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19.08.2019 | Focus

IT2-based multidimensional evaluation approach to the signaling: investors’ priorities for the emerging industries

verfasst von: Hasan Dinçer, Šárka Hošková-Mayerová, Renata Korsakienė, Serhat Yüksel

Erschienen in: Soft Computing | Ausgabe 18/2020

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Abstract

Grounded in the signaling theory, the study aims to develop a model for evaluation of emerging industries. The integrated method is proposed to evaluate the emerging industries with DANP (DEMATEL-based Analytic Network Process) and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) methodologies based on interval type 2 fuzzy sets, respectively. The application is illustrated by considering cleantech, new generation of information technology, biology/biotechnology and high-end equipment manufacturing industries, three dimensions and 12 criteria. The novelties of the study lie in a set of criteria and alternatives for the signaling in emerging industries supported by the literature and suggest a hybrid decision-making model based on the type 2 fuzzy sets. The signaling determinants for emerging industries could be evaluated by the proposed interval type 2 hybrid decision-making approach more accurately. The results demonstrate that the firms, operating in emerging industries at the early stage of their development, have to put emphasis on the third-party endorsements and human capital criteria, aiming to attract external investors. The suggested method lets the external investors narrow their options in selecting emerging industries and select the most attractive industries or spread investments among the most attractive industries.

Vorheriger Artikel Special issue on dynamics of socioeconomic systems: systemic risk—complex systems

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Titel: IT2-based multidimensional evaluation approach to the signaling: investors’ priorities for the emerging industries
verfasst von: Hasan Dinçer
Šárka Hošková-Mayerová
Renata Korsakienė
Serhat Yüksel
Publikationsdatum: 19.08.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 18/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04288-6

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