Selecting a Contractor by Using a Novel Method for Multiple Attribute Analysis:
Weighted Aggregated Sum Product Assessment with Grey Values (WASPAS-G)
Edmundas Kazimieras ZAVADSKAS, Zenonas TURSKIS,
Vilnius Gediminas Technical University,
Sauletekio al. 11, LT-10223 Vilnius, Lithuania
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Abstract: Selecting the right contractor in construction industry is an important problem for an organization while thecompetition in global markets increases. Evaluating contractors’ performance is a multiple attribute decision makingprocess consisting of vagueness and imprecision. It is based on a set of hardly exact measurable attributes: capability andskills, occupational health and safety, technical capacity, managerial capability, bid amount, past performance andexperience, financial soundness. The goals and interests of the stakeholders should be taken into consideration whenselecting the attributes and their importance for the evaluation of contractors. In this context, the paper presents a novelmethod based on multiple attribute Weighted Aggregated Sum Product Assessment with the grey attributes scores –WASPAS-G method. The proposed method was applied in a case study of evaluation and selection of a right constructioncontractor, which has to be the most appropriate to stakeholders. The proposed technique, due to its capabilities ofhandling imprecise information because of applied grey relations and capabilities of providing decisions of enhancedaccuracy when aggregating two methods, could also be used to sustain the ranking of development strategies, selecting themost effective investment or management decisions.
Keywords: Multiple Attribute Decision Making (MADM), contractor selection, Weighted Aggregated Sum ProductAssessment (WASPAS), grey relations, WASPAS-G.
CITE THIS PAPER AS:
Edmundas Kazimieras ZAVADSKAS, Zenonas TURSKIS, Jurgita ANTUCHEVICIENE, Selecting a Contractor by Using a Novel Method for Multiple Attribute Analysis: Weighted Aggregated Sum Product Assessment with Grey Values (WASPAS-G), Studies in Informatics and Control, ISSN 1220-1766, vol. 24 (2), pp. 141-150, 2015.
Construction Industry Development Board (CIDB) reported that contractors waste up to 10% of the project costs when acting in a wrong way and correcting these wrong actions later. Most of construction projects involve risks that are difficult to control and analyse .
Contractor selection has attributes both qualitative and quantitative in nature. Construction cost and time overrun is a common problem in construction industries . This is because of the sixteen following main factors: a) no clearly defined scope of project in the contract, b) no proper cost control, c) contract dispute (unclear drawings and / or guideless regulations), d) high fluctuation in commodity prices, e) the gap between construction plan and reality is too great, f) material shortage or supply delay, g) time management, h) practical experience, I) modifications of the scope of construction, j) the level of demand quality, k) project team, l) project valuation does not match the collected payment, m) procurement contract, n) geology and topography, o) climate factor, p) natural disasters.
Abbasianjahromi et al.  argued that present condition of the construction industry imposes onerous responsibilities on contractors so they are very eager to subcontract some of their works. Therefore, subcontracting also should to be taken into account when selecting proper construction contractor .
Comprehensive evaluation and proper selection of the right contractor is an important decision that has a huge impact on the overall success of a construction project. Accordingly, there is a necessity for decision support methods to assist stakeholders in making optimal decisions when selecting a contractor .
The standard optimisation techniques could be applied when: a) the rules of the game are well laid out; b) the environment is predictable; c) actors behaviour is deterministic; d) costs vary within a small, narrow band, and e) relationships between variables are linear.
However, deciding whether to bid on a project is commonly referred to as the bid/no-bid decision. It is a critical activity associated with complexity as well as uncertainty. Various multi-attribute decision-making methods are now available to help stakeholders in choosing the best decisive course of actions, including those for evaluation of contractors [6 – 8], supporting products and services acquisition , technology  or software selection . Some of the models that involve both monetary and non-monetary criteria can be partly considered as multi-attribute decision-making models [12 – 14], but they do not provide a mathematical formulation and an optimization model as their basis for decision-making . The benefits of the above-mentioned actions in construction industry are unpredictable, relationships between attributes may be actually unknown . Furthermore, modelling real-world problems with crisp values of attributes under many conditions is inadequate because human judgement and his preferences are often vague and implicit and hardly can be estimated with exact numerical values .
To overcome the listed shortcomings, the paper presents a novel multiple attribute Weighted Aggregated Sum Product Assessment method with the grey attributes scores – WASPAS-G method. The advantages of the proposed technique are based on its capabilities of handling imprecise information due to applied grey relations and capabilities of providing decisions of enhanced accuracy when optimizing weighted aggregated assessment. The proposed novel method is applied in a case study of evaluation and selection of a right contractor from a set of potential construction contractors.
The paper is organized as follows. Chapter 2 presents preliminaries of grey theory. The main recent applications of grey extensions of MADM (Multiple Attribute Decision Making) methods in construction engineering and management are shortly reviewed in Chapter 3. Introduction to WASPAS method and development of WASPAS-G method is presented in Chapter 4. Chapter 5 contains case study of construction contractor selection by applying the novel multiple attribute decision making method.
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