A Model Optimizing the Private and Social Cost-Efficiency of Port-Hinterland Container Logistics (Contributo in atti di convegno)

Type
Label
  • A Model Optimizing the Private and Social Cost-Efficiency of Port-Hinterland Container Logistics (Contributo in atti di convegno) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Alternative label
  • Iannone Fedele (2011)
    A Model Optimizing the Private and Social Cost-Efficiency of Port-Hinterland Container Logistics
    in European Transport Conference 2011, Glasgow, Scozia, Regno Unito, 10-12 Ottobre 2011
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Iannone Fedele (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • paper pubblicato negli Atti della European Transport Conference 2011 organizzata dall'Association for European Transport, Glasgow, Scozia, Regno Unito (10-12 Ottobre 2011) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IRAT - Istituto di ricerche sulle attività terziarie (literal)
Titolo
  • A Model Optimizing the Private and Social Cost-Efficiency of Port-Hinterland Container Logistics (literal)
Abstract
  • The incorporation of the negative external impacts of transportation into the analysis and planning of supply chain operations and intermodal freight logistics systems has become an important research topic among scholars and one of the evolving areas of interest to practicioners. This paper intends to contribute to the literature by analyzing a sustainable port-hinterland container logistics problem. A capacitated multimodal and multicommodity network programming model, called \"interport model\", has been employed to investigate the inland distribution of maritime containers handled at the seaports of Naples and Salerno located in the Campania region of Southern Italy. The loading units can transit through the regional dry port facilities located at Nola and Marcianise (the so called \"interports\"), as well as through extra-regional locations with railway terminal, before reaching their destination. The model optimizes simultaneously the flows of containers imported and to be exported through the regional logistics system. It minimizes all the container-related generalized logistic costs throughout the entire port-hinterland multimodal network, while allowing the measurement of the logistic and socio-economic benefits arising both from shifting the seaport exit/entry of containers to the regional interports (the \"extended gateway\" concept), and from employing intermodal solutions for inland distribution. The internal logistic costs include transportation costs (by road and railway), terminal handling and storage costs, customs control costs, in-transit inventory holding costs, and container leasing costs. In addition, the objective function of the model also internalizes the external costs in terms of greenhouse gases emissions, air pollution, noise, accidents and congestion deriving from inland transport operations. The results in terms of logistic flows, internal costs and external costs deriving from the application of the model have been compared both with the real-life scenario and with the results deriving from the solution of a second model featuring the same structure and data, but whose objective function does not internalize the transport external diseconomies. The different scenarios have been also compared in terms of physical air emissions from transport. Finally, some sensitivity tests have been executed. By this way, it has been possible to make a comprehensive and detailed assessment of the potential to improve the current performances of the Campanian seaport-interport logistics system. The attained results can constitute a useful knowledge base for regional policy initiatives aimed at promoting intermodal logistics solutions addressing modal rebalance and the pursuit of social welfare. The paper is organized as follows. Section 1 provides an overview on introductory issues concerning sustainable logistics and port-hinterland container connections. Section 2 contains both a methodological description of the model and a stylized formulation of its objective function. Section 3 illustrates the main features and results of the empirical applications of the model; the results obtained in the different modeling scenarios are also compared with the observed real situation. Section 4 addresses conclusions. (literal)
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