|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|381968||660712||2016||12 صفحه PDF||سفارش دهید||دانلود رایگان|
• Analysing ICT suppliers’ offers in contracting processes is crucial.
• A Linguistic Multi-Criteria Decision-Making model is proposed to do it.
• A fast and objective decision-making is achieved using a user-friendly tool.
• The model is validated by applying it to a real case study in the ICT sector.
• The main advantages of applying this model are presented.
Tender analysis processes are everyday processes in any company, but they become even more important when the financial resources are limited. Achieving optimal and transparent tender analysis processes requires hard work from everyone involved. This paper proposes a linguistic multi-criteria decision-making model which helps decision-makers in this task by automating it. To do that, the proposal requires diverse experts to assess different criteria and establish their corresponding weights. The processing of all these input data will determine a minimum value, called profile, to consider an alternative as valid. Additionally, assessments of a similar (probably external) process will be taken into account, becoming a reference valuation. Unlike other decision-making models, the use of this last value gives an idea of the goodness of the result depending on whether the solution obtained is close to the reference value. To the best of our knowledge, there is no expert or intelligent system specifically designed to fully meet the needs of tender analysis processes. For both input and output process stages carried out in our proposal, 2-tuple linguistic labels have been used. These linguistic labels were chosen to facilitate decision-making for the staff involved in the process, as well as for being the most suitable communication way used by human beings. To validate the model, we apply it to a case study in the ICT (Information and Communications Technology) sector. In addition, we include a literature review related to applications using the 2-tuple representation, as well as a comparison of our proposal with related methods, including the results obtained by these methods for the case study presented.
Journal: Expert Systems with Applications - Volume 57, 15 September 2016, Pages 127–138