Identification and quantification of project complexity from perspective of primary stakeholders in US construction projects
Abstract
Construction experts believe that complexity could adversely affect construction projects’ performance. Several studies have been focused on identifying leading complexity indicators; however, the complexity indicators from the perspective of primary stakeholders (owners, contractors, and consultants) have been rarely studied. Therefore, the aim of this study is to utilize the systematic Delphi method to identify, rank and weight the complexity indicators based on the primary stakeholders’ perspectives associated with US construction projects. Additionally, the shared entity-based complexity indicators (ECIs), as well as the weighting of entity-based complexity categories were determined and analyzed. Therefore, 101 potential ECIs were identified through a comprehensive literature review. Then, thirteen senior subject matter experts (SMEs), and three academic advisors were selected and invited to participate in a workshop to determine significant ECIs and then rank and weight them. The results reveal that the ECIs associated with complexity categories “scope definition” and “project resources” received the highest aggregated complexity weights in the aspect of the primary stakeholders. Although this study has been conducted based on US construction projects, the results would provide helpful guidance for international construction projects. Moreover, this study would assist the primary stakeholders in allocating resources properly in order to manage project complexity worldwide.
Keyword : construction project, project complexity, primary stakeholders, complexity indicators, indicator weighting, indicator ranking
How to Cite
Kermanshachi, S., & Safapour, E. (2019). Identification and quantification of project complexity from perspective of primary stakeholders in US construction projects. Journal of Civil Engineering and Management, 25(4), 380-398. https://doi.org/10.3846/jcem.2019.8633
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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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
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Hasson, F., Keeney, S., & McKenna, H. (2000). Research guidelines for the Delphi survey technique. Journal of Advanced Nursing, 32, 1008-1015. https://doi.org/10.1046/j.1365-2648.2000.t01-1-01567.x
He, Q. H., Luo, L., Hu, Y., & Chan, A. P. C. (2015). Measuring the complexity of mega construction projects in China – A fuzzy analytic network process analysis. International Journal of Project Management, 33(3), 549-563. https://doi.org/10.1016/j.ijproman.2014.07.009
He, Q. H., Luo, L., Wang, J., Li, Y. K., & Zhao, L. (2012). Using analytic network process to analyze influencing factors of project complexity. In Proceeding of International Conference on Management Science and Engineering (p. 1781). IEEE Technology Management Council, New York, USA. https://doi.org/10.1109/ICMSE.2012.6414413
Ji, W., AbouRizk, S. M., Zaiane, O. R., & Li, Y. (2018). Complexity analysis approach for prefabricated construction products using uncertain data clustering. Journal Construction in Engineering Management, 144(8), 04018063. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001520
Kauffman, S. A. (1993). The origins of order. Oxford: Oxford University Press.
Keeney, S., Hasson, F., & McKenna, H. P. (2001). A critical review of the Delphi technique as a research methodology for nursing. International Journal of Nursing Studies, 38(2), 195-200. https://doi.org/10.1016/S0020-7489(00)00044-4
Keeney, S., Hasson, F., & Mckenna, H. (2011). The Delphi technique in nursing and health research. Chichester: Wiley-Blackwell. https://doi.org/10.1002/9781444392029
Kermanshachi, S., Dao, B., Shane, J., & Anderson, S. (2016a). An empirical study into identifying project complexity management strategies. Procedia Engineering, 145, 603-610. https://doi.org/10.1016/j.proeng.2016.04.050
Kermanshachi, S., Dao, B., Shane, J., & Anderson, S. (2016b). Project complexity indicators and management strategies – A Delphi study. Procedia Engineering, 145, 587-594. https://doi.org/10.1016/j.proeng.2016.04.048
Kermanshachi, S., Dao, B., Rouhanizadeh, B., Shane, J., & Anderson, S. (2018). Development of the project complexity assessment and management framework for heavy industrial projects. International Journal of Construction Education and
Research, 29(2). https://doi.org/10.1080/15578771.2018.1499568
Kian Manesh Rad, E., Sun, M., & Bosche, F. (2017). Complexity for megaprojects in the energy sector. Journal of Management in Engineering, 33(4), 1-13. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000517
Kiridena, S., & Sense, A. (2016). Profiling project complexity: Insights from complexity science and project management literature. Project Management Journal, 47(6), 56-74. https://doi.org/10.1177/875697281604700605
Lehtiranta, L. (2011). Relational risk management in construction projects: modeling the complexity. Leadership and Management in Engineering, 11(2), 141-154. https://doi.org/10.1061/(ASCE)LM.1943-5630.0000114
Lessard, D., Sakhrani, V., & Miller, R. (2014). House of project complexity – Understanding complexity in large infrastructure projects. Engineering Project Organization Journal, 4(4), 170-192. https://doi.org/10.1080/21573727.2014.907151
Lindeman, C. (1981). Priorities within the health care system: A Delphi survey. Kansas City: American Nurses’ Association.
Liu, S. (2015). Effects of control on the performance of information systems projects: the moderating role of complexity risk. Journal of Operations Management, 36, 46-62. https://doi.org/10.1016/j.jom.2015.03.003
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 Project Management, 33, 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), 1-12. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000471
Manoliadis, O. G., Pantouvakis, J. P., & Christodoulou, S. E. (2009). Improving qualifications-based selection by use of the fuzzy Delphi method. Construction Management and Economics, 27(4), 373-384. https://doi.org/10.1080/01446190902758993
Manoliadis, O. G., Tsolas, I., & Nakou, A. (2006). Sustainable construction and drivers of change in Greece: a Delphi study. Construction Management and Economics, 24(2), 113-120. https://doi.org/10.1080/01446190500204804
Martino, J. P. (1983). Technological forecasting for decision-making. New York: Elsevier.
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