Measuring sensitivity of Procurement Decisions using superiority and Inferiority Ranking

Wrong decisions or inappropriate selection of equipment may lead to increase in cost and reduction in efficiency and effectiveness. Selecting right equipment has always been a key factor in the success of the process it is used for. In this study, superiority and inferiority ranking (SIR) methodis utilized for evaluation of most suitable offer for procurement of equipment installed inside a facility, whereas, analytical hierarchy process (AHP) is used to calculate the weights of factors that influence procurement decision. To achieve this target, a methodological framework of a series of interviews are conducted, then two questionnaire surveys are developed for identifying the important factors affecting the selection process of equipment and determining their relative importance. A solution of the problem is then designed in a model using AHP and SIR methods in addition to using the simple additive weighting (SAW) and technique for order preference by similarity to the ideal solution (TOPSIS) procedures to generate the superiority and inferiority flows. The model is generic and flexible and is used for the application of the multiple criteria decision making (MCDM) methods in the procurement process. The model also offers an efficient and convenient tool that aids its users to act in an orderly and methodical thinking, and guides them in making logical and robust decisions. A case study is presented to demonstrate the use of the developed model and sensitivity analysis is carried out to measure the robustness of the model in different scenarios.

[1]  C. A. Marazzi.  A value analysis method for the evaluation of telecommunication systems bid proposals , 1985, IEEE Transactions on Engineering Management.

[2]  Mohamed Marzouk,et al.  A decision support tool for construction bidding , 2003 .

[3]  Guohe Huang,et al.  Managing water resources system in a mixed inexact environment using superiority and inferiority measures , 2011, Stochastic Environmental Research and Risk Assessment.

[4]  A. Rebai.  Canonical fuzzy bags and bag fuzzy measures as a basis for MADM with mixed non cardinal data , 1994 .

[5]  Sławomir Biruk,et al.  Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment , 2010 .

[6]  Abdelwaheb Rebai,et al.  BBTOPSIS: a bag based technique for order preference by similarity to ideal solution , 1993 .

[7]  Harri Ehtamo,et al.  Interactive Multiple‐Criteria Methods for Reaching Pareto Optimal Agreements in Negotiations , 2001 .

[8]  Xiaozhan Xu,et al.  The SIR method: A superiority and inferiority ranking method for multiple criteria decision making , 2001, Eur. J. Oper. Res..

[9]  Serdar Ulubeyli,et al.  A multiple criteria decision‐making approach to the selection of concrete pumps , 2009 .

[10]  Leonas Ustinovichius,et al.  Determination of efficiency of investments in construction , 2004 .

[11]  Ana Nieto-Morote,et al.  A fuzzy multi-criteria decision making model for construction contractor prequalification , 2012 .

[12]  E. Palaneeswaran,et al.  Analytic hierarchy process based supplier selection framework for construction contractors , 2006 .

[13]  Gang Kou,et al.  A simple method to improve the consistency ratio of the pair-wise comparison matrix in ANP , 2011, Eur. J. Oper. Res..

[14]  Theodor J. Stewart,et al.  Multiple Criteria Decision Analysis , 2001 .

[15]  H. Raiffa.  The art and science of negotiation , 1983 .

[16]  Aviad Shapira,et al.  AHP-Based Equipment Selection Model for Construction Projects , 2005 .

[17]  Martin Skitmore,et al.  Contractor selection using multi criteria utility theory: an additive mode , 1998 .

[18]  Mohamed Marzouk.  A superiority and inferiority ranking model for contractor selection , 2008 .

[19]  E. Zavadskas,et al.  Application of a quantitative multiple criteria decision making (MCDM-1) approach to the analysis of investments in construction , 2007 .

[20]  Jyrki Wallenius,et al.  Advances in Negotiation Science , 1994 .

[21]  Aviad Shapira,et al.  “Soft” Considerations in Equipment Selection for Building Construction Projects , 2007 .

[22]  Joseph H. M. Tah,et al.  Genetic algorithms application and testing for equipment selection , 1999 .

[23]  J. Sebenius,et al.  Negotiation Analysis: Between Decisions and Games , 2007 .

[24]  Yi Peng,et al.  Ensemble of Software Defect Predictors: an AHP-Based Evaluation Method , 2011, Int. J. Inf. Technol. Decis. Mak..

[25]  Bernard Roy,et al.  Multicriteria programming of water supply systems for rural areas , 1992 .

[26]  Y. W. Wong,et al.  Selection of concrete pump using the Superiority and Inferiority Ranking method , 2004 .

[27]  Felix T.S. Chan,et al.  Interactive selection model for supplier selection process: an analytical hierarchy process approach , 2003 .

[28]  Awad S. Hanna,et al.  A fuzzy logic approach to the selection of cranes , 1999 .

[29]  William J. O'Brien,et al.  Rapid assessment and selection of engineered equipment suppliers , 2012 .

[30]  Simaan M. AbouRizk,et al.  UTILITY-THEORY MODEL FOR BID MARKUP DECISIONS , 1996 .

[31]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[32]  E. Triantaphyllou,et al.  A Sensitivity Analysis Approach for Some Deterministic Multi-Criteria Decision-Making Methods* , 1997 .

[33]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

[34]  Jingguo Wang,et al.  Negotiating wisely: Considerations based on MCDM/MAUT , 2008, Eur. J. Oper. Res..

[35]  Thomas L. Saaty,et al.  Decision making for leaders , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[36]  Jian-Bo Yang,et al.  Applying Evidential Reasoning to Prequalifying Construction Contractors , 2002 .

[37]  Burcu Yilmaz,et al.  A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming , 2011, Expert Syst. Appl..

[38]  Yi Peng,et al.  Evaluation of Classification Algorithms Using MCDM and Rank Correlation , 2012, Int. J. Inf. Technol. Decis. Mak..