Measuring the Construction Risk Insurability through Fuzzy Inference System
DOI:
https://doi.org/10.9744/ced.26.2.120-129Keywords:
Construction risks, fuzzy inference system, insurabilityAbstract
Contractors face most of the construction risks among stakeholders, and insurance is a common method to mitigate these risks. However, not all risks are insurable. While prior studies have typically assessed risk insurability through a binary approach (insurable versus non-insurable) and lacked clear criteria, this study offers a novel perspective by evaluating the insurability of construction risks based on four criteria: ‘accidental events,’ ‘quantifiable,’ ‘numerous and homogenous,’ and ‘evaluable.’ This study develops a fuzzy-based model to assess the degree of the construction risk insurability, accounting for the uncertainty, imprecision, and vagueness inherent in evaluating insurability against a specific criterion and criteria combinations. The model is applied to assess the insurability of several construction risks, illustrating its practical application. This paper concludes by discussing the model’s limitations and suggesting directions for future research.
References
Labombang, M., Manajemen Risiko dalam Proyek Konstruksi, Jurnal SMARTek, 9, 2011, pp. 39–46.
Monzer, N., Fayek, A.R., Lourenzutti, R., and Siraj, N.N., Aggregation-based Framework for Construction Risk Assessment with Heterogeneous Groups of Experts, Journal of Construction Engineering and Management, 145(3), 2019, pp. 1–10, doi: 10.1061/(asce)co.1943-7862.0001614.
Szymański, P., Risk Management in Construction Projects, Procedia Engineering, 208, 2017, pp. 174–182, doi: 10.1016/j.proeng.2017.11.036.
Kangari, R., Risk Management Perceptions and Trends of U.S. Construction, Journal of Construction Engineering and Management, 121(4), 1995, pp. 422–429, doi: 10.1061/(asce)0733-9364(1995)121:4(422).
Project Management Institute, A Guide to the Project Management Body of Knowledge (PMBOK guide), 7th ed. Newton Square, Pennsylvania: Project Management Institute, 2021.
Lahdenperä, P., Making Sense of the Multi-party Contractual Arrangements of Project Partnering, Project Alliancing and Integrated Project Delivery, Construction Management and Economics, 30(1), 2012, pp. 57–79, doi: 10.1080/01446193.2011.648947.
Ward, S.C. and Chapman, C.B., Risk-management Perspective on the Project Lifecycle, International Journal of Project Management, 13(3), 1995, pp. 145–149, doi: 10.1016/0263-7863(95)00008-E.
Bunni, N.G., Risk and Insurance in Construction, 2nd ed. London: Spon Press, 2003. doi: 10.1080/01446193.2013.783703.
Owusu-Manu, D.G., Ghansah, F.A., Darko, A., Asiedu, R.O., and Edwards, D.J., Insurable and Non-insurable Risks in Complex Project Deals: Case of the Ghanaian Construction Industry, Journal of Engineering, Design and Technology, 18(6), 2020, pp. 1971–1995, doi: 10.1108/JEDT-10-2019-0265.
Pramudya, A.A., Model Penilaian Kuantitatif Risiko yang Dapat Diasuransikan pada Proyek Konstruksi di Indonesia, Universitas Katolik Parahyangan, Bandung, 2023.
Battrick, P. and Duggan, P., The Rainbow Suite: The 1999 FIDIC Suite, CES, 2011, pp. 1–7..
Cheung, S.O. and Pang, K.H.Y., Anatomy of Construction Disputes, Journal of Construction Engineering and Management, 139(1), 2013, pp. 15–23, doi: 10.1061/(asce)co.1943-7862.0000532.
Perera, B.A.K.S., Rathnayake, R.M.C.K., and Rameezdeen, R., Use of Insurance in Managing Construction Risks - Evaluation of Contractors’ All Risks (CAR) Insurance Policy, 08(02), 2008, pp. 24–31.
Halwatura, R.U., Effectiveness of Contractors All Risk (Car) Insurance Policies in Road Construction Projects, Original Research Article Journal of Basic and Applied Research International, 9(1), 2015, pp. 56–67, [Online]. Available: https://www.researchgate.net/publication/278036793
Hatmoko, J.U.D., Astuti, P.K., and Farania, S.N., Insuring Project Risks: Contractor Expectations versus Insurance Company Policies, International Journal of Technology, 12(1), 2021, pp. 90–100, doi: 10.14716/ijtech.v12i1.4156.
Berliner, B., Large Risks and Limits of Insurability, The Geneva Papers on Risk and Insurance, 10(37), 1985, pp. 313–329.
Atlam, H.F., Walters, R.J., Wills, G.B., and Daniel, J., Fuzzy Logic with Expert Judgment to Implement an Adaptive Risk-Based Access Control Model for IoT, Mobile Networks Applications, 26, 2021, pp. 2545–2557.
Mendel, J.M., Murphy, S., Miller, L.C., Martin, M., and Karnik, N., The Fuzzy Logic Advisor for Social Judgments : A First Attempt, in Computing with Words in Information/Intelligent Systems 2. Studies in Fuzziness and Soft Computing, Zadeh, L.A. and Kacprzyk, J., Eds., Heidelberg: Physica, 1999.
Ndekugri, I., Daeche, H., and Zhou, D., The Project Insurance Option in Infrastructure Procurement, Engineering, Construction and Architectural Management, 20(3), 2013, pp. 267–289, doi: 10.1108/09699981311324005.
Putri, T.A.E. and Yuwono, B.E., Pengaruh Penggunaan Asuransi Contractor All Risk terhadap Pengalihan Potensi Risiko pada Proyek Konstruksi, Seminar Nasional Cendekiawan ke 3 Tahun 2017, 2017, pp. 251–255.
Hatmoko, J.U.D, Putri, D.M., and Ferry, H., Analisis Power-Interest Stakeholder terhadap Asuransi Bencana Infrastruktur Publik di Kota Semarang, Media Komunikasi Teknik Sipil, 26(2), 2020, pp. 220–228.
Desai, A. and Kashiyani, B., Role of Insurance as a Risk Management Tool in Construction Projects, International Journal of Advanced Research in Engineering, Science & Management, 2021.
Irawan, D. and Riman, Apresiasi Kontraktor dalam Penggunaan Asuransi pada Pembangunan Konstruksi di Malang, Widya Teknika, 20(1), 2012, pp. 31–38.
Musundire, S. and Aigbavboa, C., Management of Construction Risk through Contractor’s All Risk Insurance Policy: a South Africa Case Study, 5th International/11th Construction Specialty Conference, 2015, pp. 1–8.
Debela, G.Y., Construction Risk Management through Insurance in the Ethiopian Federal Road Projects, Civil and Environmental Research, 10(1), 2018, pp. 25–34, [Online]. Available: www.iiste.org
Kuo, Y.C. and Lu, S.T., Using Fuzzy Multiple Criteria Decision Making Approach to Enhance Risk Assessment for Metropolitan Construction Projects, International Journal of Project Management, 31(4), 2013, pp. 602–614, doi: 10.1016/j.ijproman.2012.10.003.
Lupyan, G., How Reliable is Perception?, Epistemology and Cognition, 45(1), 2017, pp. 81–106, doi: 10.5840/philtopics20174515.
Pedrycz, W., Why Triangular Membership Functions?, Fuzzy Sets and Systems, 64(1), 1994, pp. 21–30, doi: 10.1016/0165-0114(94)90003-5.
Bede, B., Mathematics of Fuzzy Sets and Fuzzy Logic, Heidelberg: Springer Berlin, 2013, doi: 10.1007/978-3-42-35221-8.
Van Leekwijck, W. and Kerre, E.E., Defuzzification: Criteria and Classification, Fuzzy Sets and Systems, 108(2), 1999, pp. 159–178, doi: https://doi.org/10.1016/S0165-0114(97)00337-0.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Leonardo Yonatan Tan, Andreas Wibowo, Andreas Pramudya
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain the copyright and publishing right, and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) followingthe publication of the article, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
