Authors : Darwin L. Uy; Joeme Carl Demegillo

Volume/Issue : Volume 10 - 2025, Issue 12 - December

Google Scholar : https://tinyurl.com/5xtfptkj

Scribd : https://tinyurl.com/bdzzu4y5

DOI : https://doi.org/10.38124/ijisrt/25dec914

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Abstract : This study examines scope creep—defined as the uncontrolled expansion of project scope without corresponding adjustments to baselines—through a qualitative case analysis of the South2 Residences project in Las Piñas City, Philippines. The research aims to understand the systemic nature of scope creep and propose a mitigation framework grounded in Production and Operations Management (P/OM) principles. Data were triangulated from semi-structured interviews with project managers, planners, quantity surveyors, site engineers, and contractor representatives, complemented by document analysis (change orders, RFIs/RFAs, schedules, procurement logs) and site observations. Findings reveal that scope creep resulted from multiple interacting drivers: contractor transitions, evolving client requirements, gaps in the Terms of Reference (TOR), planning and communication weaknesses, and stakeholder misalignment. Contractor transitions were the most significant contributor, acting as capacity shocks and quality risks, and accounted for 62% of the additional project budget; client-driven changes contributed 23%, while TOR and planning gaps added 15%, with substantial indirect schedule impacts. Approval bottlenecks and procurement delays further compressed work windows, with RFIs aging beyond 30 days and procurement backlogs extending up to two months, triggering costly accelerations. Interview insights reinforced these findings, highlighting incomplete turnover documentation, scope ambiguity, and mobilization disruptions. Practitioners emphasized strict documentation, baseline and BOQ enforcement, rolling look-ahead forecasting, and selective activity crashing only after transparent time–cost trade-off analysis. From a P/OM perspective, these findings translate into a systems-based mitigation framework comprising: (1) forecasting and aggregate planning for buffer discipline; (2) capacity and learning-curve management during transitions; (3) flow control and bottleneck management of approvals and procurement; (4) quality assurance to prevent rectification- driven scope increase; (5) governance and communication systems; and (6) real-time performance dashboards integrating EVM, cycle times, and buffer consumption. While limited to a single case, this study offers practical guidance for projects facing complexity, variability, and contractor performance risks, and suggests future research on quantitative validation and digital decision-support tools for real-time forecasting and scheduling.

Keywords : Scope Creep, Systems-Based Mitigation Framework, Resource Optimization, Activity Crashing, Cost Analysis, Contractor Transitions, Aggregate Planning, Forecasting, Production and Operations Management (POM), Risk Mitigation, Change Control, Time-Cost Trade-Off Analysis, South2 Residences Case Study

References :

1. Abdelalim, A. M., Salem, M., Salem, M., Al-Adwani, M., & Tantawy, M. (2025). An analysis of factors contributing to cost overruns in the global construction industry. Buildings, 15(1), 18. https://doi.org/10.3390/buildings15010018
2. Ajmal, M. M., Khan, M., Gunasekaran, A., & Helo, P. T. (2022). Managing project scope creep in construction industry. Engineering, Construction and Architectural Management, 29(7), 2786–2809. https://doi.org/10.1108/ECAM-07-2020-0568
3. Alotibe, M. (2024). Managing scope creep in project management. Research Publish Journals. https://doi.org/10.5281/zenodo.14281964
4. Alzahrani, J. I., & Emsley, M. W. (2013). The impact of contractors’ attributes on construction project performance. International Journal of Project Management, 31(3), 313–322.
5. Ballard, G. (2000). The Last Planner System of production control. Proceedings of the 9th Annual Conference of the International Group for Lean Construction, 1–13.
6. Fleming, Q. W., & Koppelman, J. M. (2016). Earned Value Project Management (4th ed.). Newtown Square, PA: Project Management Institute.
7. Goldratt, E. M. (1990). The Goal: A Process of Ongoing Improvement (2nd ed.). Great Barrington, MA: North River Press.
8. Heizer, J., Render, B., & Munson, C. (2020). Operations Management (13th ed.). Boston, MA: Pearson.
9. Hopp, W. J., & Spearman, M. L. (2011). Factory Physics (3rd ed.). New York, NY: McGraw-Hill.
10. Johansson, P. (2024). Reinforcement learning for predictive scheduling in dynamic construction environments. Automation in Construction, 155, 104789. https://doi.org/10.1016/j.autcon.2024.104789
11. Kerzner, H. (2017). Project Management: A Systems Approach to Planning, Scheduling, nd Controlling (12th ed.). Hoboken, NJ: Wiley.
12. Love, P. E. D., Sing, C. P., Wang, X., & Irani, Z. (2016). Overruns in transportation infrastructure projects. IEEE Transactions on Engineering Management, 63(4), 316–328.
13. Lutfi, M. A., Witjaksana, B., & Purnama, J. (2025). Cost and time analysis of project acceleration using the crashing method with additional working hours and labor. Asian Journal of Social and Humanities, 3(7). https://doi.org/10.59888/ajosh.v3i7.545
14. Project Management Institute (PMI). (2021). A Guide to the Project Management Body of Knowledge (PMBOK® Guide) (7th ed.). Newtown Square, PA: PMI.
15. Raffetto, C. (2025). Construction in 2025: Key challenges & risk strategies. Construction Owners Association. https://www.constructionowners.com/news/2025-construction-emerging-challenges-risk-management
16. Womack, J. P., & Jones, D. T. (1996). Lean Thinking. New York, NY: Simon & Schuster.
17. Xegwana, M. S., Sophi, S., Gqesha, L., & Nyanga, M. (2025). Determinants of scope creep in selected construction projects in the Cape Metropolis. International Journal of Advanced Business Studies, 4(1). https://doi.org/10.59857/IGCJ5838
18. Zhou, J., & Li, Y. (2024). Line-of-balance scheduling optimization using branch-and-bound algorithms for repetitive construction projects. Journal of Construction Engineering and Management, 150(3), 04024012. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002345