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Performance Prediction of Construction Projects Based on the Causes of Claims: A System Dynamics Approach

Author

Listed:
  • Ramin Ansari

    (Department of Civil Engineering, Imam Khomeini International University, Qazvin 3414896818, Iran)

  • Mohammad Khalilzadeh

    (CENTRUM Católica Graduate Business School, Pontificia Universidad Católica del Perú, Lima 15023, Peru)

  • Roohollah Taherkhani

    (Department of Civil Engineering, Imam Khomeini International University, Qazvin 3414896818, Iran)

  • Jurgita Antucheviciene

    (Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania)

  • Darius Migilinskas

    (Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania)

  • Shohreh Moradi

    (Department of Civil Engineering, Imam Khomeini International University, Qazvin 3414896818, Iran)

Abstract

Conflict in human relations is unavoidable; therefore, it can occur in construction projects that are full of many human relationships. These conflicts can lead to claims if interlocutors do not agree. The main result of the claims is the delay and overrun of costs in construction projects. Additionally, poor management of claims affects the success of construction projects and their budget and schedule. Moreover, controlling claims ensures the successful completion of construction projects and minimizes delays and disputes. This study sought to improve the project performance by ranking the causes of claims and examining their impacts on Key Performance Indicators (KPI) using the combined AHP-TOPSIS (Analytic Hierarchy Process-Technique for Order of Preference by Similarity to Ideal Solution) method. Given that construction projects are constantly evolving and becoming more complex and have many linear and nonlinear relationships and structures, these projects can be considered as a kind of system dynamics. The system dynamics have been used for nearly four decades to analyze and improve the performance of construction projects. This study attempted to provide a model with a system dynamics approach to predict the performance of construction projects based on the reasons for the claim. In this model, the most important performance indicators, interactions between them, and the relationship of these indicators with the reasons for claiming were simulated. The results showed that delays are the most important reasons for making claims, and they have a great impact on the KPIs such as scheduling, sustainability, customer satisfaction, quality, and team satisfaction, respectively. In the modeling and simulation discussion in this study, the proposed model simulated the dependencies between the KPIs of construction projects and their changes over time and provides a better understanding of how performance indicators interact with each other. Additionally, it can be used as a basis for simulating different management policies to find the best solution to prevent and correct the negative effects of poor performance.

Suggested Citation

  • Ramin Ansari & Mohammad Khalilzadeh & Roohollah Taherkhani & Jurgita Antucheviciene & Darius Migilinskas & Shohreh Moradi, 2022. "Performance Prediction of Construction Projects Based on the Causes of Claims: A System Dynamics Approach," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4138-:d:783801
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    References listed on IDEAS

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    1. Sayyid Ali Banihashemi & Mohammad Khalilzadeh & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2021. "Investigating the Environmental Impacts of Construction Projects in Time-Cost Trade-Off Project Scheduling Problems with CoCoSo Multi-Criteria Decision-Making Method," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    2. C Eden & T Williams & F Ackermann & S Howick, 2000. "The role of feedback dynamics in disruption and delay on the nature of disruption and delay (D&D) in major projects," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(3), pages 291-300, March.
    3. P. E. D. Love & P. Mandal & H. Li, 1999. "Determining the causal structure of rework influences in construction," Construction Management and Economics, Taylor & Francis Journals, vol. 17(4), pages 505-517.
    4. Aziz Naghizadeh Vardin & Ramin Ansari & Mohammad Khalilzadeh & Jurgita Antucheviciene & Romualdas Bausys, 2021. "An Integrated Decision Support Model Based on BWM and Fuzzy-VIKOR Techniques for Contractor Selection in Construction Projects," Sustainability, MDPI, vol. 13(12), pages 1-28, June.
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    Cited by:

    1. Peipei Wang & Yunhan Huang & Jianguo Zhu & Ming Shan, 2022. "Construction Dispute Potentials: Mechanism versus Empiricism in Artificial Neural Networks," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    2. Noori Adel, 2023. "Assessment of interorganisational conflict in building refurbishment projects using EFA and PLS-SEM," Organization, Technology and Management in Construction, Sciendo, vol. 15(1), pages 178-191, January.

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