Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36929
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dc.contributor.authorPAESEN, Jasper-
dc.contributor.authorCARIS, An-
dc.contributor.authorVERDONCK, Lotte-
dc.contributor.authorDEFRYN, Christof-
dc.date.accessioned2022-03-18T13:10:17Z-
dc.date.available2022-03-18T13:10:17Z-
dc.date.issued2022-
dc.date.submitted2022-03-14T08:14:28Z-
dc.identifier.citation19th CEMS Research Seminar 2022 - Supply Chain Management - Recent Trends and Future Perspectives, Riezlern, Austria, January 19-23/2022-
dc.identifier.urihttp://hdl.handle.net/1942/36929-
dc.description.abstractSupported by a significant increase in awareness among people all over the world, sustainability has become a key priority in national and international politics. The European Commission is clear and calls for a climate-neutral Europe by 2050. A fast and further reduction of greenhouse gas (GHG) emissions is necessary to reach this goal. Being responsible for 24.6% of all European GHG emissions in 2018, the transport sector has a key contribution in decarbonising the European economy (EEA, 2021). With one fifth of all road freight journeys performed by empty vehicles in 2017, the efficiency of these operations is low and the environmental, economic and social cost high. Sticking to the “business as usual” approach will not be sufficient to cope sustainably with the growing transport demand. Especially when taking into account that the GHG emission of transportation has been increasing every year since 2014 (EEA, 2020). New transport systems must emerge, according to which larger volumes of freight are carried jointly to their destination using the most efficient and sustainable (combination of) modes. In this context synchromodal transportation, or synchromodality, is a promising view on logistics. Synchromodality is a form of multimodal transportation, meaning multiple modalities are used to transport goods from origin to destination, where shippers book mode free and the logistics service provider (LSP) has the freedom to choose and switch modalities based on real-time information. Because the mode and route choice are delayed, and can even been changed, more efficient and sustainable options can be chosen due to better informed decisions (Tavasszy et al., 2018). However, the flexibility to switch mode and route at any point in time leads to certain challenges. In the transport industry, long term contracts between shippers and LSPs are common. These contracts typically contain commitments related to, e.g., volume, lead time and price, and are based on the planned execution of transport services. As these contracts apply over a longer period of time, e.g., a year, commitments need to be made long before the execution of the transport service itself. This long-term decision-making contradicts with the synchromodal idea of having the flexibility to change decisions with respect to route and transport mode in real time (Khakdaman et al., 2020). Therefore, research is needed to determine how these long-term commitments can be made to enable the switch towards synchromodal transportation. Giusti et al. (2019) and Pfoser et al. (2016) identified pricing as a key enabler for synchromodal transportation, but literature on concrete pricing strategies for synchromodal transportation is scare. Traditionally transport prices are mode-based or in other words cost-based. While, the main aim of synchromodal transportation is to provide a service that is no longer dependent on the used transport modes by exploiting their complementary nature. The focus on the service is also present in the literature, revenue (or yield) management (RM) is gaining momentum in the synchromodal literature. RM allows a LSP to create multiple fare classes, each with a related service level. The fare classes are based on customer segments, e.g., some shippers are willing to pay a higher price for a faster service than others. In other words, LSPs can use RM to maximise their revenue by selling different services, at different time periods, to different types of shippers. To optimise a LSP’s revenue when offering synchromodal transport, four sub-problems can be solved: demand forecasting, overbooking, capacity allocation and pricing (Tawfik & Limbourg, 2018). Although pricing is identified as a key enabler and is a key component of RM, to our knowledge, all existing studies with respect to synchromodality focus on one or more of the first three sub-problems (Bilegan et al., 2015; Liu & Yang, 2015; van Riessen et al., 2017, 2020; Wang, 2017). Other studies focus on short term pricing (Guo et al., 2020), or cost-plus pricing (Li et al., 2015) which is hard to implement due to the characteristics of synchromodality. This research aims to identify which pricing strategies are applicable for long-term commitments within a synchromodal context, and this from the LSP’s perspective. Only long-term demand will be considered and LSPs will be able to reserve enough capacity to efficiently meet all long-term demand. However, the long-term commitments, e.g., volume offered, will differ at time of transportation. This leads to re-planning opportunities and, probably, at one point to re-planning problems. In the end, this research answers the question which pricing strategy copes the best with the uncertainties and planning flexibility, while guaranteeing profitability for the LSP.-
dc.language.isoen-
dc.titlePricing strategies for synchromodal transportation-
dc.typeConference Material-
local.bibliographicCitation.conferencedateJanuary 19-23/2022-
local.bibliographicCitation.conferencename19th CEMS Research Seminar 2022 - Supply Chain Management - Recent Trends and Future Perspectives-
local.bibliographicCitation.conferenceplaceRiezlern, Austria-
local.bibliographicCitation.jcatC2-
dc.relation.referencesBilegan, I. C., Brotcorne, L., Feillet, D., & Hayel, Y. (2015). Revenue management for rail container transportation. EURO Journal on Transportation and Logistics, 4(2), 261–283. https://doi.org/10.1007/s13676-014-0051-7 EEA. (2020). Transport: Increasing oil consumption and greenhouse gas emissions hamper EU progress towards environment and climate objectives. European Environment Agency. EEA. (2021). Transport and environmetn report 2020—Train or plane? (No. 19/2020). European Environment Agency. Giusti, R., Manerba, D., Bruno, G., & Tadei, R. (2019). Synchromodal logistics: An overview of critical success factors, enabling technologies, and open research issues. Transportation Research Part E: Logistics and Transportation Review, 129, 92–110. https://doi.org/10.1016/j.tre.2019.07.009 Guo, W., Atasoy, B., van Blokland, W. B., & Negenborn, R. R. (2020). A dynamic shipment matching problem in hinterland synchromodal transportation. Decision Support Systems, 134, 113289. https://doi.org/10.1016/j.dss.2020.113289 Khakdaman, M., Rezaei, J., & Tavasszy, L. A. (2020). Shippers’ willingness to delegate modal control in freight transportation. Transportation Research Part E: Logistics and Transportation Review, 141, 102027. https://doi.org/10.1016/j.tre.2020.102027 Li, L., Negenborn, R. R., & De Schutter, B. (2015). Intermodal freight transport planning – A receding horizon control approach. Transportation Research Part C: Emerging Technologies, 60, 77–95. https://doi.org/10.1016/j.trc.2015.08.002 Liu, D., & Yang, H. (2015). Joint slot allocation and dynamic pricing of container sea–rail multimodal transportation. Journal of Traffic and Transportation Engineering (English Edition), 2(3), 198–208. https://doi.org/10.1016/j.jtte.2015.03.008 Pfoser, S., Treiblmaier, H., & Schauer, O. (2016). Critical Success Factors of Synchromodality: Results from a Case Study and Literature Review. Transportation Research Procedia, 14, 1463–1471. https://doi.org/10.1016/j.trpro.2016.05.220 Tavasszy, L., Behdani, B., & Konings, R. (2018). Intermodality and Synchromodality. In Ports and Networks—Strategies, Operations and Perspectives (pp. 251–266). Tawfik, C., & Limbourg, S. (2018). Pricing Problems in Intermodal Freight Transport: Research Overview and Prospects. Sustainability, 10(9), 3341. https://doi.org/10.3390/su10093341 van Riessen, B., Mulder, J., Negenborn, R. R., & Dekker, R. (2020). Revenue management with two fare classes in synchromodal container transportation. Flexible Services and Manufacturing Journal. https://doi.org/10.1007/s10696-020-09394-4 van Riessen, B., Negenborn, R. R., & Dekker, R. (2017). The Cargo Fare Class Mix problem for an intermodal corridor: Revenue management in synchromodal container transportation. Flexible Services and Manufacturing Journal, 29(3), 634–658. https://doi.org/10.1007/s10696-017-9285-7 Wang, Y. (2017). A reactive decision support system for intermodal freight transportation [Phdthesis, Université de Valenciennes et du Hainaut-Cambresis]. https://tel.archives-ouvertes.fr/tel-01722143-
local.type.specifiedConference Material - Abstract-
local.uhasselt.internationalno-
item.fullcitationPAESEN, Jasper; CARIS, An; VERDONCK, Lotte & DEFRYN, Christof (2022) Pricing strategies for synchromodal transportation. In: 19th CEMS Research Seminar 2022 - Supply Chain Management - Recent Trends and Future Perspectives, Riezlern, Austria, January 19-23/2022.-
item.fulltextNo Fulltext-
item.contributorPAESEN, Jasper-
item.contributorCARIS, An-
item.contributorVERDONCK, Lotte-
item.contributorDEFRYN, Christof-
item.accessRightsClosed Access-
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