Determination of the Social Contribution of Sustainable Additives for Asphalt Mixes Through Fuzzy Cognitive Mapping

Assessing infrastructure sustainability requires an evaluation of technical, economic, environmental, and social dimensions, with the latter often being overlooked. Asphalt mixtures incorporating end-of-life tire textile fiber additives in Chile have emerged as a sustainable alternative to conventional fibers. However, the social sustainability of these additives remains underexplored. This study develops a model to assess the social sustainability of asphalt additives in Chile using fuzzy cognitive mapping. The methodology includes three stages: (1) qualitative exploration of the conceptual model by information triangulation, (2) construction of a fuzzy cognitive model to estimate social contributions, and (3) dynamic analysis of four additives, including those derived from end-of-life tire textile fiber. The results show that these recycled additives generate distinct social impacts, particularly in terms of consumer interest, innovation, knowledge transfer, and regulatory alignment. Additionally, technical contributions and certifications significantly influence sustainability assessments, exhibiting greater independence from other factors. The findings highlight the potential of repurposed textile fiber as a socially sustainable alternative in asphalt production. This approach supports circular economy initiatives, fosters innovation, and enhances the acceptance of sustainable infrastructure materials in Chile, contributing to a more resilient and responsible construction sector.

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Publication Details

Journal
Applied Sciences
Published
2025-04-04
DOI
https://doi.org/10.3390/app15073994
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
0.00

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article

Determination of the Social Contribution of Sustainable Additives for Asphalt Mixes Through Fuzzy Cognitive Mapping

Alejandra Calabi-Floody, Leonardo Sierra, Víctor Yepes, Gonzalo Valdés et al.
Applied Sciences
Multi-Criteria Decision Making
article

Determination of the Social Contribution of Sustainable Additives for Asphalt Mixes Through Fuzzy Cognitive Mapping

Alejandra Calabi-Floody, Leonardo Sierra, Víctor Yepes, Gonzalo Valdés, Álvaro Filun-Santana
article en

Abstract

Assessing infrastructure sustainability requires an evaluation of technical, economic, environmental, and social dimensions, with the latter often being overlooked. Asphalt mixtures incorporating end-of-life tire textile fiber additives in Chile have emerged as a sustainable alternative to conventional fibers. However, the social sustainability of these additives remains underexplored. This study develops a model to assess the social sustainability of asphalt additives in Chile using fuzzy cognitive mapping. The methodology includes three stages: (1) qualitative exploration of the conceptual model by information triangulation, (2) construction of a fuzzy cognitive model to estimate social contributions, and (3) dynamic analysis of four additives, including those derived from end-of-life tire textile fiber. The results show that these recycled additives generate distinct social impacts, particularly in terms of consumer interest, innovation, knowledge transfer, and regulatory alignment. Additionally, technical contributions and certifications significantly influence sustainability assessments, exhibiting greater independence from other factors. The findings highlight the potential of repurposed textile fiber as a socially sustainable alternative in asphalt production. This approach supports circular economy initiatives, fosters innovation, and enhances the acceptance of sustainable infrastructure materials in Chile, contributing to a more resilient and responsible construction sector.

Applied SciencesVol. 15(7)
Universidad de La Frontera (CL), Universitat Politècnica de València (ES)
European Commission, Agencia Nacional de Investigación y Desarrollo, European Regional Development Fund, Agencia Estatal de Investigación, Fondo de Fomento al Desarrollo Científico y Tecnológico
Openalex Percentile: Top 93%
Multi-Criteria Decision Making
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