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A Two-Stage Decision Framework for Resolving Brownfield Conflicts
Based on the Graph Model of Conflict Resolution (GMCR), a two-stage decision framework is developed to reveal the essence of brownfield incidents and facilitate the resolution of brownfield conflicts caused by the incidents. More particularly, the forward GMCR is utilized in Stage I, the negotiation...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466265/ https://www.ncbi.nlm.nih.gov/pubmed/30909441 http://dx.doi.org/10.3390/ijerph16061039 |
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author | Han, Qingye Zhu, Yuming Ke, Ginger Y. Lin, Hongli |
author_facet | Han, Qingye Zhu, Yuming Ke, Ginger Y. Lin, Hongli |
author_sort | Han, Qingye |
collection | PubMed |
description | Based on the Graph Model of Conflict Resolution (GMCR), a two-stage decision framework is developed to reveal the essence of brownfield incidents and facilitate the resolution of brownfield conflicts caused by the incidents. More particularly, the forward GMCR is utilized in Stage I, the negotiation stage, to simulate the evolution of a Brownfield Conflict (BC) and predict its potential resolution via stability analysis. If no acceptable equilibrium can be obtained, the BC progresses into Stage II, the third-party-intervention stage, where the inverse GMCR is used to assist a third party in intervening the conflict to achieve a desirable outcome. To illustrate the practicality of this framework, a recent BC that occurred in Changzhou, China, is taken as a case study. Invaluable insights are provided through the computation and investigation of the corresponding preference relationships. |
format | Online Article Text |
id | pubmed-6466265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64662652019-04-22 A Two-Stage Decision Framework for Resolving Brownfield Conflicts Han, Qingye Zhu, Yuming Ke, Ginger Y. Lin, Hongli Int J Environ Res Public Health Article Based on the Graph Model of Conflict Resolution (GMCR), a two-stage decision framework is developed to reveal the essence of brownfield incidents and facilitate the resolution of brownfield conflicts caused by the incidents. More particularly, the forward GMCR is utilized in Stage I, the negotiation stage, to simulate the evolution of a Brownfield Conflict (BC) and predict its potential resolution via stability analysis. If no acceptable equilibrium can be obtained, the BC progresses into Stage II, the third-party-intervention stage, where the inverse GMCR is used to assist a third party in intervening the conflict to achieve a desirable outcome. To illustrate the practicality of this framework, a recent BC that occurred in Changzhou, China, is taken as a case study. Invaluable insights are provided through the computation and investigation of the corresponding preference relationships. MDPI 2019-03-22 2019-03 /pmc/articles/PMC6466265/ /pubmed/30909441 http://dx.doi.org/10.3390/ijerph16061039 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Han, Qingye Zhu, Yuming Ke, Ginger Y. Lin, Hongli A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title | A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title_full | A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title_fullStr | A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title_full_unstemmed | A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title_short | A Two-Stage Decision Framework for Resolving Brownfield Conflicts |
title_sort | two-stage decision framework for resolving brownfield conflicts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466265/ https://www.ncbi.nlm.nih.gov/pubmed/30909441 http://dx.doi.org/10.3390/ijerph16061039 |
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