Analyzing the Risks in Highway Projects Using the Markov Chain Approach

Obare DM^1, and Muraya MM¹

¹Physical Sciences Department, Chuka University, Chuka, Nairobi, Kenya

Cite this paper

Obare DM and Muraya MM. Analyzing the Risks in Highway Projects Using the Markov Chain Approach. American Journal of Applied Mathematics and Statistics. 2019; 7(2):59-64. doi: 10.12691/AJAMS-7-2-2

Abstract

The issues associated to highway projects usually affect aspects like nature of the project, cost and time. Risk events that are not usual always give rise to positive or negative feedback and normally cause variations from project designs especially inclined to risk construction projects. However, more investigations have been done on risk management associated to highway projects, there is limited literature more so to the risk of the project. These projects can be overseen under some dubious condition by applying the risk management technique. The aim of this research was to demonstrate pertinence of the Markov Chain approaches in diminishing the risks of the highway projects by utilization of data from the projects. Other Commonly utilized procedures don't investigate potential risks successfully and subsequently the utilization of Markov chains. This project has made utilization of the Markov chain procedure to evaluate the short and long-term potential risks. This research project utilized risk data acquired from experts through questionnaires. The data was then analyzed utilizing the Octave software.

Keywords

highway projects, Markov chain, risk, octave software

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Adebayo, A., (2002), “Sustainable construction in Africa, in Agenda 21 for sustainable construction in developing countries, Africa position paper, http://www.sustainablesettlement.co.za/docs/a21_adebayo.pdf>, [accessed 24/03/2010].
[2]	Molenaar, Keith Robert. Guidebook on risk analysis tools and management practices to control transportation project costs. Vol. 658. Transportation Research Board, 2010.
[3]	Guide, A. "Project Management Body of Knowledge (PMBOK® GUIDE)." Project Management Institute. 2001.
[4]	Sujiao, Zhang. "Risk analysis of construction projects based on markov chain." Proceedings of the 2009 Asia-Pacific Conference on Information Processing-Volume 01. IEEE Computer Society, 2009.
[5]	Ebrahimnejad, Sadoullah, S. Meysam Mousavi, and S. Mohammad H. Mojtahedi. "A fuzzy decision-making model for risk ranking with an application to an onshore gas refinery." International Journal of Business Continuity and Risk Management. 1.1 (2009): 38-66.
[6]	Mojtahedi, S. Mohammad H., S. Meysam Mousavi, and Ahmad Makui. "Project risk identification and assessment simultaneously using multi-attribute group decision making technique." Safety science 48.4 (2010): 499-507.
[7]	Akinci B. and Fischer M. (1998), Factors affecting contractors' risk and cost overburden, Journal of Management in Engineering, ASCE, 14(1): 67-76.
[8]	Tah, J.H.M. and Carr, V. (2000) Information modelling for a construction project risk management system, Engineering, Construction and Architectural Management and Economics, 7(2): 107-119.
[9]	Tavakkoli-Moghaddam, R., S. M. Mousavi, and H. Hashemi. "A fuzzy comprehensive approach for risk identification and prioritization simultaneously in EPC projects." Risk management in environment, production and economy. In Tech, 2011.
[10]	Mousavi, S. Meysam, et al. "Risk assessment for highway projects using jackknife technique." Expert Systems with Applications. 38.5 (2011): 5514-5524.
[11]	Hashemi, H., Mousavi, S. M., & Mojtahedi, S. M. H. (2011). Bootstrap technique for risk analysis with interval numbers in bridge construction projects. Journal of Construction Engineering and Management, 137(8), 600-608.
[12]	Makui, A., Mojtahedi, S. M., & Mousavi, S. M. (2010). Project risk identification and analysis based on group decision making methodology in a fuzzy environment. International Journal of Management Science and Engineering Management, 5(2), 108-118.
[13]	Zaghoul and Hertman (2003). "Risk analysis and management" International Journal of Highway Construction, 18 (2), 80-88.
[14]	Molenaar, K. (2005). "Programmatic cost risk analysis for highway megaprojects". Journal of Construction Engineering and Management 131(3), 343-353.
[15]	Hashim, A. and Ku Hamid, K.H. (2007). Pollutant removal system on Senai-Desaru Expressway, 9th Joint Technical Conference (JTC) 2007 Penang, Malaysia.
[16]	Akintoye, A. and MacLeod, M. (1997). "Risk analysis and management in construction." International Journal of Project Management, 15 (1), 31-38.
[17]	Ashley, D., Diekmann, J., and Molenaar, K. (2006). "Guide to risk assessment and allocation for highway construction management." FHA, International Technology Scanning Program. Office of international program, FHA, Washington, DC, 4-17.
[18]	PMI. (2004). "A Guide to the project management body of knowledge." Project Management Institute, Newtown Square, PA, 237-268.
[19]	Asbridge, M., Hayden, J. A., & Cartwright, J. L. (2012). Acute cannabis consumption and motor vehicle collision risk: systematic review of observational studies and meta-analysis. Bmj, 344, e536.
[20]	Brooks, S., Gelman, A., Jones, G., & Meng, X. L. (Eds.). (2011). Handbook of Markov chain Monte Carlo. CRC press.
[21]	Truhlar, D. G., Garrett, B. C., & Klippenstein, S. J. (1996). Current status of transition-state theory. The Journal of physical chemistry, 100(31), 12771-12800.
[22]	Gardiner, C. (2009). Stochastic methods (Vol. 4). Berlin: springer.
[23]	Mane, S., & Pimplikar, D. S. (2013). Risk Assessment of BOT projects. International Journal of Computational Engineering Research, 3(8).
[24]	Sato, Y., Kitazume, K., & Miyamoto, K. (2005). Quantitative risk analysis of road projects based on empirical data in Japan. Journal of the Eastern Asia Society for Transportation Studies, 6, 3971-3984.