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Article
Publication date: 29 June 2012

Philippe Nemery, Alessio Ishizaka, Mauricio Camargo and Laure Morel

Most of the proposed decision aid methods provide the user only with a prescriptive approach (quantitative analysis) without any descriptive approach (qualitative analysis). It is…

Abstract

Purpose

Most of the proposed decision aid methods provide the user only with a prescriptive approach (quantitative analysis) without any descriptive approach (qualitative analysis). It is therefore not possible to justify and recommend ways of improvement. The purpose of this paper is to introduce visualization techniques to complement prescriptive approaches.

Design/methodology/approach

Visual techniques have been developed for the FlowSort sorting method, namely the FS‐GAIA and stacked bar diagrams.

Findings

It is found that with visual techniques, fine details can be captured, e.g. detection of incomparability (with FS‐GAIA) and the composition of a score (with stacked bar diagrams).

Research limitations/implications

In the future, it is expected that other multi‐criteria decision methods will be complemented by prescriptive approaches.

Practical implications

A real case study is introduced in order to illustrate the practicality of the visual techniques. In this paper, the innovation performances of small and medium enterprises from the French Lorraine region are assessed.

Social implications

It is expected that the quality of the decisions taken are improved because of being better informed.

Originality/value

The paper, using a real case study, provides important new tools to enhance decision quality.

Abstract

Details

Journal of Modelling in Management, vol. 8 no. 3
Type: Research Article
ISSN: 1746-5664

Article
Publication date: 2 August 2022

Ahmet Aytekin, Ömer Faruk Görçün, Fatih Ecer, Dragan Pamucar and Çağlar Karamaşa

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed…

Abstract

Purpose

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.

Design/methodology/approach

The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.

Findings

The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.

Originality/value

The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.

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