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Top1. Introduction
In Jordan, at least 22 different ministries and government institutions are available at a time. Each one of these entities has its official website which is improved at least every three years because of the rapid changes in information and technology. In most cases the ministry or institution would issue a tender to the public for revamping its website. Once the tenders are submitted then the evaluation process would start to select one winner bidder. Ministries in Jordan have realized for some time that the lowest price bid is not always the best choice. In many cases the quality of the proposed services, products or projects is not necessary met by the lowest bidder. This has been noticed in the past with different tender types, including hardware equipment, software, services, building construction, etc.
Many approaches for tenders’ evaluation do currently exist. The most common one is to have a mathematical equation which relies on weighted criteria or factors, that not only depends on the price but also have factors related to quality, such as company experience, new technologies used, project management, risk managements and other factors.
(Liu & Lai, 2000) have shown that evaluations that depends on price only have bad results. That is because it will ignore the importance of other attributes, such as quality, experience, performance, time, safety, and others. Liu have presented a multi attribute model based on weighted mathematical equation. The major selected attributes were as follows: safety, time, quality and cost.
Besides using equation of multi weighted criteria, fuzzy logic was introduced in many ways in tenders’ evaluation because most of the criteria used in evaluation are qualitative in nature. This makes using fuzzy approach more suitable for this kind of evaluation.
Many fuzzy logic-based models were applied to tender evaluation in building construction and engineering projects (Zhang, 2015; Liu & Lai, 2000; Nguyen, 1985; Hsieh, Lu & Tzeng, 2004; Jianxiang, 2010; Morote & Vila, 2012; Bendana, Del Cano & De La Cruz, 2004). A model for engineering project tender evaluation based on fuzzy Data Envelopment Analysis (DEA) and grey relational analysis have been presented (Zhang, 2015; Shen & Li, 2005; & Huang & Qiu, 2003). The presented model has used fuzzy synthetic assessment and DEA for qualitative indicators such as Project Quality, Construction Technology and Corporate Reputation. The following linguistic values in the assessment: very poor, poor, medium, good, and excellent have been used by (Zhang, 2015). The grey system theory for quantitative indicators that were actually cost indicators such as Project Quotation (in million-yuan) and Project Duration (in Days) have also been used by (Zhang, 2015). (Zhang, 2015) not only have shown how it is useful to evaluate the tenders based on qualitative and quantitative indicators but also found the reasons for ineffectiveness of bad bidders.
A fuzzy and multi-criteria model for tender evaluation have been proposed by (Nguyen, 1985; Brown & Yao, 1983). The proposed model has depended on the following three main criteria: cost, past experience of tenderers and present bid information.
A model for selecting alternatives for planning and design (P&D) in public office building have been presented by (Hsieh et al., 2004; Altrock & Krause, 1994; Baas & Kwakernaak, 1997; & Chang & Chen, 1994). First, the model has included the following three interest groups: owners, users and expert representatives. The model has used the Fuzzy Analytic Hierarchy Process (FAHP) to calculate the weight factors to each interest group. Second, it did use Fuzzy Multiple Criteria Decision Making (FMCDM) to represent group decision. (Hsieh et al., 2004) has effectively simplified the complicated multi-criteria and fuzzy perception problem of selecting alternatives for building P&D.