The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road

Abstract

Nearly 70% of the world’s maritime crude oil transportation relies on the Maritime Silk Road (MSR). In order to deeply explore the impact of slumping oil price on the shipping situation of tanker along the MSR, this paper establishes the relationship between monthly ship and oil price through Autoregressive Distributed Lag model. Distributions of cargo flow before and after the oil price slumped are compared to explore the changing law of tanker shipping situation. The study finds: (1) The correlation between the cargo flow situation of the tanker seaborne export and oil price, where the export cargo flow correlation is stronger than that of the import cargo flow. (2) The MSR tanker shipping situation is lagging (3 months) behind the impact of oil price. The lag effect in Europe, North Asia and East Asia is strong while that in Southeast Asia and South Asia is weak. (3) After the oil price slumped, the tanker shipping cargo flow increased less during the crude oil export stage, and the increase in the crude oil shipping trade after the transfer period was larger. The research results can provide a scientific basis for improving the decision-making ability of the crude oil shipping market and formulating maritime operations management measures.

Assessing the Connectivity Reliability of a Maritime Transport Network: A Case of Imported Crude Oil in China

“…The study also explored whether oil price volatility drives structural changes in the tanker shipping network and provided support for national policies related to tanker transport. Additionally, Mou et al [24] investigated the correlation and cargo flow patterns of maritime trade modes along the regions of the MSR through various types of MTN. Furthermore, Peng et al [25] utilized AIS trajectories to construct a global COMTN, revealing a complex hub-and-spoke structure and identifying the top three global hub ports.…”

“…In this section, the minimum disjoint path sets algorithm [47] is employed to compute the CR of the imported crude oil network under deliberate attacks. The calculation equations are presented in Equations ( 21)- (24).…”

Assessment of the Resilience of a Complex Network for Crude Oil Transportation on the Maritime Silk Road

“…AIS records the trajectory of ships, and the generated data contain the port of origin and the port of destination of each ship, which can be represented as O (origin) and D (destination) points in a complex network, where a line between OD (origin-destination) is an edge of the complex network [45]. This provides an excellent opportunity for the study of network resilience.…”

Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road

“…Peng et al [20] established the global crude oil transportation network between ports by using the crude oil AIS trajectory data from 2009 to 2016, evaluated the temporal and spatial characteristics of the port-port crude oil transportation network, and then analyzed the impact of each port in the global crude oil transportation network [21]. Based on the AIS data of crude oil in 2014, Mou et al [22] made an in-depth study on the lag effect of the collapse of oil price on the shipping situation of oil tankers along the Maritime Silk Road, which provided a scientific basis for improving the decision-making ability of crude oil transportation market and formulating maritime operation management measures. Wang et al [23] proposed autonomous statistic methods for counting daily ship traffic volume at ports only based on AIS data, then taking Shanghai port as an instance, they counted the daily ship traffic volume by using the proposed statistic methods for three common types of ship: cargo ship, passenger ship, and tanker ship, which could instruct shipping company to make sound judgment and decision for operational management.…”