Clustering and performance: the case of maritime clustering in The Netherlands

Over the last years, the concept of clustering has become a central concept for analysing the competitiveness of nations, industries and firms. The cluster concept can be usefully applied to study clustering of maritime activities. Maritime activities, such as shipping, shipbuilding and port and maritime services, are clearly geographically concentrated in a number of maritime clusters. Due to ongoing internationalization in these industries, the concentration of maritime activities in clusters is likely to increase. This observation leads to two important research questions: what are the advantages for firms to locate in clusters and what factors influence the development of maritime clusters? This study identifies four agglomeration economies that attract firms to cluster: a joint labour pool, a broad supplier and customer base, knowledge spillovers, and low transaction costs. Furthermore, it discusses the effects of aspects of the cluster structure, being the presence of internal competition, the heterogeneity of the cluster population, the entry and exit barriers, and the presence of (above mentioned) agglomeration effects. It also briefly discusses the important issue of cluster governance. This overview allows one to develop a theoretical framework to analyse clusters. In the empirical part, this framework is applied to the maritime cluster in The Netherlands. Based on empirical data, from surveys amongst firms in the maritime cluster, studies commissioned by the Dutch maritime Network and regional statistics, the presence of agglomeration economies in the cluster is shown. Secondly, it is shown that the cluster structure is beneficial for the performance. This paper finishes with conclusions and suggestions for further research.     

韩国高速铁路列车

介绍了在韩国高速线上运行的KTX列车,以及将要运行的HSR-350X样机。     

A behavioural car-following model for computer simulation

The ability to predict the response of a vehicle in a stream of traffic to the behaviour of its predecessor is important in estimating what effect changes to the driving environment will have on traffic flow. Various proposed to explain this behaviour have different strengths and weaknesses. The paper constructs a new model for the response of the following vehicle based on the assumption that each driver sets limits to his desired braking and acceleration rates. The parameters in the model correspond directly to obvious characteristics of driver behaviour and the paper goes on to show that when realistic values are assigned to the parameters in a simulation, the model reproduces the characteristics of real traffic flow.     

Are AIS-based trade volume estimates reliable? The case of crude oil exports

Most global trade statistics in the public domain refer to official customs data, which are not generally available on a micro (individual cargo) level. With the increasing availability and completeness of ship positioning data from the global Automated Identification System (AIS), it is possible to derive more timely and detailed trade statistics for homogeneous commodity groups. The objective of this article is twofold: (1) to compare the accuracy of AIS-derived trade statistics to official customs data in the crude oil market and (2) to add a breakdown of trade by vessel size over time. We find that while AIS-derived data for seaborne crude exports show good alignment with official export numbers in aggregate, there are substantial temporal and geographical differences across countries and time due to the use of pipelines and transshipment in parts of the supply chain. We highlight the challenges in properly structuring and aggregating micro-level cargo data. Our findings are important for the proper derivation of shipping demand from trade data.