Innovation & Management Review (May 2020)

Multicriteria decision choices for investment in innovative upper-middle income countries

  • Marcela do Carmo Silva,
  • Helder Gomes Costa,
  • Carlos Francisco Simões Gomes

DOI
https://doi.org/10.1108/INMR-02-2019-0016
Journal volume & issue
Vol. 17, no. 3
pp. 321 – 347

Abstract

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Purpose – The purpose of this paper is to observe how to invest in upper-middle income countries via an innovation perspective following global innovation index (GII) by multicriteria decision aid (MCDA) approach, once MCDA was designed to support subjective decisions. Design/methodology/approach – Pearson’s correlation was the milestone for understanding innovation indicators at upper-middle income countries profiles. In a MCDA first step, the analytical hierarchy process (AHP) was applied to obtain the criteria weight. In this step, the judgments or evaluations inputted in AHP were collected from a sample composed by five experts in GII. After getting the criteria weights compose to GII, Borda and Preference Ranking Organization Method for Enrichment Evaluations (PROMÉTHÉE) methods were applied to obtain an MCDA-based GII. The inputs for this second step were: the weights come from AHP output; and the countries performance came from GII data. Findings – As a result, it was found out the upper-middle countries’ rank to invest and groups with countries acting like “hubs” or “bridges” for economic sectors in near countries; when they are grouped according to their maximum and minimum scores profiles, observing not only a particular region but also similar profiles at diverse world areas. Originality/value – Pearson-AHP-PROMÉTHÉE works as a supportive decision tool for several and complex investment perspectives from criteria and alternatives analysis regarding innovation indicators for upper-middle income countries. This combination also demonstrates grouping possibilities, aligning profiles and not only ranking countries for investment and eliminating others but also grouping countries with similar profiles via innovation indicators MCDA combined application.

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