PREQUALIFICATION OF CONTRACTOR IN THE CONSTRUCTION INDUSTRY USING MULTI-ATTRIBUTE UTILITY THEORY: A MULTIPLICATIVE APPROACH

Authors

  • M.V. Krishna Rao Department of Civil Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad, India
  • V.S.S. Kuma V.S.S. Kuma Department of Civil Engineering, University College of Engineering (A), Osmania University, Hyderabad, India
  • P. Rathish Kumar Department of Civil Engineering, National Institute of Technology, Warangal, India.

DOI:

https://doi.org/10.11113/mjce.v28.15987

Keywords:

KeywordsMulti Attribute Utility Theory (MAUT), construction industry, criteria, prequalification, contractor.

Abstract

The construction industry is commented for its ineffectiveness in delivering outcomes such as time and cost overruns, low quality and productivity, and subsequent poor customer satisfaction. To improve the probability of success in construction projects, choosing a suitable contractor is one of the major decisions to be taken by the clients. The choice of a suitable contractor is a multi-criteria decision making (MCDM) process. This paper employs Multi Attribute Utility Theory (MAUT), considering the multiplicative form of utility function, for ranking the prequalified construction contractors. In the present work, fifteen performance assessment criteria covering contracting company attributes, experience record, past performance, performance potential, financial stability and project specific criteria are considered for contractor evaluation. A case study of multi-storeyed building construction for which four contractors submitted bids is considered to illustrate the applicability and effectiveness of multiplicative approach of MAUT to rank the prequalified contractors. The proposed MAUT decision making methodology can be extended to decision making in other sectors also.

References

Chan, A., Chan, D., and Ho, K. (2003). An Empirical Study of the Benefits of Construction

Partnering in Hong Kong. Construction Management and Economics 21 (5): 523-533.

Dubois, A., and Gadde, L. E. (2002). The Construction Industry as a Loosely Coupled System:

Implications for Productivity and Innovation. Construction Management and Economics

(7): 621-632.

Dyer, J.S., Fishburn, P.C., Steuer, R.E., Wellenius, J., and Zionts, S. (1992). Multiple Criteria

Decision Making, Multiattribute Utility Theory: The Next Ten Years. Management

Science 38(5): 645-654.

Fong, P., and Choi, S. (2000). Final Contractor Selection using the Analytical Hierarchy

Process. Construction Management and Economics 18 (5): 547-557.

Goicoechea, A., Hansen, D. R. and Duckstein, L. (1982). Multi objective Decision Analysis with

Engineering and Business Applications. Wiley Publishing, New York.

Hatush, Z., and Skitmore, M. (1997). Criteria for contractor selection. Construction

Management and Economics 15(1): 19-38.

Jennings, P., and Holt, G.D.(1998). Prequalification and multicriteria selection: a measure of

contractors’ opinions. Construction Management and Economics 16: 651–660.

Keeney, R.L., and Raiffa, H. (1993). Decisions with multiple objectives: Preference and value

trade-offs. Cambridge University Press, Cambridge.

Keeny, R.L., and Wood, E.F.(1977). An illustrative example of the use of multiattribute utility

theory for water resource planning. Water resources research 13(4): 705-712.

Kid, J.B., and Prabhu, S.P. (1990). A practical example of multi attribute decision aiding

technique. Omega 18(2): 139-149.

Krishna Rao, M.V. (2013). Multi-criteria decision making for contractor selection – A fuzzy set

theoretic approach. PhD Thesis, Osmania University, Hyderabad, India.

Krishna Rao, M.V., Kumar, V.S.S., and Rathish Kumar, P. (2015). Contractor Selection Criteria

in the Indian Context: A Proposal. NICMAR Journal of Construction Management XXX

(III): 13–22.

Kumaraswamy, M., and Anvuur, A. (2008). Selecting Sustainable Teams for PP Projects.

Building and Environment 43 (6): 999-1009.

Kumaraswamy, M.M. (1996). Contractor Evaluation and Selection: a Hong Kong perspective.

Building and Environment 31(3): 273-282.

Lam, K., Hu, T., NG, T., Skitmore, M., and Cheung, S.O. (2001). A Fuzzy Neural Network

Approach for Contractor Prequalification. Construction Management and Economics 19

(2): 175-188.

Latham, M. (1994). Constructing the Team. London, HMSO.

Mustafa, M.A., and Ryan, T.C. (1990). Decision support for bid evaluation. International journal

of Project Management 8(4): 230-235.

Ngai, S., Drew, D., Lo, H. P., and Skitmore, M. (2002). A Theoretical Framework for

Determining the Minimum Number of Bidders in Construction Bidding Competitions.

Construction Management and Economics 20(6): 473-482.

Palaneeswaran, E., and Kumaraswamy, M. (2001). Recent Advances and Proposed

Improvements in Contractor Prequalification Methodologies. Building and Environment

: 73-87.

Palaneeswaran, E., and Kumaraswamy, M. (2001). Recent advances and proposed improvements

in contractor prequalification methodologies. Building and Environment 36(1): 73-87.

Plebankiewicz, E. (2008). Criteria of contractor selection used by polish investors. Journal of

Civil Engineering and Management 15(4): 377–385.

Puri, D., and Tiwari, S. (2014). Evaluating the Criteria for Contractors’ Selection and Bid

Evaluation. International Journal of Engineering Science Invention 3(7): 44 - 48.

Russell, J. S., Hancher, D. E., and Skibniewski, M. J. (1992). Contractor prequalification data

for construction owners. Construction Management and Economics 10: 117–29.

Singh,D., and Tiong, R.L.K. (2005a). A fuzzy decision making framework for contractor

selection. Journal of Construction Engineering and Management, ASCE 131 (1): 62-70.

Singh,D., and Tiong,R.L.K.(2005b). Contractor selection criteria: Investigation of opinions of

Singapore construction practitioners. Journal of Construction Engineering and

Management, ASCE 132(9): 998-1008.

Downloads

Published

2018-07-16

Issue

Section

Articles

How to Cite

PREQUALIFICATION OF CONTRACTOR IN THE CONSTRUCTION INDUSTRY USING MULTI-ATTRIBUTE UTILITY THEORY: A MULTIPLICATIVE APPROACH. (2018). Malaysian Journal of Civil Engineering, 28(3). https://doi.org/10.11113/mjce.v28.15987