Normalization techniques for collaborative networks

Nazanin Vafaei (Instituto de Desenvolvimento de Novas Tecnologias, Universidade Nova de Lisboa UNINOVA, Caparica, Portugal)
Rita A. Ribeiro (Instituto de Desenvolvimento de Novas Tecnologias, Universidade Nova de Lisboa UNINOVA, Caparica, Portugal)
Luis M. Camarinha-Matos (Instituto de Desenvolvimento de Novas Tecnologias, Universidade Nova de Lisboa UNINOVA, Caparica, Portugal)
Leonilde Rocha Valera (University of Minho, Guimaraes, Portugal)

Kybernetes

ISSN: 0368-492X

Publication date: 19 June 2019

Abstract

Purpose

Normalization is a crucial step in all decision models, to produce comparable and dimensionless data from heterogeneous data. As such, various normalization techniques are available but their performance depends on a number of characteristics of the problem at hand. Thus, this study aims to introduce a recommendation framework for supporting users to select data normalization techniques that better fit the requirements in different application scenarios, based on multi-criteria decision methods.

Design/methodology/approach

Following the proposed approach, the authors compare six well-known normalization techniques applied to a case study of selecting suppliers in collaborative networks.

Findings

With this recommendation framework, the authors expect to contribute to improving the normalization of criteria in the evaluation and selection of suppliers and business partners in dynamic networked collaborative systems.

Originality/value

This is the first study about comparing normalization techniques for selecting the best normalization in dynamic multiple-criteria decision-making models in collaborative networks.

Keywords

Citation

Vafaei, N., Ribeiro, R., Camarinha-Matos, L. and Valera, L. (2019), "Normalization techniques for collaborative networks", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-09-2018-0476

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Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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