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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.

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.

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.

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.

The purpose of this paper is to propose a disruption claim management (DCM) life cycle and a risk management framework to provide comprehensive guidance to construction practitioners for facilitating effective and efficient DCM.

DCM life cycle was initially developed through a focus group discussion (FGD) with the participation of the construction practitioners who have diverse experiences about DCM. The life cycle is comprised of 6 phases and also includes proper reactions of the owners and contractors. Then, 42 risk factors that can impact the deliverables of DCM were identified through a literature review and an additional FGD session. This was then followed by a Fuzzy Analytical Hierarchy Process (FAHP) which was performed to evaluate the importance of each risk factor in terms of the factor's impact on the success of DCM. Additionally, consistency analysis was performed to further maximize the reliability of the results.

Findings revealed that a proactive and systematic approach should be adopted and DCM practices should be initiated before any disruption event is triggered. Accordingly, the proposed framework recommends DCM practices to be initiated early in the contract development phase since compensation for the disruption might be recovered only to the extent that the contract permits. The contract-related risks were given top priority by the experts so that the results of the fuzzy AHP analysis also verified the significance of the contract development phase. Besides contract-related risks, risks related to insufficient site observation, ignorance of the project team, cognitive bias and conflict of interest were determined as the most significant DCM risks, needing an urgent and sophisticated risk response plan. Lastly, results suggested that “Site observation and record-keeping” is the most formidable phase since the phase's implementation on a continuous basis could create unforeseen organizational challenges such as mismanagement of project records, especially in the dynamic and turbulent environment of the construction projects.

Disruption – which is caused mostly by change – is inevitable in construction projects due to their sophisticated nature. DCM, therefore, becomes crucial to compensate losses of contractors and eliminate or diminish the prolonged dispute resolution process. Existing studies, however, do not provide a comprehensive theoretical basis for the DCM life cycle and DCM life cycle's potential risks so that DCM life cycle's promising benefits can hardly be materialized. Thus, developing a DCM life cycle and associating DCM life cycle with risk management, this study is highly believed to make a promising theoretical contribution to the DCM domain since this is one of the earliest attempts in the literature. Additionally, this research provides construction practitioners with an insight into the effective implementation of DCM practices in construction projects.

The purpose of this study is to develop a decision-support framework that can be used by decision-makers to suspend public infrastructure projects. Additionally, the study also investigates how to select the most convenient infrastructure project for suspension.

The proposed framework includes an extensive set of factors and a novel comparison mechanism that can reveal the most convenient infrastructure project to be suspended. A comprehensible literature review and focus group discussion (FGD) sessions were conducted to identify factors that should be considered for suspension. Then, the neutrosophic analytic hierarchy process (N-AHP) method was used to determine the relative importance of the factors. Finally, the proposed comparison mechanism was demonstrated through a hypothetical case study and Technique for order of preference by similarity to ideal solution (TOPSIS) analysis.

Results showed that suspension decisions cannot be made merely based on “financial” factors. Instead, the other aspects, namely “Technical and managerial” and “Social and Environmental”, should also be taken into consideration. Second, factors related to the initial investment, cost of refinancing, cash flow, permits and approvals, insufficiency of bidders, degradation of the components, reputation, impact on stakeholders and criticality of the infrastructure were particularly elaborated as the most significant, needing the utmost attention of the decision-makers. Lastly, the results demonstrated that the proposed comparison mechanism has considerable potential to identify the most convenient infrastructure project for suspension.

Public infrastructure projects are often under pressure due to the inflationary state and economic stagnation of countries after major crises. The suspension decision for infrastructure projects necessitates comprehensible assessments to consider all consequences. Studies have widely investigated the contractual and legal aspects of project suspension in light of existing literature. However, little effort has been devoted to identifying the factors that decision-makers should consider before suspending a particular infrastructure project. Furthermore, existing literature does not investigate how to select the most convenient infrastructure project for suspension either. Thus, by developing a specific suspension framework for infrastructure projects by considering various factors, this study is the earliest attempt to examine the contract suspension mechanism of public infrastructure projects. In this respect, the study significantly contributes to the theory of contract management domain and has important managerial implications.

The purpose of this paper is to identify and prioritize key performance indicators (KPIs) that can be used for stage-based performance assessment of build-operate-transfer (BOT) projects.

This research was conducted through focus group discussions and face-to-face questionnaires. Firstly, stage-level KPIs for BOT projects were identified by conducting a literature survey. The list of KPIs that can be used for measuring performance at different stages of a BOT project was finalized by conducting focus group discussions with 12 participants. The data related to the importance of identified KPIs were collected via a face-to-face questionnaire in which 30 high-level managers participated. Based on these data, KPIs were prioritized considering eight different stages of a BOT project by using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

The research findings reveal that 63 stage-level KPIs can be used for measuring the performance of BOT projects at eight different stages, which are “feasibility study and preliminary plan,” “announcement and submission of application,” “evaluation and selection,” “negotiation and signing of concession agreement,” “design,” “construction,” “operation” and “transfer.” The most important KPIs were determined as “comprehensiveness of project technical feasibility,” “detailed tendering procedure,” “effectiveness of concessionaires' technical knowledge/capability evaluation,” “good relationships between government and concessionaire,” “technology transfer,” “effectiveness of quality control,” “effectiveness of facility management” and “effectiveness of hand-back management” for each stage. The findings can be used by companies to evaluate performance at each stage of a BOT project and, if necessary, take the necessary actions for performance improvement at the stage level.

The main limitation is the size of the sample, which represents the perspectives of 30 Turkish high-level managers on KPIs in BOT projects. Besides, the selected method, namely, TOPSIS, does not provide quality measures related to the outputs; therefore, it is difficult to see the inconsistencies among the experts.

The study findings will help in devising appropriate performance evaluation practices for BOT projects to overcome the shortfalls of the existing practices and systems proposed in the literature and help in achieving the superior performance while developing infrastructure through the BOT route.

This paper proposes a process-based approach for measuring the performance of a BOT project considering eight different stages. It fills a research gap in the public–private partnership literature by focusing on stages rather than phases. The results can be used by practitioners to establish stage-level performance management systems for BOT projects.

The purpose of this paper is to develop a new conceptual life cycle performance measurement system (PMS) based on stage level key performance indicators (KPIs) to measure the performance of build–operate–transfer (BOT) projects.

This study uses a literature review to reveal the deficiencies of existing PMSs for public–private partnership (PPP) projects. Based on these deficiencies, four recommendations were proposed for developing a PMS. The validation of these recommendations was performed via focus group discussion sessions conducted with 12 experts. Then, a conceptual framework was developed based on the validated recommendations and the additional recommendations emerged during focus group discussions. Finally, the recommendations proposed by the focus group were tested by a questionnaire survey, the findings of the Friedman test and descriptive analysis validated these recommendations.

Findings of the focus group discussion, Friedman test and descriptive analysis indicated that the PMS should have four crucial features to develop an efficient, effective and comprehensible PMS for the BOT project. Firstly, non-financial and financial KPIs should be integrated. Secondly, the PMS should be developed as a process-based system with stage level KPIs. The performance of the BOT projects should be monitored and reviewed continuously, however the most important KPIs should be used for continuous performance measurement to increase the applicability of the system and allocate the resources more efficiently.

This survey was conducted on experts who have experience with BOT projects located in Turkey, therefore, judgments of experts might be affected by external factors specific to Turkey such as geopolitical situations, investment environment. However, due to the nature of BOT projects, the experience of experts can also be utilized at the international level.

This is the first time a PMS has been developed to measure the performance of a BOT project. In addition, this system has unique features when compared with the PMS proposed in the literature. Especially, the stage level KPIs and continuous performance measurement with the most important KPIs throughout each stage has never been used. This research provides both public sector and private entities with an insight into effectively measure, control and manage their BOT infrastructure projects' performances throughout their life cycles.