Influence of Risk-Transfer Modifications in FIDIC Conditions on Contractor Participation in Pakistan Public Tenders

Abstract

This study examines the association between risk-transfer modifications in FIDIC-based contract conditions and contractor participation in Pakistan's public tenders. A convergent parallel mixed-methods design was employed using 150 contractor survey responses, 180 public tender documents issued during 2023–2025, and 18 expert interviews. Tender documents were analysed by comparing Particular Conditions with relevant FIDIC 1999 General Conditions, focusing on modifications related to unforeseeable physical conditions, price escalation, third-party delays, force majeure, design errors, variations, and suspension. The findings indicate that risk-transfer modifications are prevalent, particularly for physical conditions and price escalation. Risk-transfer density was negatively associated with contractor participation (r = -0.68, p < 0.001). Regression analysis further showed a significant negative association (β = -0.52, p < 0.001), while logistic regression achieved an AUC of 0.847. The results highlight the importance of balanced contractual risk allocation for improving contractor participation and supporting more competitive public procurement in Pakistan.

REFERENCES

[1] Fédération Internationale des Ingénieurs-Conseils (FIDIC), Conditions of Contract for Construction for Building and Engineering Works Designed by the Employer, 1st ed. Geneva, Switzerland: FIDIC, 1999.

[2] Fédération Internationale des Ingénieurs-Conseils (FIDIC), FIDIC Golden Principles, 1st ed. Geneva, Switzerland: FIDIC, 2019.

[3] Fédération Internationale des Ingénieurs-Conseils (FIDIC), FIDIC Contracts 1999 Editions Guide, 1st ed. Geneva, Switzerland: FIDIC, 2000.

[4] Pakistan Engineering Council (PEC), Contract Management Under the FIDIC Red Book 1999. Islamabad, Pakistan: Pakistan Engineering Council, 2019.

[5] Pakistan Engineering Council (PEC), Standard Form of Bidding Documents for Procurement of Civil Works. Islamabad, Pakistan: Pakistan Engineering Council.

[6] Public Procurement Regulatory Authority (PPRA), Government of Pakistan, Public Procurement Rules, 2004. Islamabad, Pakistan.

[7] World Bank, Standard Bidding Documents: Procurement of Works. Washington, DC, USA: World Bank, 2002.

[8] S. C. Ward, C. B. Chapman, and B. Curtis, "On the allocation of risk in construction projects," International Journal of Project Management, vol. 9, no. 3, pp. 140–147, 1991, doi: 10.1016/0263-7863(91)90038-W.

[9] A. S. Akintoye and M. J. MacLeod, "Risk analysis and management in construction," International Journal of Project Management, vol. 15, no. 1, pp. 31–38, 1997, doi: 10.1016/S0263-7863(96)00035-X.

[10] F. Hartman and P. Snelgrove, "Risk allocation in lump-sum contracts—Concept of latent dispute," Journal of Construction Engineering and Management, vol. 122, no. 3, pp. 291–296, 1996, doi: 10.1061/(ASCE)0733-9364(1996)122:3(291).

[11] J. H. M. Tah and V. Carr, "Information modelling for a construction project risk management system," Engineering, Construction and Architectural Management, vol. 7, no. 2, pp. 107–119, 2000, doi: 10.1046/j.1365-232X.2000.00126.x.

[12] K. C. Lam, D. Wang, P. T. K. Lee, and Y. T. Tsang, "Modelling risk allocation decision in construction contracts," International Journal of Project Management, vol. 25, no. 5, pp. 485–493, 2007, doi: 10.1016/j.ijproman.2006.11.005.

[13] S. M. El-Sayegh, "Risk assessment and allocation in the UAE construction industry," International Journal of Project Management, vol. 26, no. 4, pp. 431–438, 2008, doi: 10.1016/j.ijproman.2007.07.004.

[14] G. R. Smith and C. M. Bohn, "Small to medium contractor contingency and assumption of risk," Journal of Construction Engineering and Management, vol. 125, no. 2, pp. 101–108, 1999, doi: 10.1061/(ASCE)0733-9364(1999)125:2(101).

[15] S. Zhang, S. Zhang, Y. Gao, and X. Ding, "Contractual governance: Effects of risk allocation on contractors' cooperative behavior in construction projects," Journal of Construction Engineering and Management, vol. 142, no. 6, 2016, doi: 10.1061/(ASCE)CO.1943-7862.0001111.

[16] Y. Tang, Y. Chen, Y. Hua, and Y. Fu, "Impacts of risk allocation on conflict negotiation costs in construction projects: Does managerial control matter?" International Journal of Project Management, vol. 38, no. 3, pp. 188–199, 2020, doi: 10.1016/j.ijproman.2020.03.002.

[17] Y. Q. Chen, S. J. Zhang, L. S. Liu, and J. Hu, "Risk perception and propensity in bid/no-bid decision-making of construction projects," Engineering, Construction and Architectural Management, vol. 22, no. 1, pp. 2–20, 2015, doi: 10.1108/ECAM-01-2013-0011.

[18] M. S. El-Mashaleh, "Empirical framework for making the bid/no-bid decision," Journal of Management in Engineering, vol. 29, no. 3, 2013, doi: 10.1061/(ASCE)ME.1943-5479.0000147.

[19] R. M. Choudhry and K. Iqbal, "Identification of risk management system in construction industry in Pakistan," Journal of Management in Engineering, vol. 29, no. 1, 2013, doi: 10.1061/(ASCE)ME.1943-5479.0000122.

[20] S. N. Nawaz, A. Waqar, S. A. R. Shah, M. Sajid, and M. I. Khalid, "An innovative framework for risk management in construction projects in developing countries: Evidence from Pakistan," Risks, vol. 7, no. 1, Art. no. 24, 2019, doi: 10.3390/risks7010024.

[21] W. Farid, N. I. Kureshi, S. Babar, and S. Mahmood, "Critical risk factors of construction industry of Pakistan for improving project outcome," Mehran University Research Journal of Engineering and Technology, vol. 39, no. 1, pp. 71–80, 2020, doi: 10.22581/muet1982.2001.08.

[22] A. Kamal, M. Abbas, D. Khan, and R. W. Azfar, "Risk factors influencing the building projects in Pakistan: From perspective of contractors, clients and consultants," International Journal of Construction Management, vol. 22, no. 6, pp. 1141–1157, 2022, doi: 10.1080/15623599.2019.1683693.

[23] M. O. Khan, R. Akhtar, and I. ul Haq, "Risk factors identification from contractors perspective," Pakistan Journal of Engineering and Technology, vol. 5, no. 2, pp. 221–225, 2022, doi: 10.51846/vol5iss2pp221-225.

[24] K. M. Aldossari, "Exploring bid/no-bid decision factors of construction contractors for building and infrastructure projects," Buildings, vol. 14, no. 10, Art. no. 3114, 2024.

[25] J.-B. Hillig, D. Dan-Asabe, S. Donyavi, O. Dursun, and A. Thampurattty, "FIDIC's Red Book 1999 edition: A study review," Proceedings of the Institution of Civil Engineers—Management, Procurement and Law, vol. 163, no. 3, pp. 129–133, 2010, doi: 10.1680/mpal.2010.163.3.129.

[26] A. Al Kium et al., "Health equity and digital disparities in cancer screening and cardiovascular care across socioeconomic and ethnic groups: A systematic review," Vascular and Endovascular Review, vol. 6, no. 2, pp. 35–44, 2023.

[27] M. I. K. Jabed, "Stock market price prediction using machine learning techniques," American International Journal of Sciences and Engineering Research, vol. 7, no. 1, pp. 1–6, 2024.

[28] M. I. K. Jabed, M. Imran, A. A. Khan, M. Mehedi, A. Islam, and R. Pervez, "Explainable machine learning framework for early heart disease detection using SMOTE and SHAP," Vascular and Endovascular Review, vol. 9, no. 1, pp. 316–324, 2026.

[29] M. I. K. Jabed, M. R. M. Sirazy, S. Mandal, S. A. Akter, A. Hassan, and H. Esa, "Developing AI-based financial forecasting and cybersecurity systems for the US digital economy," Frontiers in Computer Science and Artificial Intelligence, vol. 5, no. 5, pp. 30–38, 2026.

[30] M. A. Rahman, R. K. Devnath, S. B. Niloy, C. M. Mehedi, T. H. Chowdhury, and M. I. K. Jabed, "A stacking ensemble framework for predicting employee turnover: Explainable AI with SHAP," in Proc. 2025 IEEE 2nd Int. Conf. Computing, Applications and Systems (COMPAS), Oct. 2025, pp. 1–6.

[31] M. A. Rahman, M. I. K. Jabed, R. K. Devnath, C. M. Mehedi, M. Begum, and T. Mahmud, "MSRFF: An interpretable CNN-Vision Transformer framework for diabetic retinopathy detection," in Proc. 2026 2nd Int. Conf. Computational Intelligence Approaches and Applications (ICCIA), May 2026, pp. 1–7.

[32] M. M. R. Akash, "Cardiotoxicity prediction models in cancer patients using artificial intelligence and genomics," International Journal of Drug Delivery Technology, vol. 16, pp. 60–73.

[33] M. I. K. Jabed, M. Imran, C. A. Gomes, P. S. Ponduru, S. Mandal, and S. Hassan, "Deep learning and explainable AI framework for predicting lung cancer severity," Journal of Computer Science and Technology Studies, vol. 7, no. 12, pp. 573–598, 2025.

[34] M. I. K. Jabed, M. Imran, C. A. Gomes, and P. S. Ponduru, "Machine learning-based prediction of poor self-rated health among U.S. adults using behavioral and socioeconomic factors," World Journal of Advanced Research and Reviews, vol. 27, no. 1, pp. 2817–2829, 2025, doi: 10.30574/wjarr.2025.27.1.2649.

[35] M. I. K. Jabed, M. A. Manzoor, F. M. Tofa, and M. H. Khan, "Interpretable ensemble learning approach for breast cancer diagnosis using SHAP-based explainable AI," Journal of Computer Science and Technology Studies, vol. 8, no. 8, pp. 244–255, 2026.

[36] M. I. K. Jabed, M. P. Ahmed, F. M. Tofa, M. F. Islam, C. A. Gomes, and R. M. Sirazy, "Federated intrusion detection for Internet of Medical Things networks: Differential privacy, non-IID robustness, and cross-device generalization," Journal of Computer Science and Technology Studies, vol. 8, no. 8, pp. 303–315, 2026.

[37] P. S. Ponduru, "Road accident prediction using LSTM-GRU neural networks," Ph.D. dissertation, California State University, Northridge, 2023.

[38] P. S. Ponduru, P. P. V. Nandanavanam, and S. K. K. Ponduru, "Ecological proportionality in generative AI: The ethics of marginal capability and environmental sufficiency," 2026.

[39] P. S. Ponduru, "Decision intelligence for AI and emerging technologies: The AEGIS-DM framework for trustworthy, cost-aware, and low-latency decision making," 2024.

[40] P. S. Ponduru, P. P. V. Nandanavanam, and S. K. K. Ponduru, "SAFE-HealCloud: Safety-aware, agentic self-healing for cloud infrastructure," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 12, no. 4, pp. 163–188, 2026.

[41] M. Akram, W. Khan, M. D. Rasheed, M. Imran, M. W. Iqbal, A. Delshadi, and M. Sultana, "Cybersecurity risk assessment model for Internet of Medical Things (IoMT) devices in healthcare systems," Spectrum of Engineering Sciences, vol. 4, no. 3, pp. 312–326, 2026.

[42] M. D. Rasheed, M. Akram, M. Imran, R. H. Ahmed, and A. Rauf, "Towards human-centric smart manufacturing: A digital twin enabled affective ergonomic framework for adaptive human robot collaboration," International Journal of Advances in Signal and Image Sciences, pp. 1544–1555, 2025.

[43] M. D. Rasheed, W. Khan, M. Imran, N. Ahmad, Y. Khan, M. Akram, and M. Sultana, "Leveraging artificial intelligence for advance data networking and cybersecurity," Spectrum of Engineering Sciences, vol. 4, no. 3, pp. 286–298, 2026.

[44] M. R. Hasan, M. A. Rahman, C. A. H. Gomes, F. N. Nitu, C. A. Gomes, M. R. Islam, and R. E. R. Shawon, "Building robust AI and machine learning models for supplier risk management: A data-driven strategy for enhancing supply chain resilience in the USA," Advances in Consumer Research, vol. 2, no. 4, pp. 1152–1171, 2025.

[45] N. M. Ali, M. E. Ahmed, M. F. Islam, C. A. Gomes, and M. S. Islam, "Toward a circular US economy: Green and artificial intelligence innovation, renewable energy, and domestic material consumption," Energy Sources, Part B: Economics, Planning, and Policy, vol. 21, no. 1, Art. no. 2685043, 2026.

[46] M. S. S. Shovon, C. A. Gomes, S. A. Reza, P. K. Bhowmik, C. A. H. Gomes, T. Jakir, and M. S. Hasan, "Forecasting renewable energy trends in the USA: An AI-driven analysis of electricity production by source," Journal of Ecohumanism, vol. 4, no. 3, pp. 322–345, 2025.

[47] M. F. Islam, M. E. Ahmed, N. M. Ali, C. A. Gomes, and M. Faisal-E-Alam, "US Path to Industry 4.0: Reassessing Supply Chain Digitalization and AI for Industrial Sustainability," Sustainable Development, 2026.