Compositional data techniques for the analysis of the container traffic share in a multi-port region

M Grifoll,J J Egozcue,M I Ortego

doi:10.1186/s12544-019-0350-z

M Grifoll, J J Egozcue + Show 1 more

Open Access

https://doi.org/10.1186/s12544-019-0350-z

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Abstract

The statistical techniques based on compositional data are applied to investigate the evolution of the traffic share of the container throughput in a multi-port system. Compositional vectors are those which contain relative information of parts of some whole. The application of conventional statistical techniques to compositional data may lead to erroneous conclusions and spurious correlations. Therefore, compositional data (CoDa) should be treated taking into account their own mathematical structure. The so-called log-ratio approach provides a set of transformations that allow to apply conventional statistical techniques to the transformed compositional data samples. Thus, the objective of this paper is double. As a first stage it aims to introduce the CoDa formalism and highlight its potentiality in the port container throughput analysis as example of transport system providing an applied example: the container throughput evolution in the Spanish Mediterranean Ports system during the period 1976–2015. Second, based on the previous analysis, the aim is to characterize the container throughput in SpanishMed ports and its temporal evolution. The CoDa analysis clarifies the interpretation and data association of the container traffic throughput evolution in function of some selected change points: boom of containerization in 1990s and 2008 crisis. This contribution proves that the CoDa methodology is useful to investigate the complexity of the transport disciplines in order to understand and to manage the spatial integration that results from the movement of people and freight.

Highlights

Transport disciplines are motivated to explain the spatial integration that result from the movement of people and freight from one place to another
compositional data (CoDa) techniques have been applied to problems in many areas of science such as social sciences [19], earth science [20], climate change [23], production engineering [31], geostatistics [12] or economy [16]. These works remark the suitability of the CoDa methodology for a proper interpretation of data sets when we focus on the relative information rather than the absolute amounts
7 Conclusions The SpanishMed port system has been used as an example of introducing the CoDa methodology in transport disciplines

Summary

Introduction

Transport disciplines are motivated to explain the spatial integration that result from the movement of people and freight from one place to another. Modes and networks are the basis of complex systems under constant evolution influenced by the geo-spatial economy development (with private and public agents), growth of infrastructures and physical restrictions. Containerization plays an important role in the maritime transport and in the global economy growth. Since the first wave of containerization (1970s), the global container traffic has been reformulated seeking economy of scales and more efficient distribution systems (e.g. huband-spoke model or transshipment activity). In this sense, the container throughput share of ports has evolved at the same time that the industrial regions and global trade have shifted. An S-shaped curve has been observed in the traffic evolution of world ports

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