Abstract

Port efficiency and port clustering are two aspects that have received different degrees of attention in the existing literature. While the actual estimation of port efficiency has been extensively studied, the existing literature has paid little attention to developing robust methodologies for port classification. In this paper, we review the literature on classification methods for port efficiency, and present an approach that combines stochastic frontier analysis, clustering and self-organized maps (SOM). Cluster methodologies that build on the estimated cost function parameters could group ports into performance metrics’ categories. This helps when setting improvement targets for ports as a function of their specific cluster. The methodology is applied to a database of Spanish port authorities. The dendrogram features three clusters and five outlier Spanish Port Authorities. SOM are employed to track the temporal evolution of Spanish Port Authorities that are of special interest for some reasons (i.e. outliers). Results show that use of a combination of cost frontier and cluster methods to define robust port typology and SOMs, jointly or in isolation, offers useful information to the decision-makers.

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