Identifying Innovative Reliable Criteria Governing the Selection of Infrastructures Construction Project Delivery Systems

Meshref, Ahmed Nouh; El-Kasaby, El-Sayed; Wageh, Omnia

doi:10.1515/eng-2021-0028

Cited by 12 publications

(5 citation statements)

References 43 publications

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“…Unfortunately, the matching degree between project characteristics and the EPC model does not significantly affect owners' perceived usefulness of the EPC model, nor does it significantly affect the adoption behavior of the EPC model. This suggests that although previous studies have shown that the matching degree between project characteristics and the EPC model is an influential factor in the EPC model-adoption behavior [57], its impact on the EPC-adoption behavior is low compared with other factors. The possible reason is that China is currently in the early stage of promoting the EPC model, and whether public project owners adopt the EPC model is influenced more by policies and owner characteristics than by project characteristics.…”

Section: Key Findingsmentioning

confidence: 82%

Drivers of Engineering Procurement and Construction Model Adoption Behavior by Public Construction Owners in China

2023

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The promotion of the EPC model in public construction projects is a priority for reform in the Chinese construction industry. This study integrates the push–pull–mooring (PPM) model with the stimulus-organism-response (SOR) framework to explore the influencing factors and action mechanisms of adopting the EPC model of the owners of public construction projects in China. An online questionnaire was sent to public construction project owners who have participated in EPC projects. Partial least squares-structural equation modeling (PLS-SEM) was employed to analyze the survey data. The results identified that the push factors for public construction project owners to the adoption of the EPC model include owners’ management ability, owner’s knowledge about EPC, and the matching degree between the owner’s management philosophy and EPC model; the pull factor is the performance pressure of the project; and the mooring factors include subjective norms, the maturity degree of the EPC, and the support environment. In addition, perceived usefulness, cognitive, and adoption attitude play a mediating role in the relationship between external stimuli and adoption behavior. Overall, this study enhances the understanding of Chinese public project owners’ behavior in adopting the EPC model and provides a theoretical basis for policy recommendations to promote the adoption of the EPC model by public construction project owners in China.

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Section: Key Findingsmentioning

confidence: 82%

Drivers of Engineering Procurement and Construction Model Adoption Behavior by Public Construction Owners in China

2023

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“…Selection of the contractor depends on qualifications or best value which is a procurement strategy that considers a combination of factors, including cost, qualifications, expertise, and reputation, to select a contractor or service provider that offers the most advantageous overall value for a project. The range of APDMs comprises methods like Design-Build (DB), Construction Manager at Risk (CMAR), Integrated Project Delivery (IPD), and many others [21,22].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Among these methodologies, the traditional Design-Bid-Build (DBB) framework [19], Design-Build (DB) which integrates design and construction to overcome some of the hurdles [20] and one of the alternative delivery methods that is rapidly growing in popularity Construction Manager at Risk (CMAR) [21] will be focused. Additionally, as traditional project delivery systems used in the general construction sectors have many constraints [22], Integrated Project Delivery (IPD) which is an integrated delivery approach to the planning, design, and construction of civil engineering projects [23] and "an approach to enhance project implementation" [24], along with other innovative approaches.…”

Section: Introductionmentioning

confidence: 99%

Restoration manager: Adapting project delivery methods for the restoration of architectural heritage

Aktuna,

Eskici

2024

Turkish Journal of Engineering

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The restoration of architectural heritage is a complex process and presents intricate and formidable challenges. The project delivery method plays a pivotal role for the success of the restoration process. There exists a diverse array of project delivery methods, each characterized by its distinct set of advantages and disadvantages. In the context of architectural heritage restoration, given its distinct characteristics, these advantages and disadvantages encompass a wide spectrum. Current project delivery methods, while effective for certain contexts, often fall short in addressing the unique requisites of restoration projects. Acknowledging this inadequacy, this article undertakes a research that includes a literature review that not only examines prevailing project delivery methods but also articulates the need for a tailored framework within the restoration field. This article is produced from the doctoral thesis titled "Development of a Sustainable Integrated Management System for the Conservation of Architectural Heritage", which is in the process of preparation. In the light of the results of the survey which is conducted within the scope of the first author's doctoral study in order to examine the project delivery approach preferred among the participants that are working in the field of the conservation of architectural heritage, a project delivery method called "Restoration Manager", which has been precisely prepared to meet the requirements inherent in restoration initiatives, is presented. This comprehensive project delivery method seeks to fill the void by addressing the distinct needs and challenges encountered in restoration projects. The essence of this work is to create an appropriate project delivery system that adapts to the nuances of the restoration works, and through this project delivery framework, the restoration processes and outcomes will successfully be completed.

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“…Simo's procedure Simo's procedure was used in several studies to obtain the weights of multiple factors based on the opinions of experts. This method can be applied based on a card playing procedure wherein different factors are classified into different clusters, which are ranked and weighted (Meshref et al, 2021). Experts evaluated each cluster: project data and organizational data.…”

Section: Construction Project Using Doementioning

confidence: 99%

Establishment of prediction system for cost of defect liability phase in construction project

Nouh

El-Kasaby

Hussein

2022

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Purpose This study aims to establish a new system to predict the defect liability phase (DLP) cost using the Six Sigma methodology, which investigates sources of variations and reduces the error level to 3.4 per million through five phases: define, measure, analyze, design and verify. Design/methodology/approach After the initial handover of the construction project, the DLP follows the practical completion. During this stage, the contractor is responsible for the remedy of any defects that appeared in the project. Many researchers have studied defect reasons and their associated costs in different industries, while the construction industry remains a green field for this kind of research. The objective of this study was to develop a model to predict the DLP cost. The research methodology adopted the five stages of the Six Sigma cycle: defining objectives, measuring the data, analyzing performance, designing the model and verifying the results. Twenty factors were identified as potential factors affecting the DLP cost. Factors were categorized into two main clusters: project data and organization data. Interviews were conducted with 42 project management experts, who have 8–35 years of experience in construction project management, to rank the 20 factors based on their importance. Simo’s procedure was used to obtain the weight of each factor affecting the DLP cost based on the opinions of the experts. The Pareto principle was used to select the “Vital Few” factors affecting the DLP cost, and six factors were selected. The design of experiments (DOE) was used to establish a dynamic model to predict the DLP cost using a sample of 41 construction projects obtained from the above-mentioned 42 project management experts. The model accuracy was verified using data obtained from a different sample of five construction projects, which were not used to establish the model. Findings The results showed that among the 20 factors, only six were found to have a cumulative impact of 50% over the cost of the DLP: type of project, project contract value, nationality of the employer, project manager experience, DLP duration and sector of the employer. A model was established through the DOE to predict the DLP cost using the values of the aforementioned factors. Research limitations/implications As a natural limitation of using DOE, the newly developed model can be applied to predict the DLP cost based on data within the range of data used during the model development, which means that model is confined within the specific measured values of factors. Furthermore, it will be beneficial for future studies to study the impact of other factors related to the types of materials or equipment used in building the project because it was not considered during this study because of the huge diversities in these factors and difficulties in determining its impact on the DLP cost. Practical implications The unique results of using DOE through Minitab software facilitated obtaining of a dynamic model, which means that researchers can modify any value of the six factors and monitor instantly the expected change in the DLP cost, which will allow a better understanding of the impact of each factor on the DLP cost. Moreover, the new model will help contractors to predict the expected DLP cost to be added for their project budget, which will mitigate the risk of cost overrun resulted from the cost of defect rectification. Originality/value A dynamic model was established to predict the DLP cost using the DOE. The new model was validated, and the prediction error ranged from −18% to +21%.

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Identifying Innovative Reliable Criteria Governing the Selection of Infrastructures Construction Project Delivery Systems

Cited by 12 publications

References 43 publications

Drivers of Engineering Procurement and Construction Model Adoption Behavior by Public Construction Owners in China

Drivers of Engineering Procurement and Construction Model Adoption Behavior by Public Construction Owners in China

Restoration manager: Adapting project delivery methods for the restoration of architectural heritage

Establishment of prediction system for cost of defect liability phase in construction project

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