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IDENTIFICATION OF PERCEIVED RELATIONSHIPS BETWEEN ENVIRONMENTAL PERFORMANCE INDICATORS IN ECODESIGN PROJECTS: THE CASE OF RAIL INFRASTRUCTURE PROJECTS

Published online by Cambridge University Press:  19 June 2023

Joseph Mansour Salamé*
Affiliation:
Laboratoire Genie Industriel, Université Paris-Saclay, CentraleSupélec, France;
Yann Leroy
Affiliation:
Laboratoire Genie Industriel, Université Paris-Saclay, CentraleSupélec, France;
Michael Saidani
Affiliation:
Laboratoire Genie Industriel, Université Paris-Saclay, CentraleSupélec, France; Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, USA
Isabelle Nicolaï
Affiliation:
Laboratoire Genie Industriel, Université Paris-Saclay, CentraleSupélec, France;
*
Mansour Salamé, Joseph, CentraleSupelec - University Paris Saclay, France, [email protected]

Abstract

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Sharing information between stakeholders is a critical success factor for ecodesign projects. This sharing is based on indicators that can be interrelated, i.e., impacting each other.

This article focuses on the perception of environmental performance indicators’ relationships during the design phase of projects. It uses a DEMATEL approach combined with a graph-database visualization linking environmental performance indicators. While the DEMATEL approach highlights the critical environmental indicators, the graph-based visualization maps the primary interrelations of these factors and defines the best scale to manage them. The novelty here lies in the complementary use of these two methods to facilitate environmental project monitoring.

This research is applied to rail infrastructure projects. The main results insist on land optimization, landscape insertion, carbon footprint, economic benefits, and biodiversity measures as critical factors when designing these projects. The graph-based visualization maps the main oriented links between indicators, allowing managers to identify the gaps between the perceived knowledge and the ground truth, facilitating their project monitoring.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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