EDM(t). This study amends the available outcomes. Thus, for schedulers or researchers interested in implementing EVM, ESM and EDM(t), this study can provide more constructive instructions.

An S-curve is an essential project-management tool. However, it is difficult to adjust S-curve to deal with a force majeure event. The present study develops four valuable adjustment approaches, designed to achieve a compromise between the views of the client and contractor. These can be used to control projects after a force majeure event.

The present study develops four adjustment approaches, which can be used to achieve a compromise between the views of the client and those of the contractor when controlling projects after a force majeure. To determine the S-curves during a force majeure event, two approaches can be selected: BCWS (budgeted cost of scheduled work)-base approach, or BCWP (budgeted cost of work performed)-base approach. To determine the rest of S-curves after a force majeure event, two approaches can be considered: maintaining the original curve of the remaining BCWS, or allocating the original curve of the remaining BCWS. Based on the validation of three empirical cases, drawn from a professional project-management website, this study confirms the feasibility of four proposed empirical approaches and a selection procedure for S-curve adjustment.

The S-curve-adjustment approaches presented here can be used to deal with cases that are ahead of, on and behind schedule. Using the proposed approaches and selection procedure, contractors can easily revise S-curves and control projects more effectively. To deal with a force majeure event, such as COVID-19, they are strongly advised to adopt the approaches labeled SA-A1 (to adjust the S-curve based on the extension ratio multiplied by the difference in progress during the force majeure) and SA-B1 (to maintain the original curve of the remaining BCWS) for the A/E and E/F curves, respectively.

The proposed approaches can be used in cases of continuous construction during force majeure events. If construction work is totally suspended during such an event, it will be necessary to fine-tune the proposed approaches.

Previous studies have used case-oriented or mathematical-simulation approaches to forecast S-curves. The present study proposes simple approaches that allow the client and contractor to adjust the S-curve easily after a force majeure event. These approaches can be used to adjust work and project-completion targets within an extended duration. Selecting the right S-curve adjustment approach can help to control the remainder of the project, reducing the possibility of delay claims.