Abstract

The present paper studies the bundling of road cargo flows of neighbouring seaports to a common hinterland. In specific cases, some hinterland flows can be too small to make bundling in a sufficient frequency possible. By combining the road freight flows of neighbouring ports, this problem can be solved. However, the additional cost of bundling and the loss of time need to be compensated for by a lower transport cost. The paper presents an empirical model for the 104 core Trans-European Transport Network (TEN-T) ports of the European Union (EU) and their 271 NUTS2 (Nomenclature of Territorial Units for Statistics) hinterland regions that allows identifying opportunities for bundling as well as the direct and external cost effects. By including the value of time (VOT) of each transport mode, the generalised cost is also calculated. The result is a business model that helps port authorities, and other port actors, to identify bundling projects that will lower the direct, generalised and external costs of the hinterland connectivity, thus increasing the port attractiveness for port users as well as lowering potential aversion by the surrounding community to port operations that create hinterland nuisance.

Highlights

  • Seaports, defined as a geographical location where cargo changes transport mode, one of these being a seagoing vessel, are important drivers of the regional economy of which they are part

  • The present paper studies the bundling of road cargo flows of neighbouring seaports to a common hinterland

  • The paper presents an empirical model for the 104 core Trans-European Transport Network (TEN-T) ports of the European Union (EU) and their 271 NUTS2 (Nomenclature of Territorial Units for Statistics) hinterland regions that allows identifying opportunities for bundling as well as the direct and external cost effects

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Summary

Introduction

Seaports, defined as a geographical location where cargo changes transport mode, one of these being a seagoing vessel, are important drivers of the regional economy of which they are part. When two supply chains have an equal out-of-pocket cost, the faster one has a lower generalised cost because less value is lost because less time is spent during the transport This discrete choice probability formula starts from the supply chain perspective of which a port is a part, PA being the probability that port A will be chosen rather than any of the competing ports. When a large port is treated as two (or more) separate ports, intuitively it is obvious that this should not change the probability of the other ports, but the discrete choice formula still leads to a different outcome This can be avoided by using a nested logit model [18]

Break-Even Analysis of Hinterland Bundling and Multimodality
Identifying Opportunities for Hinterland Cooperation
Cost Calculation Aspects of Port Cooperation in Hinterland Bundling
Time and Distance Costs
Conclusion
Time and Distance Parameters
Transfer and Bundling Costs
Empiricalisation
All-Road Situation from Zeebruges and Dunkirk to NUTS2 Düsseldorf
Results and Analysis
Conclusions and Further Research
Full Text
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