Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107813
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dc.contributorFaculty of Business-
dc.creatorWang, T-
dc.creatorXu, J-
dc.creatorJin, Y-
dc.creatorWang, S-
dc.date.accessioned2024-07-12T06:06:58Z-
dc.date.available2024-07-12T06:06:58Z-
dc.identifier.urihttp://hdl.handle.net/10397/107813-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2024 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 (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wang T, Xu J, Jin Y, Wang S. Assessing the Belt and Road Initiative’s Impact: A Multi-Regression Model Based on Economic Interaction. Sustainability. 2024; 16(11):4694 is available at https://doi.org/10.3390/su16114694.en_US
dc.subjectBelt and Road Initiativeen_US
dc.subjectEconomic interactionen_US
dc.subjectEconomy and shipping performanceen_US
dc.subjectPrincipal component regressionen_US
dc.titleAssessing the belt and road initiative’s impact : a multi-regression model based on economic interactionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume16-
dc.identifier.issue11-
dc.identifier.doi10.3390/su16114694-
dcterms.abstractThis study examines the impact of joining the Belt and Road Initiative (BRI) on the economies of ASEAN countries, focusing on the shipping industry’s performance. Ten economic interaction indicators were analyzed using data from 2015–2022 and predicting future data for 2015–2030 through GM(1,1) and FOA-SVR models. The principal component regression (PCR) model, combined with the Analytic Hierarchy Process (AHP), assessed the correlation of these indicators with GDP and port container throughput (PCT). The findings reveal a strong correlation between economic interaction scores with China and economic and shipping performance, highlighting Chinese investment’s significant impact on GDP and shipping connectivity’s substantial influence on container throughput. This study provides a framework for quantifying organizational engagement levels and policy effectiveness-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSustainability, June 2024, v. 16, no. 11, 4694-
dcterms.isPartOfSustainability-
dcterms.issued2024-06-
dc.identifier.scopus2-s2.0-85195884955-
dc.identifier.eissn2071-1050-
dc.identifier.artn4694-
dc.description.validate202407 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2987ben_US
dc.identifier.SubFormID49066en_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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