{"title":"Spatial-temporal effects on cargo throughput at Chinese ports: Insights from a multiscale geographically weighted regression approach","authors":"Xialan Fang , Jian Fu , Yihua Liu , Jun Ye","doi":"10.1016/j.ocecoaman.2025.107936","DOIUrl":null,"url":null,"abstract":"<div><div>Port cargo throughput is a key indicator for evaluating port operations and economic development, playing a crucial role in national economic growth, trade activities, and urban development. Understanding the factors that affect port cargo throughput is crucial for optimizing port management and policy planning. This study uses a multiscale geographically weighted regression (MGWR) model to analyze the determinants of port cargo throughput. This study utilized data from 55 ports in China to discuss the independent variables that affect spatial distribution, including regional gross domestic product, investment in road and waterway construction, total import and export volume, total retail sales of consumer goods, number of port berths, and consumption expenditure of urban residents. The regression results of MGWR indicate that compared with the fixed bandwidth geographically weighted regression (GWR) model, the MGWR model with adaptive bandwidth provides better fitting. The innovation of MGWR model lies in solving the single bandwidth limitation of traditional GWR. From the perspective of time change, we collect panel data from 2018 to 2023, and add variables such as the domestic emission control area policy (DECA), the COVID-19, and the geographical location of the port (whether the port is located inland or coastal) to study the impact of these variables on port cargo throughput. The regression results indicate that regional gross domestic product, total retail sales of consumer goods invested in highway construction, number of berths, DECA, and whether the port is located inland or coastal have a significant impact on the port's cargo throughput. From a temporal and spatial perspective, the spatial pattern of changes in port cargo throughput has gradually shifted from being dominated by coastal ports to a coordinated development of coastal and inland ports.</div></div>","PeriodicalId":54698,"journal":{"name":"Ocean & Coastal Management","volume":"271 ","pages":"Article 107936"},"PeriodicalIF":5.4000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean & Coastal Management","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0964569125003990","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
Port cargo throughput is a key indicator for evaluating port operations and economic development, playing a crucial role in national economic growth, trade activities, and urban development. Understanding the factors that affect port cargo throughput is crucial for optimizing port management and policy planning. This study uses a multiscale geographically weighted regression (MGWR) model to analyze the determinants of port cargo throughput. This study utilized data from 55 ports in China to discuss the independent variables that affect spatial distribution, including regional gross domestic product, investment in road and waterway construction, total import and export volume, total retail sales of consumer goods, number of port berths, and consumption expenditure of urban residents. The regression results of MGWR indicate that compared with the fixed bandwidth geographically weighted regression (GWR) model, the MGWR model with adaptive bandwidth provides better fitting. The innovation of MGWR model lies in solving the single bandwidth limitation of traditional GWR. From the perspective of time change, we collect panel data from 2018 to 2023, and add variables such as the domestic emission control area policy (DECA), the COVID-19, and the geographical location of the port (whether the port is located inland or coastal) to study the impact of these variables on port cargo throughput. The regression results indicate that regional gross domestic product, total retail sales of consumer goods invested in highway construction, number of berths, DECA, and whether the port is located inland or coastal have a significant impact on the port's cargo throughput. From a temporal and spatial perspective, the spatial pattern of changes in port cargo throughput has gradually shifted from being dominated by coastal ports to a coordinated development of coastal and inland ports.
期刊介绍:
Ocean & Coastal Management is the leading international journal dedicated to the study of all aspects of ocean and coastal management from the global to local levels.
We publish rigorously peer-reviewed manuscripts from all disciplines, and inter-/trans-disciplinary and co-designed research, but all submissions must make clear the relevance to management and/or governance issues relevant to the sustainable development and conservation of oceans and coasts.
Comparative studies (from sub-national to trans-national cases, and other management / policy arenas) are encouraged, as are studies that critically assess current management practices and governance approaches. Submissions involving robust analysis, development of theory, and improvement of management practice are especially welcome.