Wildcards – natural and artificial: the combination of a panel of experts and Fuzzy TOPSIS

Mohsen Mohammadi | Mohammad Rahim Eivazi | Jafar Sajjadi

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=84891
Date :  2016/12/05
Publish in :    Foresight
DOI :  https://doi.org/10.1108/fs-08-2016-0040

Keywords :artificial, combination, panel, experts, Fuzzy, TOPSIS

Abstract :

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Purpose The purpose of this paper is threefold: to classify wildcards into three particular types sharing similar characteristics; use the Fuzzy TOPSIS as a new method in foresight to turn qualitative ideas into quantitative ones; and apply a combination of Fuzzy TOPSIS and a panel of experts to prioritize weak signals. Design/methodology/approach In this paper, the authors classify wildcards into three particular types which share similar character: natural wildcards, artificial wildcards (Degree 1) and artificial wildcards (Degree 2). Wildcards point to unexpected and surprising events including important results that can form watershed in the development of a specific trend. In addition, the authors present a Fuzzy TOPSIS model which can be used in various cases to prioritize a number of weak signals and put them in order, so that the most important ones are likely to yield the wildcard in the future Findings