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Evaluating Cost Contingency for Construction Projects: A Fuzzy Risk Analysis Approach

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Ambient Communications and Computer Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 356))

Abstract

Controlling and managing project costs in infrastructure construction projects within budget is a matter of prime importance since these projects require a large amount of capital investment. The use of cost contingencies is found as an effective tool for reducing the cost overrun. Traditionally, the contingency is estimated using a fixed percentage of the estimated cost. Project costs’ sensitivity to risk factors impacting the cost is not considered in this method resulting in underestimated or overestimated values. Therefore, in this paper, an alternate methodology is presented for developing a risk-induced model to predict the cost contingency after identifying and quantifying the risks involved in the projects. To develop the model, a rule-based fuzzy inference system has been used. The fuzzy theory can deal with incomplete, imprecise and uncertain data intrinsic to complex construction projects. This methodology provides a practical approach for estimating cost contingency by considering the frequently occurring and important risk factors impacting the cost of construction projects. Details about the development and validation of the model are presented in this research study. Project managers and decision-makers will find this model very useful for making decisions regarding various issues related to the project such as contingency estimation, bid price calculation, mark-up estimation and assessment of different projects.

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References

  1. Baccarini D (2006) The maturing concept of estimating project cost contingency—a review. In: 31st Australasian University Building Educators Association Conference (AUBEA 2006), Curtis University of Technology, Australia

    Google Scholar 

  2. Baloi D, Price ADF (2003) Modeling global risk factors affecting construction cost performance. Int J Proj Manag 21(4):261–269

    Article  Google Scholar 

  3. Barraza G, Bueno R (2007) Cost contingency management. J Constr Eng Manag 23(3):140–146

    Google Scholar 

  4. Barraza G (2011) Probabilistic estimation and allocation of project time contingency. J Constr Eng Manag 137(4):259–265

    Article  Google Scholar 

  5. Boukendour S (2005) A new approach to project cost overrun and contingency management. In: OCRI partnership conferences series process and project management, 22 March 2005, Ottawa

    Google Scholar 

  6. Chen D, Hartman FT (2000) A neural network approach to risk assessment and contingency allocation. AACE international transactions. Risk.07.01- Risk.07.06 Contingencies. J Constr Eng Manag 126(2):130–136

    Google Scholar 

  7. Diekmann JE (1983) Probabilistic estimating: mathematics and applications. J Constr Eng Manag 109(3):297–308

    Article  Google Scholar 

  8. Dikmen I, Birgonul MT, Han S (2007) Using fuzzy risk assessment to rate cost overrun risk in international construction project. Int J Project Manage 25:495–505

    Article  Google Scholar 

  9. Ahiaga-Dagbui DD, Tokede O, Smith SD, Wamuziri S (2013) A neuro-fuzzy hybrid model for predicting final cost of water infrastructure projects. In: Conference: 29th ARCOM conference at: reading, UK, September 2013. https://doi.org/10.13140/2.1.2382.6880

  10. Elizabeth S, Sujatha L (2015) Project scheduling method using triangular intuitionistic fuzzy numbers and triangular fuzzy numbers. Appl Math Sci 9(4):185–198

    Google Scholar 

  11. Esragh F, Mamdani EH (1981) A general approach to linguistic approximation, fuzzy reasoning, and its application. Academic Press, Cambridge, MA, USA

    Google Scholar 

  12. Ford DN (2002) Achieving multiple project objectives through contingency management. J Constr Eng Manage 128(1):30–39

    Article  Google Scholar 

  13. Hassanein AAB, Cherlopalle V (1999) Fuzzy sets theory and range estimating. AACE International Transactions, K4111. Hassanein, 1999.pdf, AACE Int Trans, K4 (1)

    Google Scholar 

  14. Idrus A, Nuruddin MF, Rohman MA (2011) Development of project cost contingency estimation model using risk analysis and fuzzy expert system. Expert Syst Appl 38:1501–1508

    Article  Google Scholar 

  15. Jin XH, Zhang G (2011) Modelling optimal risk allocation in PPP projects using artificial neural networks. Int J Proj Manag 29(5):591–603

    Article  Google Scholar 

  16. Kutsch E, Hall M (2010) Deliberate ignorance in project risk management. Int J Proj Manag 28(3):245–255

    Article  Google Scholar 

  17. Lorance RB, Wendling RV (2001) Basic techniques for analysing and presenting cost risk analysis. Cost Eng 43(6):25–31

    Google Scholar 

  18. Mak S, Picken D (2000) Using risk analysis to determine construction project. J Constr Eng Manag. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:2(130)

    Article  Google Scholar 

  19. Mamdani EH (1997) Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191

    Article  Google Scholar 

  20. Mamdani H, Assillian S (1975) An experimental in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7(1):1–13

    Article  Google Scholar 

  21. Marco AD, Rafele C, Thaheem MJ (2015) Dynamic management of risk contingency in complex design-build projects. J Manage Eng. ISSN 0733–9364/04015080(10)

    Google Scholar 

  22. McGrew JF, Bilotta JG (2000) The effectiveness of risk management: measuring what didn’t happen. Manag Decis 38(4):293–301

    Article  Google Scholar 

  23. Moselhi O (1997) Risk assessment and contingency estimation. AACE Int Trans 90–95

    Google Scholar 

  24. Paek J, Lee YW, Ock JH (1993) Pricing construction risk: fuzzy set application. J Constr Eng Manag 119(4):743–756

    Article  Google Scholar 

  25. Project Management Institute (2013) A guide to the project management body of knowledge (PMBOK® Guide)

    Google Scholar 

  26. Shaheen A, Robinson FA, AbouRizk SM (2007) Fuzzy numbers in cost range estimating. J Constr Eng Manag 133(4):325–334

    Article  Google Scholar 

  27. Sharma S, Goyal PK (2014) Cost overrun factors and project cost risk assessment in construction industry—a state of the art review. Int J Civil Eng 3(4):139–154

    Google Scholar 

  28. Sharma S, Goyal PK (2019) Fuzzy assessment of the risk factors causing cost overrun in construction industry. Evol Intel. https://doi.org/10.1007/s12065-019-00214-9

    Article  Google Scholar 

  29. Sonmez R, Ergin A, Birgonul MT (2007) Quantitative methodology for determination of cost contingency in international projects. J Manag Eng 23(1):35–39

    Article  Google Scholar 

  30. Thal AE, Cook JJ, White ED (2010) Estimation of cost contingency for air force construction projects. J Constr Eng Manage 136(11):1181–1188

    Article  Google Scholar 

  31. Touran A (2003) Probabilistic model for cost contingency. J Constr Eng Manag 129(3):280–284

    Article  Google Scholar 

  32. Wang WC, Bilozerov T, Dzeng RJ, Hsiao FY, Wang KC (2017) Conceptual cost estimations using neuro-fuzzy and multi-factor evaluation methods for building projects, pp 1–14. https://doi.org/10.3846/13923730.2014.948908

  33. Williams TP (2003) Predicting final cost for competitively bid construction projects using regression models. Int J Project Manage 21:593–599

    Article  Google Scholar 

  34. Yeo KT (1990) Risks, classification of estimates and contingency management. J Manag Eng 6(4):458–470

    Article  Google Scholar 

  35. Zadah LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Delhi Technological University, Delhi, 110042, India

    Pradeep K. Goyal

  2. Government Polytechnic College, Ajmer, Rajasthan, 305002, India

    Savita Sharma

Authors
  1. Pradeep K. Goyal
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  2. Savita Sharma
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Management, Providence University, Taichung, Taiwan

    Yu-Chen Hu

  2. Krishna Engineering College, Ghaziabad, India

    Shailesh Tiwari

  3. National Institute of Technology Agartala, Tripura, India

    Munesh C. Trivedi

  4. Computer Science and Engineering Department, MNNIT, Allahabad, India

    K. K. Mishra

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Goyal, P.K., Sharma, S. (2022). Evaluating Cost Contingency for Construction Projects: A Fuzzy Risk Analysis Approach. In: Hu, YC., Tiwari, S., Trivedi, M.C., Mishra, K.K. (eds) Ambient Communications and Computer Systems. Lecture Notes in Networks and Systems, vol 356. Springer, Singapore. https://doi.org/10.1007/978-981-16-7952-0_58

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  • DOI: https://doi.org/10.1007/978-981-16-7952-0_58

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7951-3

  • Online ISBN: 978-981-16-7952-0

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