Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31339
Appears in Collections:Management, Work and Organisation Journal Articles
Peer Review Status: Refereed
Title: Methodology for gender analysis in transport: Factors with influence in women's inclusion as professionals and users of transport infrastructures
Author(s): García-Jiménez, Elena
Poveda-Reyes, Sara
Molero, Gemma Dolores
Santarremigia, Francisco Enrique
Gorrini, Andrea
Hail, Yvonne
Ababio-Donkor, Augustus
Leva, Maria Chiara
Mauriello, Filomena
Keywords: fairness characteristics
clustering
decision-making process
public transport
bike sharing
employment
autonomous vehicles
Issue Date: May-2020
Citation: García-Jiménez E, Poveda-Reyes S, Molero GD, Santarremigia FE, Gorrini A, Hail Y, Ababio-Donkor A, Leva MC & Mauriello F (2020) Methodology for gender analysis in transport: Factors with influence in women's inclusion as professionals and users of transport infrastructures. Sustainability, 12 (9), Art. No.: 3656. https://doi.org/10.3390/su12093656
Abstract: This work analyzes gendered processes by a methodology based on clustering factors with influence in the decision-making process of women as users or employees of the transport system. Considering gender as a social construction which changes over time and space, this study is based on the concept of a woman as a person who adopts this role in society. This paper performs a deep analysis of those factors women consider as needs and barriers to use or work in the transport system in four scenarios: railway public transport infrastructures, automated vehicles, bicycle sharing, and jobholders. A literature review and focus group discussions were performed under the consideration that the definition of woman includes the addition of several personal characteristics (age, sexual orientation, family responsibilities, and culture). The data analysis allowed the identification of fairness characteristics (FCs) that affect the interaction of women with the transport system for each scenario. A methodology for clustering the fairness characteristics identified the main areas of action to improve the inclusion of women within each use case. Further studies will be focused on the quantification and prioritization of the FCs through mathematical methods and the suggestion of inclusive measures by an interdisciplinary panel.
DOI Link: 10.3390/su12093656
Rights: This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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