{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:16:59Z","timestamp":1760059019486,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T00:00:00Z","timestamp":1747008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["72371045"],"award-info":[{"award-number":["72371045"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>This paper utilizes AIS (Automatic Identification System) data to study the micro-level features of the international container capacity correlation network and their impact on shipping freight rates. It proposes, for the first time, constructing a capacity correlation network based on the correlation of operational capacity between different shipping routes. This approach captures micro changes in the shipping market by observing the \u201csynchronized increase and decrease\u201d in operational capacity across all routes, whereby \u201cone decreases while the other increases\u201d between routes. Secondly, a continuous synchronization method is introduced to construct a capacity correlation network feature index, reflecting trends in the structural changes in the capacity correlation network. This method establishes the capacity correlation network\u2019s features without causing information loss, while capturing all detailed characteristics of the network and assigning \u201cweights\u201d based on the continuity of all features. Finally, the impact of the capacity correlation network feature index on shipping freight rates is examined. Experimental results indicate that the capacity correlation network feature index has a significant impact on shipping freight rates, which cannot be explained by factors such as supply, demand, or costs. This study is beneficial for revealing the price formation mechanism in the shipping market from a micro perspective.<\/jats:p>","DOI":"10.3390\/systems13050371","type":"journal-article","created":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T12:18:06Z","timestamp":1747052286000},"page":"371","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysis of the Features of Capacity Correlation Network and Its Impact on Shipping Freight Rate"],"prefix":"10.3390","volume":"13","author":[{"given":"Wei","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Maritime Economics and Management, Dalian Maritime University, Dalian 116000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Sui","sequence":"additional","affiliation":[{"name":"School of Maritime Economics and Management, Dalian Maritime University, Dalian 116000, China"},{"name":"Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Maritime Economics and Management, Dalian Maritime University, Dalian 116000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.trb.2020.01.003","article-title":"Pricing with Risk Sensitive Competing Container Shipping Lines: Will Risk Seeking Do More Good than Harm?","volume":"133","author":"Choi","year":"2020","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_2","first-page":"176","article-title":"Analysis and combined forecasting of China containerized freight index based on VMD","volume":"41","author":"Tang","year":"2021","journal-title":"Syst. Eng.-Theory Pract."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.tranpol.2021.10.021","article-title":"The container transport system during Covid-19: An analysis through the prism of complex networks","volume":"115","author":"Guerrero","year":"2022","journal-title":"Transp. Policy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/s12544-022-00566-x","article-title":"The dynamic interaction between COVID-19 and shipping freight rates: A quantile on quantile analysis","volume":"14","author":"Khan","year":"2022","journal-title":"Eur. Transp. Res. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1057\/s41278-020-00180-5","article-title":"Disruptions and resilience in global container shipping and ports: The COVID-19 pandemic versus the 2008\u20132009 financial crisis","volume":"23","author":"Notteboom","year":"2021","journal-title":"Marit. Econ. Logist."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"104004","DOI":"10.1016\/j.jtrangeo.2024.104004","article-title":"Geopolitical tension and shipping network disruption: Analysis of the Red Sea crisis on container port calls","volume":"121","author":"Yap","year":"2024","journal-title":"J. Transp. Geogr."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Sui, C., Wang, S., Liang, J.M., and Nikos, K.N. (2024). The Supply-Elasticity-Based Influence of Operating Capacity on Freight Rates in the Container Shipping Market. SSRN, 4910365. Available online: https:\/\/ssrn.com\/abstract=4910365.","DOI":"10.2139\/ssrn.4910365"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.jsc.2016.03.009","article-title":"A persistence landscapes toolbox for topological statistics","volume":"78","author":"Bubenik","year":"2017","journal-title":"J. Symb. Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1057\/mel.2012.18","article-title":"Forecasting spot rates at main routes in the dry bulk market","volume":"14","author":"Chen","year":"2012","journal-title":"Marit. Econ. Logist."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"121383","DOI":"10.1016\/j.energy.2021.121383","article-title":"Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach","volume":"235","author":"Bai","year":"2021","journal-title":"Energy"},{"key":"ref_11","first-page":"713","article-title":"Cross-market impacts of shipping and bulk commodities: The evidence from iron ore and its routes","volume":"42","author":"Sui","year":"2022","journal-title":"Syst. Eng. Theory Pract."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"103651","DOI":"10.1016\/j.tre.2024.103651","article-title":"Sentiment as a shipping market predictor: Testing market-speciffc language models","volume":"189","author":"Sui","year":"2024","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.tre.2018.08.012","article-title":"Volatility forecasting across tanker freight rates: The role of oil price shocks","volume":"118","author":"Gavriilidis","year":"2018","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tre.2019.08.003","article-title":"Understanding the fundamentals of freight markets volatility","volume":"130","author":"Lim","year":"2019","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"102490","DOI":"10.1016\/j.tre.2021.102490","article-title":"Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage","volume":"155","author":"Bai","year":"2021","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"126779","DOI":"10.1016\/j.energy.2023.126779","article-title":"The impact of geopolitical risk on the behavior of oil prices and freight rates","volume":"269","author":"Monge","year":"2023","journal-title":"Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.tre.2019.03.015","article-title":"The eye in the sky\u2013Freight rate effects of tanker supply","volume":"125","author":"Regli","year":"2019","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102326","DOI":"10.1016\/j.tre.2021.102326","article-title":"A data fusion approach to predict shipping efficiency for bulk carriers","volume":"149","author":"Sugrue","year":"2021","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.trb.2021.02.008","article-title":"Optimizing freight rate of spot market containers with uncertainties in shipping demand and available ship capacity","volume":"146","author":"Wang","year":"2021","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.tranpol.2022.04.006","article-title":"Impact of COVID-19 on China\u2019s international liner shipping network based on AIS data","volume":"121","author":"Jin","year":"2022","journal-title":"Transp. Policy."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"103694","DOI":"10.1016\/j.tre.2024.103694","article-title":"Multidimensional container shipping alliance decisions among competitors: Impact of capacity constraints and market competition","volume":"190","author":"Wang","year":"2024","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/s10479-018-3023-8","article-title":"Optimization in liner shipping. Ann","volume":"271","author":"Brouer","year":"2018","journal-title":"Oper. Res."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Yu, H., Fang, Z., Lu, F., Murray, A.T., Zhao, Z., Xu, Y., and Yang, X. (2019). Massive automatic identification system sensor trajectory data-based multi-layer linkage network dynamics of maritime transport along 21st-century maritime silk road. Sensors, 19.","DOI":"10.3390\/s19194197"},{"key":"ref_24","first-page":"390","article-title":"Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes. Appl","volume":"237","author":"Yu","year":"2019","journal-title":"Energy."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Tsiotas, D., and Ducruet, C. (2021). Measuring the effect of distance on the network topology of the Global Container Shipping Network. Sci. Rep., 11.","DOI":"10.1038\/s41598-021-00387-3"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103151","DOI":"10.1016\/j.trb.2024.103151","article-title":"Shore-power capacity allocation in a container shipping network under ships\u2019 strategic behaviors","volume":"192","author":"Tan","year":"2025","journal-title":"Transp. Res. Part B."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"857","DOI":"10.2307\/2580193","article-title":"Structure and Dynamics of the Global Economy: Network Analysis of International Trade 1965\u20131980","volume":"70","author":"Smith","year":"1992","journal-title":"Soc. Forces."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1137\/S003614450342480","article-title":"The structure and function of complex networks","volume":"45","author":"Newman","year":"2003","journal-title":"SIAM Rev."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"103321","DOI":"10.1016\/j.resourpol.2023.103321","article-title":"Impacts of China\u2019s exports decline in rare earth primary materials from a trade network-based perspective","volume":"81","author":"Hu","year":"2023","journal-title":"Resour. Policy."},{"key":"ref_30","first-page":"77","article-title":"Statistical topology data analysis using persistence landscapes","volume":"16","author":"Bubenik","year":"2015","journal-title":"J. Mach. Learn. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1016\/j.physa.2017.09.028","article-title":"Topological data analysis of financial time series: Landscapes of crashes","volume":"491","author":"Gidea","year":"2018","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"126459","DOI":"10.1016\/j.physa.2021.126459","article-title":"Early warning signals of financial crises using persistent homology","volume":"586","author":"Ismail","year":"2022","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Tu, X., Yang, Y., Lin, Y., and Ma, S. (2023). Analysis of influencing factors and prediction of China\u2019s Containerized Freight Index. Front. Mar. Sci., 10.","DOI":"10.3389\/fmars.2023.1245542"},{"key":"ref_34","first-page":"1927","article-title":"Research on the long memory linkage effect of economic policy uncertainty on shipping market and financial market","volume":"43","author":"Meng","year":"2023","journal-title":"Syst. Eng.-Theory Pract."}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/5\/371\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:31:32Z","timestamp":1760031092000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/5\/371"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,12]]},"references-count":34,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["systems13050371"],"URL":"https:\/\/doi.org\/10.3390\/systems13050371","relation":{},"ISSN":["2079-8954"],"issn-type":[{"type":"electronic","value":"2079-8954"}],"subject":[],"published":{"date-parts":[[2025,5,12]]}}}