Application of Multi-Criteria Analysis in the Public Procurement Process Optimization

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Abstract

One of the key steps in the implementation of a public procurement process is the criteria selection that are associated with the bidders, which are intended to ensure that bidders will be able to meet the requirements from the contract. Implicitly, the criteria selection includes their evaluation in situations when the criterion of the lowest price is not applied, but instead the criterion of the most economically advantageous tender. The aim of the paper is to show that decision-makers in the public sector can use multi-criteria analysis for the efficient and fair public procurement process implementation and the establishment of objective conditions for the contract awarding in accordance with the general social interests. In this sense, the paper presents a comparative approach to the Analytic Hierarchy Process and Analytic Network Process as the methods of support in decision making, measurement and evaluation criteria for the selection of the best bids in the procurement process. Hierarchical model with five criteria and nine sub-criteria and the network model, which takes into account the mutual influences of criteria, were developed in a hypothetical public procurement selection procedure for the best performers for the construction of the infrastructure facility. Selection of the best bidder, i.e. bids for the realization of the work, is distinctive, multi-criteria problem which includes both qualitative and quantitative factors.

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  • Alarcon L.F. & Mourgues C. (2002). Performance modelling for contractor selection. Journal of Management in Engineering 18 (2) 52–60.

  • Al-Harbi K. M. & A.-S. (2001). Application of the AHP in project management. International Journal of Project Management 19 (1) 19 –27.

  • Andruškevičius A. (2005). Evaluation of contractors by using COPRAS – the multiple criteria method. Technological and Economic Development of Economy 11(3) 158–169.

  • Azis I.J. (2010). Predicting a Recovery Date from the Economic Crisis of 2008. Socio economic planning sciences 44 122-129.

  • Banaitis A. & Banaitien N. (2006). Analysis of criteria for contractors’ qualification evaluation Technological and Economic. Development of Economy 12(4) 276–282.

  • Blair A.R. Mnadelker G.N. Saaty T.L. & Whitaker R. (2010). Forecasting the resurgence of the U.S. economy in 2010: An expert judgment approach. Socio - Economic Planning Sciences 44(3) 114-121.

  • Carr P. G. (2012). Investigation of Bid Price Competition Measured through Prebid Project Estimates Actual Bid Prices and Number of Bidders. Journal of Construction Engineering and Management 131(11) 1165–1172.

  • Dobi K. Gugić J. Kancijan D. (2010). AHP As a Decision Support Tool in the Multicriteria Evaluation of Bids in Public Procurement Proceedings of the ITI 2010 32nd Int. Conf. on Information Technology Interfaces June 21-24 Cavtat Croatia.

  • Fong P. S. W.& Choi S. K.-Y. (2000). Final contractor selection using the analytical hierarchy process. Construction Management & Economics 18(5) 547–557.

  • Ginevicius R. & Podvezko V. (2008). Multicriteria graphical analytical evaluation of the financial state of construction enterprises. Technological and Economic Development of Economy 14(4) 452–461.

  • Hatush Z. & Skitmore M. (1998). Contractor selection using multicriteria utility theory: An additive model. Building and Environment 33(2-3) 105–115.

  • Holt G.D. (1997). Classifying construction contractors: a case study using cluster analysis. Building Research and Information 25(6) 374–82.

  • Holt G.D. (1998). Which contractor selection methodology? International Journal of Project Management 16(3) 153–164.

  • Holt G. D. & Edwards D. J. (2005). Domestic builder selection in the UK housing repair and maintenance sector: a critique. Journal of Construction Research 6(1) 123–137.

  • Hughes M. (2005). Evaluation of the Local Government Procurement Agenda – Baseline Survey Report. The Office of the Deputy Prime Minister London. [On-line]. Available at www.odpm.gov.uk. [Last retrieved April 20 2006].

  • Ishizaka A. & Labib A. (2011). Review of the main developments in the analytic hierarchy process. Expert Systems with Applications 38(11): 14336–14345.

  • Izveštaj o javnim nabavkama u Republici Srbiji za period 01.01.2014-30.06.2014.godine Republika Srbija Uprava za javne nabavke Beograd 2014.

  • Jayant A. Paul V. & Kumar U. (2015). Aplication of Analytic Network Process (ANP) in Business Environment: A Comprehensive Literature Review IJRMET 5(1) 29-37.

  • Kandanala R. Al-Hussein M. & Vanderstar A. (2005). Automation of pre-bidding process for construction projects. Cost Engineering 147(6) 30–34.

  • Lam K.C. Hu T. Ng S.T. Skitmore M. & Cheung S.O. (2001). A fuzzy neural network approach for contractor prequalification. Construction Management & Economics 19(2) 175–188.

  • Laver J. & Larsberger O. (2011). The Art of identifying „The Most Economically Advantageous Tender” – the Use of Relative Evaluation Models in Public and Utilities Procurement Hannes Snellman Attorneys Ltd. www.whoswholegal.com.

  • Mahdi I.M. Riley M.J. Fereig S.M. & Alex A.P. (2002). A multi-criteria approach to contractor selection. Engineering Construction and Architectural Management 9(1) 29–37.

  • Minchin Jr. R.E. & Smith G.R. (2005). Quality-based contractor rating model for qualification and bidding purposes. Journal of Management in Engineering 21(1) 38–43.

  • Mitkus S. & Trinkuniene E. (2008). Reasoned decisions in construction contracts evaluation. Technological and Economic Development of Economy 14(3) 402–416.

  • Molenaar K. R. & Johnson D. E. (2003). Engineering the procurement phase to achieve the best value. Leadership & Management in Engineering 3(3) 137–141.

  • Ng S. T. & Skitmore R. M. (1999). Client and consultant perspectives of prequalification criteria. Building and Environment 34(5) 607–621.

  • Nikolovová P. Palguta J. & Pertold F. (2012). Public Contracts in the Czech Republic. What the Data Say on Behaviour of Contracting Authorities? Veřejné zakázky v ČR: Co říkají data o chování zadavatelů?. Cerge EI. [Online] 6. [Citace: 10. May 2013.] http://idea.cerge-ei.cz/docu.

  • Paul A. & Gutierrez G. (2005). Simple probability models for project contracting. European Journal of Operational Research 165(2) 329–338

  • Plenkiewicz E. (2009). Contractor prequalification model using fuzzy sets. Journal of Civil Engineering and Management 15(4) 377–385

  • Russell J.S. & Skibniewski M. (1987). A structured approach to the contractor prequalification process in the USA. CIB-SBI Fourth Int.Sym. on Building Economics Session D:240-51. Danish Building Research Copenhagen Denmark.

  • Russel J.S. (1991). Contractor failure: analysis. Journal of Performance of Constructed Facilities ASCE 5(3) 163-180.

  • Russell J. S. Hancher D. E. & Skibniewski M. J. (1992). Contractor prequalification data for construction owners. Construction Management & Economics 10(2) 117–135.

  • Saaty T. L. (1980). The Analytic Hierarchy Process New York McGraw-Hill.

  • Saaty T. L. & Kearns P. K. (1985). Analytical planning The Organization of Systems The Analytic Hierarchy Process Series Vol. IV RWS Publications Pittsburgh.

  • Saaty T. L. (2005). Theory and Applications of the Analytic Network Process Decision Making with Benefits Opportunities Costs and Risks RWS Publications Pittsburgh.

  • Saaty T. (2010). Economic forecasting with tangible and intagible criteria: the analytic hierarchy process of measurement and its validation Economic Horizons 1 5-45.

  • Saaty T.L. & Peniwati K. (2008). Group decision making: drawing out and reconciling differences. RWS Publications Pittsburgh.

  • Shen L. Y. Lu W. Shen Q. & Li H. (2003). A computer-aided decision support system for assessing a contractor’s competitiveness. Automation in Construction 12(5) 577–587.

  • Sipahi S. Timor M. (2010). The analytic hierarchy process and analytic network process: an overview of applications. Management Decision 48(5) 775 – 808

  • Skibniewski M. & Chao L. (1992). Evaluation of advanced construction technology with AHP method. Journal of Construction Engineering and Management ASCE 118 255–261.

  • Strand I. Ramada P. & Canton E. (2011). Public procurement in Europe Cost and effectiveness A study on procurement regulation. Prepared for the European Commission March 2011 London Economics ECORYS.

  • Topcu Y. I. (2004). A decision model proposal for construction contractor selection in Turkey. Building and Environment 39(4) 469–481.

  • Turskis Z. (2008). Multi-attribute contractors ranking method by applying ordering of feasible alternatives of solutions in terms of preferability technique. Technological and Economic Development of Economy 14(2) 224–239.

  • Vaidya O.S & Kumar S. (2006). Analytic hierarchy process: An overview of applications European Journal Of Operational Research Publisher: Emerald Group Publishing Limited 169(1) 1-29.

  • Wong C. H. Holt G. D. & Harris P. (2001). Multi-criteria selection or lowest price? Investigation of UK construction clients’ tender evaluation preferences. Engineering Construction & Architectural Management 8(4) 257–271.

  • Wong C. H. Holt G. D. & Cooper P. A. (2000). Lowest price or value? Investigation of UK construction clients’ tender selection process. Construction Management & Economics 18(7) 767–774.

  • Voulgaridou D. Kirytopoulos K.E. & Leopoulos V. (2009). An Analytic Network Process Approach for sales forecasting Operations Research International Journal 9 35-53.

  • Zavadskas E. K. Kaklauskas A. & Banaitiene N. (2001). Multi-criteria analysis of a building life cycle. Vilnius: Technika 380 p. (in Lithuanian).

  • http://curia.europa.eu/juris/liste.jsf?language=en&num=C-532/06

  • http://www.loc.gov/law/help/govt-procurement-law/eu.php

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