A Conceptual-Delphi Framework for Identifying and Prioritising Complexity-Generating Factors in Civil Projects Based on the Intrinsic Characteristics of Complex Systems and Aligned with the PMBOK 7 Performance Domains

Sajjadi, Ali; Jani, Rasoul; Fard Moradinia, Sina; Ghorbani, Mohammadali; Salami, Ebrahim

doi:10.22034/ijumes.2026.2105062.1402

A Conceptual-Delphi Framework for Identifying and Prioritising Complexity-Generating Factors in Civil Projects Based on the Intrinsic Characteristics of Complex Systems and Aligned with the PMBOK 7 Performance Domains

Document Type : Case Study

Authors

Ali Sajjadi ¹

Rasoul Jani ¹

Sina Fard Moradinia ¹

Mohammadali Ghorbani ²

Ebrahim Salami ³

¹ Department of Civil Engineering, Ta.C., Islamic Azad University, Tabriz, Iran

² Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.

³ Department of Civil Engineering, Payame Noor University٫ Tehran, Iran.

10.22034/ijumes.2026.2105062.1402

Abstract

Delphi studies are widely used to identify the factors that generate complexity in civil projects; however, the extent to which the participating experts share a clear understanding of the concept of complexity and of the characteristics of complex systems is rarely reported. Building on the intrinsic characteristics of complex systems, this study introduces a “Conceptual Delphi” procedure applied before the Delphi rounds begin to create cognitive alignment among experts and thereby improve the validity and generalisability of the results. Twenty intrinsic characteristics of complex systems were extracted from sixteen complexity-science sources and presented to the experts in a structured form. A three-round Delphi panel was then conducted; the factors were organised within the eight performance domains of the PMBOK 7 standard, and consensus was evaluated using the median, inter-quartile ranges and agreement rate, complemented by Kendall’s coefficient of concordance and the Wilcoxon signed-rank test. The preliminary list comprised 160 factors in the first round and was reduced to 55 factors in the second and third rounds. From the second to the third round, 17 of the 55 factors reached consensus, and only the “Development Approach and Life Cycle” performance domain achieved statistically significant. While the experts affirmed the importance of all factors, these results were used to derive a quantitative framework for prioritising project-complexity management. The resulting quantitative, PMBOK-7-aligned framework gives project managers a defensible basis for prioritising and managing the drivers of complexity in civil projects, particularly in unstable economic and administrative environments such as Iran.

Graphical Abstract

A Conceptual-Delphi Framework for Identifying and Prioritising Complexity-Generating Factors in Civil Projects Based on the Intrinsic Characteristics of Complex Systems and Aligned with the PMBOK 7 Performance Domains

Highlights

· A “Conceptual Delphi” procedure is introduced: before the Delphi rounds, experts are briefed on the intrinsic characteristics of complex systems to create shared conceptual understanding and improve validity.

· Twenty complex-system characteristics (from sixteen sources) and the eight PMBOK 7 performance domains together structure the identification of complexity-generating factors in civil projects.

· A three-round panel (19/16/14 experts) reduced an initial 160 factors to 55; between rounds two and three, 15 of the 55 factors (27%) reached consensus (median ≥ 4, IQR ≤ 1, agreement ≥ 75%).

· Only the “Development Approach and Life Cycle” domain reached statistically significant agreement (Kendall’s W = 0.37, p < 0.01), and the Wilcoxon test confirmed stable ratings between the final rounds.

· The framework yields a stable, standard-aligned and prioritised list of complexity drivers that supports complexity management and project success, especially in unstable environments such as Iranian construction.

Keywords

Complex systems

Conceptual Delphi

Complexity factors

PMBOK 7

project complexity

· Antoniadis, D. N., Edum-Fotwe, F. T., & Thorpe, A. (2011). Socio-organo complexity and project performance. International Journal of Project Management, 29(7), 808–816. https://doi.org/10.1016/j.ijproman.2011.02.006

· Azmat, Z., & Siddiqui, D. A. (2023). Analyzing project complexity, its dimensions and their impact on project success. Systems, 11(8), 417. https://doi.org/10.3390/systems11080417

· Baccarini, D. (1996). The concept of project complexity: A review. International Journal of Project Management, 14(4), 201–204. https://doi.org/10.1016/0263-7863(95)00093-3

· Bakhshi, J., Ireland, V., & Gorod, A. (2016). Clarifying the project complexity construct: Past, present and future. International Journal of Project Management, 34(7), 1199–1213. https://doi.org/10.1016/j.ijproman.2016.06.002

· Bjorvatn, T., & Wald, A. (2018). Project complexity and team-level absorptive capacity as drivers of project management performance. International Journal of Project Management, 36(6), 876–888. https://doi.org/10.1016/j.ijproman.2018.05.003

· Bosch-Rekveldt, M., Jongkind, Y., Mooi, H., Bakker, H., & Verbraeck, A. (2011). Grasping project complexity in large engineering projects: The TOE (Technical, Organizational and Environmental) framework. International Journal of Project Management, 29(6), 728–739. https://doi.org/10.1016/j.ijproman.2010.07.008

· Boulton, J. G., Allen, P. M., & Bowman, C. (2015). Embracing complexity: Strategic perspectives for an age of turbulence. Oxford University Press.

· Carvalho, M. M., Patah, L. A., & Bido, D. de S. (2015). Project management and its effects on project success: Cross-country and cross-industry comparisons. International Journal of Project Management, 33(7), 1509–1522. https://doi.org/10.1016/j.ijproman.2015.04.004

· Chu, D., Strand, R., & Fjelland, R. (2003). Theories of complexity: Common denominators of complex systems. Complexity, 8(3), 19–30. https://doi.org/10.1002/cplx.10059

· Cicmil, S., Cooke-Davies, T., Crawford, L., & Richardson, K. (2009). Exploring the complexity of projects: Implications of complexity theory for project management practice. Project Management Institute.

· Diamond, I. R., Grant, R. C., Feldman, B. M., Pencharz, P. B., Ling, S. C., Moore, A. M., & Wales, P. W. (2014). Defining consensus: A systematic review recommends methodologic criteria for reporting of Delphi studies. Journal of Clinical Epidemiology, 67(4), 401–409. https://doi.org/10.1016/j.jclinepi.2013.12.002

· Estrada, E. (2024). What is a complex system, after all? Foundations of Science, 29(4), 1143–1170. https://doi.org/10.1007/s10699-023-09917-w

· Floricel, S., Michela, J. L., & Piperca, S. (2016). Complexity, uncertainty-reduction strategies, and project performance. International Journal of Project Management, 34(7), 1360–1383. https://doi.org/10.1016/j.ijproman.2015.11.007

· Ghaleb, H., Alhajlah, H. H., Bin Abdullah, A. A., Kassem, M. A., & Al-Sharafi, M. A. (2022). A scientometric analysis and systematic literature review for construction project complexity. Buildings, 12(4), 482. https://doi.org/10.3390/buildings12040482

· Hallowell, M. R., & Gambatese, J. A. (2010). Qualitative research: Application of the Delphi method to CEM research. Journal of Construction Engineering and Management, 136(1), 99–107. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000137

· Jaber, H., Marle, F., Vidal, L.-A., Sarigol, I., & Didiez, L. (2021). A framework to evaluate project complexity using the fuzzy TOPSIS method. Sustainability, 13(6), 3020. https://doi.org/10.3390/su13063020

· Lafhaj, Z., Rebai, S., AlBalkhy, W., Hamdi, O., & Mossman, A. (2024). Complexity in construction projects: A literature review. Buildings, 14(3), 680. https://doi.org/10.3390/buildings14030680

· Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3(1), 33–67. https://doi.org/10.1007/s13194-012-0056-8

· Lu, Y., Luo, L., Wang, H., Le, Y., & Shi, Q. (2015). Measurement model of project complexity for large-scale projects from task and organization perspective. International Journal of Project Management, 33(3), 610–622. https://doi.org/10.1016/j.ijproman.2014.12.005

· Luo, L., He, Q., Xie, J., Yang, D., & Wu, G. (2017). Investigating the relationship between project complexity and success in complex construction projects. Journal of Management in Engineering, 33(2), 04016036. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000471

· Ma, L., & Fu, H. (2020). Exploring the influence of project complexity on the mega construction project success: A qualitative comparative analysis (QCA) method. Engineering, Construction and Architectural Management, 27(9), 2429–2449. https://doi.org/10.1108/ECAM-12-2019-0679

· Marle, F., & Vidal, L.-A. (2016). Managing complex, high-risk projects: A guide to basic and advanced project management. Springer. https://doi.org/10.1007/978-1-4471-6787-7

· Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.

· Nguyen, A. T., Nguyen, L. D., Le-Hoai, L., & Dang, C. N. (2015). Quantifying the complexity of transportation projects using the fuzzy analytic hierarchy process. International Journal of Project Management, 33(6), 1364–1376. https://doi.org/10.1016/j.ijproman.2015.02.007

· Nikolić, M., & Čerić, A. (2022). Classification of key elements of construction project complexity from the contractor perspective. Buildings, 12(5), 616. https://doi.org/10.3390/buildings12050616

· Project Management Institute. (2021). The standard for project management and a guide to the project management body of knowledge (PMBOK guide) (7th ed.). PMI.

· San Cristóbal, J. R., Carral, L., Diaz, E., Fraguela, J. A., & Iglesias, G. (2018). Complexity and project management: A general overview. Complexity, 2018, 4891286. https://doi.org/10.1155/2018/4891286

· Schmidt, R. C. (1997). Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences, 28(3), 763–774. https://doi.org/10.1111/j.1540-5915.1997.tb01330.x

· Sourani, A., & Sohail, M. (2015). The Delphi method: Review and use in construction management research. International Journal of Construction Education and Research, 11(1), 54–76. https://doi.org/10.1080/15578771.2014.917132

· Tatikonda, M. V., & Rosenthal, S. R. (2000). Technology novelty, project complexity, and product development project execution success. IEEE Transactions on Engineering Management, 47(1), 74–87. https://doi.org/10.1109/17.820727

· Vidal, L.-A., Marle, F., & Bocquet, J.-C. (2011a). Measuring project complexity using the analytic hierarchy process. International Journal of Project Management, 29(6), 718–727. https://doi.org/10.1016/j.ijproman.2010.07.005

· Vidal, L.-A., Marle, F., & Bocquet, J.-C. (2011b). Using a Delphi process and the analytic hierarchy process (AHP) to evaluate the complexity of projects. Expert Systems with Applications, 38(5), 5388–5405. https://doi.org/10.1016/j.eswa.2010.10.016

· Vidal, L.-A., Marle, F., & Bocquet, J.-C. (2013). Building up a project complexity framework using an international Delphi study. International Journal of Technology Management, 62(2/3/4), 251–283. https://doi.org/10.1504/IJTM.2013.055170

· von der Gracht, H. A. (2012). Consensus measurement in Delphi studies: Review and implications for future quality assurance. Technological Forecasting and Social Change, 79(8), 1525–1536. https://doi.org/10.1016/j.techfore.2012.04.013

· Williams, T. M. (1999). The need for new paradigms for complex projects. International Journal of Project Management, 17(5), 269–273. https://doi.org/10.1016/S0263-7863(98)00047-7

· Xia, W., & Lee, G. (2005). Complexity of information systems development projects: Conceptualization and measurement development. Journal of Management Information Systems, 22(1), 45–83.