Introducing an Applicable Technique for Ranking and Selecting Project Portfolio, based on Qualitative Risk Assessment

Document Type: Research Paper

Author

Department of Energy Economics & Management, Petroleum University of Technology (PUT), Tehran, Iran.

Abstract

Projects execution is an important way to implement organizational strategies, especially in the project-based organizations. In such organizations, the decision-makers usually encounter a problem of the project portfolio selection. Of course, regarding the decision-makers’ risk attitude, they tend to direct organizational resources toward projects with low threats and high opportunities. This paper introduces a new technique for ranking projects and selecting a project portfolio, taking into account the decision-makers’ risk attitudes. In this technique, for application easiness, experts’ judgments are received as qualitative estimations. Besides, the proposed technique includes a special way to calculate the total risk level so that it avoids the computational issues of the traditional methods. At the end of this paper, an application of the proposed technique in a real case extracted from steel structure industry is analyzed.

Keywords

Main Subjects


  1. Crittenden, V. and Crittenden, W. (2008). “Building a capable organization: the eight levers of strategy implementation.” Business Horizons, Vol. 51, 301-309.
  2. Jeffrey, K.P. (2010). Project management: achieving competitive advantage, 2nd Ed., Prentice Hall, Pearson Education Inc.
  3. Cooper, D. and Chapman, C. (1987). Risk analysis for large projects - models, methods and cases, 1st Ed. Wiley, NY, USA.
  4. Ravanshadnia, M., Rajaie, H. and Abbasian H.R. (2011). “A comprehensive bid/no-bid decision making framework for construction companies.” Iranian Journal of Science and Technology, Transaction B: Engineering, Vol. 35, No. C1, 95-103.
  5. Teller, J. and Kock, A. (2013). “An empirical investigation on how portfolio risk management influences project portfolio success.” International Journal of Project Management, Vol. 31, No. 6, 817-829.
  6. Markowitz, H.M. (1952). Portfolio selection: efficient diversification of investments, 1st Ed., Yale University Press, New Haven, USA.
  7. Modarres, M. and Hassanzadeh, F. (2009). “A robust optimization approach to R&D project selection.” World Applied Science Journal, Vol. 7, No. 5, 582-592.
  8. Huang, X. (2008). “Risk curve and fuzzy portfolio selection.” Journal of Computers and Mathematics with Applications, Vol. 55, 1102-1112.
  9. Drake, A.R. and Kohlmeyer, J.M. (2010). “Risk-taking in new project selection: additive effects of bonus incentives and past performance history.” Advances in Accounting, Vol. 26, No. 2, 207-220.
  10. Golmohammadi, A. and Pajoutan, M. (2010). “Meta-heuristics for depended portfolio selection problem considering risk.” Journal of Expert Systems with Applications, Vol. 38, No. 5, 5642-5649.
  11. Ozkan, B, Wu, D., Linderoth, J.T. and Moore, J. (2010). “R&D project portfolio analysis for the semiconductor industry.” Operations Research, Vol. 58, No. 6, 1548-1563.
  12. Abbasi, M., Ashrafi, M., Kheirkhah, A., Bonyad, H. and Ghorbanzadeh Karimi, H. (2013). “R&D project selection using DEA and BSC.”Science & TechnologyPolicy, Vol. 5, No. 3, 67-84.
  13. Rashidi, A., Jazebi, F. and Brilakis, I. (2011). “Neuro-fuzzy genetic system for selection of construction project managers.” Journal of Construction Engineering and Management, Vol. 137, No. 1, 17-29.
  14. Torfi, F. and Rashidi, A. (2011). “Selection of project managers in construction firms using AHP and fuzzy TOPSIS: a case study.” Journal of Construction in Developing Countries, Vol. 16, No. 1, 69-89.
  15. Taylan, O., Bafail, A.O., Abdulaal, R.M.S. and Kabli, M.R. (2014), “Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies.” Applied Soft Computing, Vol. 17, 105-116.
  16. Padovani, M., DeCarvalho, M.M. and NamurMuscat, A.R. (2012). “Project portfolio adjustment and balance: a case study in the chemical sector.” Production, Vol. 22, No. 4, 674-694.
  17. Abbasianjahromi, H.R. and Rajaie, H. (2013). “Application of fuzzy CBR and MODM approaches in the project portfolio selection in construction companies.” Iranian Journal of Science and Technology, Vol. 37, No. C1, 143-155.
  18. Souder, W.E. and Sherman, J.D. (1994). Managing new technology development, McGraw Hill, New York, USA.
  19. Williams, T.M. (1996). “The two-dimensionality of project risk.” International Journal of Project Management, Vol. 14, No. 3, 185-186.
  20. Elmaghraby, S.E. (2005). “On the fallacy of averages in project risk management.” European Journal of Operational Research, Vol. 165, 307-313.
  21. Miler, J. (2005). A method of software project risk identification and analysis, Ph.D. Dissertation, Gdansk University of Technology, Gdansk, Polish.
  22. Project Management Institute (PMI). (2013). A Guide to the Project Management Body of Knowledge (PMBoK Guide), 5th Ed., Newtown Square, PA, USA.
  23. Arsanjani, M.A., Ershadi M., Ahmadvand A.M. and Ghazizadeh Fard S.Z. (2012). “Dynamic analysis of problems related to absence of project portfolio system in the project based organizations.” Iranian Journal of Management Science, Vol. 7, No. 27, 71-93.
  24. Kahkonen, K. and Artto, K.A. (1997). Managing risks in projects, 1st Ed., E & FN SPON, Helsinki, Finland.
  25. Flanagan, R. and Norman, G., (1993). Risk management and construction, 1st Ed., Blackwell Scientific Publications, Oxford, UK.