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Characterizing the evolution of the Yangtze River Delta multi-port system using compositional data techniques
dc.contributor.author | Huang, Dong |
dc.contributor.author | Grifoll Colls, Manel |
dc.contributor.author | Feng, Hongxiang |
dc.contributor.author | Ortego Martínez, María Isabel |
dc.contributor.author | Zheng, Pengjun |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Enginyeria Civil |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental |
dc.date.accessioned | 2022-01-12T10:53:53Z |
dc.date.available | 2023-03-01T01:32:09Z |
dc.date.issued | 2021-09-12 |
dc.identifier.citation | Huang, D. [et al.]. Characterizing the evolution of the Yangtze River Delta multi-port system using compositional data techniques. "Maritime Policy & Management", 12 Setembre 2021, vol. 49, núm. 5, p. 667-684. |
dc.identifier.issn | 0308-8839 |
dc.identifier.uri | http://hdl.handle.net/2117/359408 |
dc.description | This is an Accepted Manuscript of an article published by Taylor & Francis Group in Maritime Policy & Management on Published online: 12 Sep 2021, available online at: http://www.tandfonline.com/10.1080/03088839.2021.1972175. |
dc.description.abstract | The Yangtze River Delta multi-port system (YMPS) receives increasing attention due to its relevance in world trade and excellent competitiveness in the container traffic market. To insight into the development pattern of YMPS, this paper proposes a method that combines the Hierarchical Clustering with compositional data (CoDa) exploratory tools (i.e., biplot and dendrogram) to explore the temporal and spatial evolution of the YMPS from 1992 to 2019. CoDa describes parts of some whole (i.e., frequency and percentage), conveying relative information in the ratios between its components. Container traffic share in a multi-port region is typical CoDa. Traditional statistical approaches to CoDa could lead to spurious correlations and erroneous conclusions. However, using suitable CoDa techniques, such as the centered log-ratio (clr) transformation, can effectively avoid these misinterpretations. The novel method can simultaneously find the temporal and spatial characteristics. The findings indicate that the development of the YMPS has gone through four stages and the evolution of the YMPS is characterized by a tendency towards a ‘multi-core development’ and faces a differentiated pattern of ‘peripheral port challenges’. The analysis further improves the port system’s evolutionary model and explains the underlying reason for the YMPS development. CoDa techniques also provide a new perspective for the temporal and spatial evolution of the transport discipline. |
dc.description.sponsorship | This work was supported by the Ministerio de Ciencia, Innovación y Universidades under project Methods for Compositional analysis of Data (CODAMET) [grant number RTI2018-095518-B-C22, 2019-2021] and 111 Project [grant number D21013] |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 4.0 International |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Anàlisi multivariant |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització |
dc.subject.lcsh | Survival analysis (Biometry) |
dc.subject.lcsh | Operations research |
dc.subject.other | Yangtze River Delta multi-port system |
dc.subject.other | Compositional data |
dc.subject.other | Concentration indexes |
dc.subject.other | Hierarchical Clustering |
dc.title | Characterizing the evolution of the Yangtze River Delta multi-port system using compositional data techniques |
dc.type | Article |
dc.subject.lemac | Anàlisi de supervivència (Biometria) |
dc.subject.lemac | Investigació operativa |
dc.contributor.group | Universitat Politècnica de Catalunya. BIT - Barcelona Innovative Transportation |
dc.contributor.group | Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis |
dc.identifier.doi | 10.1080/03088839.2021.1972175 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.ams | Classificació AMS::62 Statistics::62N Survival analysis and censored data |
dc.subject.ams | Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science |
dc.relation.publisherversion | https://www.tandfonline.com/doi/abs/10.1080/03088839.2021.1972175 |
dc.rights.access | Open Access |
local.identifier.drac | 32106302 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095518-B-C22/ES/TRANSFERENCIA Y DESARROLLO METODOLOGICO DE TECNICAS COMPOSICIONALES PARA LAS CIENCIAS APLICADAS Y LA INGENIERIA/ |
local.citation.author | Huang, D.; Grifoll, M.; Feng , H.; Ortego, M.I.; Zheng, P. |
local.citation.publicationName | Maritime Policy & Management |
local.citation.volume | 49 |
local.citation.number | 5 |
local.citation.startingPage | 667 |
local.citation.endingPage | 684 |
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