Mismatch between volume and value: a new perspective on the significance of global ports

Abstract

ABSTRACTTo achieve high-volume and high-quality development of maritime transport and establish a port industry ecosystem, maritime stakeholders and national policymakers must recognise ports as crucial economic and trade windows. For a comprehensive and in-depth interpretation of a port, this study focuses on seaborne cargo as the entry point and proposes a methodological framework for assessing port importance. The proposed framework is based on a multi-methodological fusion and considers the relationship between the type, direction, volume, and value of the maritime cargo transported through the port, while distinguishing between the associated economic sectors, industry types, imports, exports and transhipments, and volume and value. Hence, port importance is assessed based on three dimensions: identification of the maritime transport cargo types for which the port has a comparative advantage, measurement of the port combined cargo transport capacity, and differentiation of the port type. The results reveal that seaborne cargo volumes and values are mismatched in global ports; high seaborne cargo value increases port importance to a greater degree than high seaborne cargo volume; and ports can be classified as inland serving, balanced inland and outward serving, and outward serving. These findings provide a research basis for a new port industrial-ecosystem construction strategy.KEYWORDS: Global portcargomaritime transportationRCA indexfactor analysisport type AcknowledgmentsZ. Li and Q, Zhang collaboratively conceived and designed the study. Q, Zhang completed the overall research. Y, Xie gave very valuable comments for writing. X, Qi provided valuable input into the production of the figures. All authors made substantial contributions to discussions of content and reviewed and edited the manuscript before submission. Thanks to all the authors for their contribution. We are very grateful to Jasper Verschuur for supporting the data. At the same time, we appreciate the reviewers and journal experts.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. OriginPro 2021, developed by OriginLab Corporation, is used for Graphing & Analysis. Thelink is https://www.originlab.com/2021.2. SPSS 20.0 is the world’s leading statistical software used to solve business and research problems by means of ad-hoc analysis, hypothesis testing, and predictive analytics. The link is https://www.ibm.com/support/pages/ibm-spss-statistics-20-documentation.Additional informationFundingThe work was supported by the Department of Education of Liaoning Province [XLYC2004008].