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University of the West Indies St Augustine Civil & Environmental Engineering . Procurement Selection Models- Why they do not work. Presented by: Hector Martin . Authors: Hector Martin, Timothy Lewis, Andrew Petersen. OUTLINE. Procurement within Trinidad
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Civil & Environmental Engineering
Procurement Selection Models- Why they do not work
Presented by: Hector Martin
Authors: Hector Martin, Timothy Lewis, Andrew Petersen
“The first requirement for any construction project is a clear and enforceable contract which covers all aspects of the project; fundamental to this …. …. is a need for greater standardization of contract forms and procurement methods” (Uff and Thornhill 2010).
4 decades - Poor Procurement practices has been described as the main theme (Joseph 2008).
Commission of enquiry into the construction sector (Terms of reference- Value for money, poor procurement practices) (2009)
Cochran ( 2009) Submission on behalf of the Institute of surveyors of T&T
GROTT (2005) Noted deficiencies and highlighted the need in its Procurement Reform White Paper
PMI – Exclusion of procurement selection method
What benefits are possible ? (Contractual 1987)
It can therefore be summarized that there exists a need to justify the selection of a procurement route and contract strategy in an informed manner and also to formulate a decision support framework and model to appropriately guide this selection process.
The development of a procurement delivery model should help to identify the best way of achieving the objectives of the project and value for money, taking account of the risks and constraints, leading to decisions about the funding mechanism and asset ownership for the project.
Can a Quantitative Procurement Decision Support Model be built using International Best Practice to suit the Trinidad and Tobago Construction Industry?
Building, verifying and validating a Quantitative Procurement Decision Support Model for the Trinidad and Tobago construction industry
Investigate selection criteria and principal factors previously considered by others to develop a refine set of factors for this study, verify and validate the usefulness to the Trinidad and Tobago context.
Would the same criteria for procurement method selection be applicable for all projects irrespective of the internal and external demands imposed, and the constantly changing nature of projects and client needs?
Determine the nature, and characteristics of procurement methods in Trinidad & Tobago.
Can Procurement Methods be Classified and Characterized?
Build a Quantitative Procurement Decision Support Model for the Trinidad and Tobago construction industry.
Can procurement methods be selected utilizing Radial Basis Artificial Neural Networks?
Within Trinidad and Tobago the identification of experts for procurement selection is limited (Ministry of Finance 2004). Therefore, in identifying the most appropriate methodology the procurement expert must be removed from the end-user interface and be incorporated into the model development.
Skitmore & Marsden (1998); Bennett and Grice (1990); Love, Skitmore & Earl (1998); Chang & Ive (2002); Ratnasabapathy & Rameezdeen (2007)
Source of Information
Sum of the attribute weights is typically larger than the weight directly attached to the objective (Weber, Eisenfuhr, and Detlof Von 1988).
The greater the amount of missing information the less favorable the evaluation (Johnson and Levin 1985).
All models developed have different weighting for a characteristic procurement method
Omission of correlation between variables
The rating are simple averages, the distribution of the response is not taken into consideration (Yiu 2006)
Multi Attribute Utility Theory
The user can adjust the relative important weightings of the selection factors to fit the current needs
(Mahdi and Alreshaid (2005); Zhang and Wang (2009); Sai-On et. al. (2001); Mafakheri et. al. (2007); Al Khalil (2002)
Priority vector derived can violate a condition of order preservation (Bana e Costa and Vansnick 2008).
Lacks a strong normative foundation and that the questions the decision maker must answer are ambiguous (Smith and Von Winterfeldt 2004).
Axioms conflict with the axioms of expected utility theory ambiguous (Smith and Von Winterfeldt 2004).
Applications of the AHP based on the assumption of the principle of hierarchic composition produce rankings based on the consistent responses of a decision maker that cannot be shown to be consistent with his or her preferences (Dyer 1990).
Analytical Hierarchy Process
A peer wise evaluation and ranking of alternatives
Luu, Ng, & Chen (2005) (CBR) - Chen et. al.(2010) [BP. ANN & DEA]
The storage of cases can be expensive which places a high demand on the efficiency of their retrieval.
Predictions are limited to the observed cases. (Eshach and Bitterman 2003).
The learning complexity is generally high (Zhang and zhang 1997).
Adaptive learning, Adaptive to changing environment.
Evidential response- decision with a measure of confidence.
Fault Tolerance via Redundant Information Coding (Li 2004).
It allows the avoidance of previous mistakes (Eshach and Bitterman 2003).
The selection of the factors to classify the procurement method will be undertaken using Factor Analysis.
There remains a need to numerically classify standard forms of contracts and by extension procurement route (Martin, Peterson, and Lewis 2011).
“By comparing observable characteristics (properties) of a set of objects, patterns can be noticed, relationships identified, and differentiation made among groups and individuals. In this manner meaning, context and a sense of organization are constructed.”(Eichinger 2009).
Ross (1998) emphasizes the Nobel Laureate Herbert Simon whose central finding was that pattern recognition is critical in most human decision making task: “The more relevant patterns at your disposal, the better your decision will be.”
Sub Question 2
FACTOR ANALYSIS and ANOVA (P<=0.01)
DELPHI and CLADISTICS
Design Bid Build Characteristic vector X2
Binary representation of X2
Figure 1: Advantage of RBF Network
Adaptive Resonance Theory (ART), LVQ, SOM, RNN, Hopfield and RBF
Where xi (i = 1, 2, … , n) and Yj (j = 1, 2, ... , m) are the input vectors (classification factors) of i-th and output vector (procurement methods) of the j-th sample respectively, and Cj ( j = 1, 2, … , n:, and wij denotes the output-layer weight linked between the i-th hidden neuron and the j-th output-layer. Pkn – The preference of the decision maker towards each alternative.
1. Gather Data
3.1 Network Type?
2. Select Predictand(s)
4.1 Data Cleansing
3.2 Training Algorithm
3. ANN Selection
4. Data Preprocessing
4.3 Data Standardization
5. Network Training
4.4 Data set
The contribution to new knowledge by this research will primarily be the development of a Decision Support model (RBF Neural Networks) for construction procurement in a new context (Trinidad and Tobago) with a new approach quantifying the graphical heuristics for contract selection noted by Tate (2003).
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