Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Markov Analysis as a Tool for Developing a Model for Risk Management:A Case Study Based on Electrical Transmission Line Installation Projects


Affiliations
1 Department of Management Studies, Indian School of Mines, Dhanbad, India
     

   Subscribe/Renew Journal


The study develops a model for risk assessment by the use of Markov analysis combined with the Delphi approach for expert opinion, the paper gives a methodology under which the various risk factors are firstly collected then they are applied for Markov analysis, the Markov analysis returns the probability of occurrence of that particular risk factor, this probability is then used to calculate the Rvalue, a model is then given which is used to calculate the final impact value for each risk, which will be used in risk deciding risk mitigation plan.

Keywords

Risk Management, Markov Analysis, Electrical Transmission Line Installation Project and Risk Assessment.
User
Subscription Login to verify subscription
Notifications
Font Size

  • • Aloini, D. Dulmin, R. & Mininno, V. (2012). Risk assessment in ERP projects. Information Systems. 37, 183-199.
  • • Baccarini, D. & Archer, R. (2001). The risk ranking of projects: A methodology. International Journal of Project Management. 19, 139 -145.
  • • Barber, E. (2004). Benchmarking the management of projects: A review of current thinking. International Journal of Project Management. 22, 301- 307.
  • • Castro, Robert D. (1995). Overview of the transmission line construction process. Electric Power System Research. 35, 119-125.
  • • Chen, Z., Li, H., Ren, H., Xu, Q. & Hong, j. (2011). A total environmental risk assessment model for international hub airports. International Journal of Project Management. 29, 856-866.
  • • Dey, P. (2010). Managing project risk using combined analytical hierarchy process and risk map. Applied Soft Computing, 10, 990 – 100.
  • • Dey, P. (2001). Decision support system for risk management: a case study. Management Decision, 39 (8), 634-649.
  • • Dikmen, I., Birgonul, M.T., Anac, C., Tah, J.H.M. & Aouad, G. (2008). Learning from risks: A tool for post-project risk assessment. Automation in Construction, 18, 42–50.
  • • Erickson, J. M. & Evaristo, R. (2006). Risk Factors in Distributed Projects. Proceedings of the 39th Hawaii International Conference on System Sciences IEEE.
  • • Fan, M., Lin, N. & Sheu, C. (2007). Choosing a risk handling strategy: An analytical model. International Journal of Production Economics. 112, 700-713.
  • • Fang, C. & Marle, F. (2012). A simulation based risk network model for decision support in project risk management. Decision Support Systems. 52, 635-644.
  • • Geraldi, J. G., Turner, J. R., Maylor, H., Soderholm, A., Hobday & Brady, T. (2008). Innovation in project management: Voices of research. International Journal of Project Management. 26, 586-589.
  • • Iyer, K.C. & Sagheer, M. (2010). Hierarchical Structuring of PPP Risks Using Interpretive Structural Modeling. Journal of Construction Engineering and Management. 136, 151-159.
  • • Menches, L. C. & Hanna, A. S. (2006). Quantitative measurement of Successful Performance from the Project Manager’s Perspective. Journal of Construction Engineering and Management, 132, 1284 – 1293.
  • • Olaru, M., Sandru, M. & Pirnea, I.C. (2014). Monte Carlo method application for environmental risks impact assessment investment projects. Procedia – Social and Behavioral Sciences, 109, 940 – 943.
  • • Ping, Z. W. & Li, L. (2010). The Analysis and Estimation on Risk Factors in Engineering Project Life Cycle. 978-1-4244-5326-9/10, IEEE.
  • • Regos, G. (2012). Comparison of power plant’s risks with multi criteria decision Models. Central European Journal of Operations Research, 21(4), 845 – 865.
  • • Skulj, D. (2011). The use of Markov operators to constructing generalized probabilities. International journal of Approximate Reasoning, 52, 1392 – 1408.
  • • Soderholm, A. (2008). Project management of unexpected events. International Journal of Project Management, 26, 80-86.
  • • Sun, W. & Ma. Y. (2008). Risk Assessment in Electrical Power Network Planning Project Based on Principal Component analysis and Support vector Machine. Proceedings of 7th World Congress on Intelligent Control and Automation.
  • • Tanimoto, J. & Hagishima, A. (2005). State transition probability for the Markov Model dealing with on/off cooling schedule on dwellings. Energy and Building. 37, 181 - 187.
  • • Tavares, L. V., Ferreira, J. A. A. & Coelho, J. S. (1998). On the optimal management of project risk. European Journal of Operational Research. 107, 451-469.
  • • Thevendran, V. & Mawdesley, M. J. (2004). Perception of human risk factors in construction Projects: an exploratory study. International Journal of Project Management. 22, 131-137.
  • • Thiry, M. (2002). Combining value and project management into effective programme management model. International Journal of Project Management. 20, 221-227.
  • • Tummala, V. M. R. & Burchett, J. F. (1999). Applying a risk Management Process (RMP) to manage cost risk for a EHV Transmission line project. International Journal of Project Management. 19, 223-235.
  • • Wu, C.H., Wang, Luan & Fang, K. (2008). Investigating the Relationship between Project Risk and Project Performance. Third international Conference on Convergence and Hybrid Information Technology IEEE.
  • • Wyk, R. V., Bowen, P. & Akintoye, A. (2007). Project risk management practice: The case of a South African utility company. International Journal of Project Management. 26, 149-163.

Abstract Views: 248

PDF Views: 0




  • Markov Analysis as a Tool for Developing a Model for Risk Management:A Case Study Based on Electrical Transmission Line Installation Projects

Abstract Views: 248  |  PDF Views: 0

Authors

Shwetank Parihar
Department of Management Studies, Indian School of Mines, Dhanbad, India
Chandan Bhar
Department of Management Studies, Indian School of Mines, Dhanbad, India

Abstract


The study develops a model for risk assessment by the use of Markov analysis combined with the Delphi approach for expert opinion, the paper gives a methodology under which the various risk factors are firstly collected then they are applied for Markov analysis, the Markov analysis returns the probability of occurrence of that particular risk factor, this probability is then used to calculate the Rvalue, a model is then given which is used to calculate the final impact value for each risk, which will be used in risk deciding risk mitigation plan.

Keywords


Risk Management, Markov Analysis, Electrical Transmission Line Installation Project and Risk Assessment.

References