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1 – 10 of over 1000This 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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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Ozan Okudan, Murat Cevikbas and Zeynep Işık
The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for…
Abstract
Purpose
The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.
Design/methodology/approach
The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.
Findings
The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.
Originality/value
Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.
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Farshad Peiman, Mohammad Khalilzadeh, Nasser Shahsavari-Pour and Mehdi Ravanshadnia
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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)).
Practical implications
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.
Originality/value
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.
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Wensheng Lin, Guangbin Wang, Yan Ning, Qiuwen Ma and Shuyuan Dai
Megaproject performance measurement (MPM) has received great attention in the project management community, but it primarily focused on the design of performance measures or…
Abstract
Purpose
Megaproject performance measurement (MPM) has received great attention in the project management community, but it primarily focused on the design of performance measures or frameworks. Yet, whether MPM utilization can improve megaproject performance and how project actors use MPM to improve megaproject performance is less well understood. This study aims to investigate whether and how the use of MPM can contribute to better megaproject performance.
Design/methodology/approach
Through the lens of the lever of control, this study conceptualizes MPM utilization as diagnostic use and interactive use. A holistic research model and related hypotheses integrating MPM use, project complexity and megaproject performance were established. The model was validated using a partial square-structural equation modeling method.
Findings
Based on 214-megaproject data collected through a questionnaire survey in China, the results show positive effects of diagnostic use and interactive use on megaproject performance. Both, however, have substitutional interaction effects. The moderating results suggest that the higher project complexity weakens the positive effects of MPM utilization on megaproject performance.
Originality/value
This study advances megaprojects performance measurement and management literature by validating the value of MPM utilization on performance. It also presents practical implications for project managers to improve performance by appropriate MPM utilization.
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Mojdeh Naderi, Ahad Nazari, Ali Shafaat and Sepehr Abrishami
This study addresses the prevailing complexities and limitations in estimating and managing construction overhead costs (COCs) in the existing literature, with the purpose of…
Abstract
Purpose
This study addresses the prevailing complexities and limitations in estimating and managing construction overhead costs (COCs) in the existing literature, with the purpose of enhancing the accuracy of cost performance indicators in construction project management.
Design/methodology/approach
An innovative approach is proposed, employing the activity-based costing (ABC) accounting method combined with building information modelling (BIM) to assign real overhead costs to project activities. This study, distinguished by its incorporation of a real case study, focuses on an administrative building with a four-story concrete structure. It establishes an automated method for evaluating project cost performance through the detailed analysis of earned value management (EVM) cost indicators derived from ABC results and BIM data.
Findings
The results show that the ABC integration improves the accuracy of cost performance indicators by over 9%, revealing the project's true cost index for the first time and demonstrating the substantial value of the approach in construction engineering and management.
Research limitations/implications
The current study highlights a notable gap in the existing literature, addressing the challenges in onsite overhead cost estimation and offering a solution that incorporates the state-of-the-art techniques.
Practical implications
The proposed method has significant implications for project managers and practitioners, enabling better-informed decisions based on precise cost data, ultimately leading to enhanced project outcomes.
Originality/value
This research uniquely combines ABC and BIM, presenting a pioneering solution for the accurate estimation and management of COCs in construction projects, adding significant value to the current body of knowledge in this field.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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Seyed Ashkan Zarghami and Ofer Zwikael
A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key…
Abstract
Purpose
A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.
Design/methodology/approach
This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.
Findings
The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.
Originality/value
This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.
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Jeffrey S. Russell, Islam El-adaway, Ramy Khalef, Fareed Salih and Gasser Ali
Project management (PM) involves planning, allocating, directing and controlling project resources within a set of predetermined objectives. The modern definition of PM has…
Abstract
Purpose
Project management (PM) involves planning, allocating, directing and controlling project resources within a set of predetermined objectives. The modern definition of PM has evolved and grown into a broader concept. This paper supports the notion that PM evolved into four distinct phases: PM 1.0 is primarily concerned with planning, PM 2.0 with collaboration, PM 3.0 with proactive adaptation and PM 4.0 with using innovative technologies. Research efforts tackled critical aspects of PM, but none of them provided a clear foundation for the full context of PM principles and how they complement one another. This study fills this knowledge gap by investigating the evolution of PM over time.
Design/methodology/approach
The authors collected a dataset of research papers between 1960 and 2022 and performed a bibliometric analysis on the collected dataset to isolate the main trends that define the evolution of PM phases.
Findings
Results show that all PM phases overlap in terms of overarching themes, concepts, principles and contributions. More importantly, PM 5.0 may be around the corner to facilitate effective and efficient handling of time, cost, scope and risks within the ever-growing complexity of project initiatives.
Originality/value
This paper provides a data-driven study for a holistic understanding of the key trends in PM and the associated expectations of future research directions. This will be of interest to stakeholders within the overall PM domain and multidisciplinary work related to the construction industry.
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Mehmet Bulent Durmusoglu and Canan Aglan
The inherent variability on process times and demand are the factors that prevent the efficient application of lean philosophy in multi-project product development (PD…
Abstract
Purpose
The inherent variability on process times and demand are the factors that prevent the efficient application of lean philosophy in multi-project product development (PD) environments. Considering this variability, a hybrid push–pull project control system is developed, and value stream costing (VSC) analysis is performed to reflect the relation between project lead time, capacity and project cost. The assessment of the push/pull project control on lead time improvement and long-term savings on capacity have been aimed with the proposed complete design structure.
Design/methodology/approach
In a team-based structure, formed through clustering, push control techniques for planning tasks within cross-functional teams and pull control techniques for planning tasks between cross-functional teams are developed. The final step evaluates the proposed structure through VSC and long-term savings have been pointed out, especially in terms of freed-up capacity. For the validation of the proposed methodology, an office furniture manufacturing firm’s PD department has been considered and the performance of the hybrid system has been observed through simulation experiments and based on the simulation results, the lean system is evaluated by VSC.
Findings
The results of simulation experiments show a superior performance of the proposed hybrid push/pull project control mechanism under different settings of cycle time between projects or shortly project cycle time, dispatching rules within teams and variability levels. The results of the Box-Score (tool to apply VSC) indicate increased capacity in the long term to add extra projects during the planning period with the same project lead time and without additional cost.
Research limitations/implications
Although extensive simulation experiments have been performed to quantify the effect of project control structure and positive results have been reported on lead time and cost, the proposed design structure has not been tested in all existing PD environments.
Originality/value
To the best of authors’ knowledge, the quantification of the effect of hybrid project control with VSC is the first attempt to be applied in lean PD projects.
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Kaouther Toumi and Amal Hamrouni
The study aims to investigate the Shari’ah governance quality effectiveness, at the bank and national levels, on the value relevance of Islamic banks’ (IBs’) earning per share and…
Abstract
Purpose
The study aims to investigate the Shari’ah governance quality effectiveness, at the bank and national levels, on the value relevance of Islamic banks’ (IBs’) earning per share and book value per share.
Design/methodology/approach
Quantitative analyses are conducted using a panel of 40 listed IBs from 12 countries during 2012–2019. Data were retrieved from the Refinitiv Eikon database and banks’ annual reports.
Findings
The findings suggest that Shari’ah supervisory boards’ attributes negatively influence the value relevance of accounting information while the internal procedures positively impact it. The results also provide evidence of a complementary effect between Shari’ah governance mechanisms at the bank and national levels on the value relevance of accounting information.
Practical implications
IBs’ boards and managers need to be more aware of the role of Shari’ah governance and its impact on value relevance. The observed complementarity between Shari’ah governance systems at the bank and national levels may incite regulators to include comprehensive Shari’ah governance regulations in their best practices. Strengthening collaboration between regulators and the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) is also required to create an enabling environment for investors to rely on the AAOIFI accounting standards in their investment decision-making process.
Originality/value
Existing studies tend to ignore the effectiveness of Shari’ah governance quality at the bank level on value relevance. There is a similar lack of empirical research on the effectiveness of the centralized Shari’ah governance scheme on accounting issues.
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