Shipping connectivity data analytics: Implications for maritime policy-Reference-Cited by-同舟云学术

Shipping connectivity data analytics: Implications for maritime policy

Published:2023-03 Issue: Volume:132 Page:112-127
ISSN:0967-070X
Container-title:Transport Policy
language:en
Short-container-title:Transport Policy

Author:

Yap Wei Yim^ORCID,Hsieh Cheng-Hsien,Lee Paul Tae-Woo

Publisher

Elsevier BV

Subject

Transportation,Geography, Planning and Development

Reference89 articles.

1. Mining port congestion indicators from big AIS data;AbuAlhaol,2018

2. User's guide to correlation coefficients;Akoglu;Turkish Journal of Emergency Medicine,2018

3. A review on data analytics for supply chain management: a case study;Anitha;Int. J. Inf. Eng. Electron. Bus.,2018

4. Does the traffic volume of a port determine connectivity? Revisiting port connectivity measures with high-frequency satellite data;Bai;J. Transport Geogr.,2022

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