Current state of environmental awareness of transport service stakeholders and end-customers in the intermodal transport chain
Abstract
Despite all the measures already taken and those still underway, pollution remains a major global problem, as the transport sector is the one where emissions are expected to increase in the coming years. Companies and policy makers are under increasing pressure to reduce the impact of their logistics activities in order to make transportation more environmentally friendly. One of the solutions to reduce emissions from intermodal transport is to choose the “right” mode of transport for each step in the transport chain. Such a measure increases the complexity of the transport chain and places an additional burden on transport companies in planning and organising transport for the entire transport chain. Additional difficulties arise from the fragmentation of information on emissions emitted for a single transport link and the lack of a unified approach to measuring and estimating transport chain emissions. As a result, this work finds that there is a lack of knowledge among users about the environmental impacts of transportation, despite the desire to contribute to greener transportation by paying more for a product or transportation service. The current research fills the gap in stakeholders’ understanding of the negative environmental impacts for individual transportation and for the entire transport chain. In addition, the study reveals a need for a systematically regulated and adapted way of informing users of intermodal transport chains due to the lack of transparency and comparison between different intermodal transport chains. To successfully address the challenges, the study proposes a 2-pillar approach. The 1st pillar approach focuses on designing a set of necessary measures (combination of top-down and bottom-up approach) for the transition to a low-carbon transport chain, while the 2nd pillar mainly focuses on mapping the level of green transport for easy comparison of similar products or services. The results of the research study show that the combination of numerical data with symbolic data is best suited to provide information on the level of green transport.
Keyword : green transport, intermodal transport, decarbonisation, green supply chain, minimisation, transport emissions, bottom-up approach, commercial evaluation
How to Cite
Golnar, M., & Beškovnik, B. (2024). Current state of environmental awareness of transport service stakeholders and end-customers in the intermodal transport chain. Transport, 39(1), 1–12. https://doi.org/10.3846/transport.2024.20540
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Carvalho, H.; Govindan, K.; Azevedo, S. G.; Cruz-Machado, V. 2017. Modelling green and lean supply chains: an eco-efficiency perspective, Resources, Conservation and Recycling 120: 75–87. https://doi.org/10.1016/j.resconrec.2016.09.025
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Gong, M.; Gao, Y.; Koh, L.; Sutcliffe, C.; Cullen, J. 2019. The role of customer awareness in promoting firm sustainability and sustainable supply chain management, International Journal of Production Economics 217: 88–96. https://doi.org/10.1016/j.ijpe.2019.01.033
Hrušovský, M.; Demir, E.; Jammernegg, W.; Van Woensel, T. 2018. Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty, Flexible Services and Manufacturing Journal 30(3): 486–516. https://doi.org/10.1007/s10696-016-9267-1
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ISO 9001:2015/Amd 1:2024. Quality Management Systems. Requirements. Amendment 1: Climate Action Changes.
ISO 14001:2015. Environmental Management Systems. Requirements with Guidance for Use.
ISO 22000:2018/Amd 1:2024. Food Safety Management Systems. Requirements for Any Organization in the Food Chain. Amendment 1: Climate Action Changes.
ISO/IEC 27001:2022/Amd 1:2024. Information Security, Cybersecurity and Privacy Protection. Information Security Management Systems. Requirements. Amendment 1: Climate Action Changes.
ISO/TS 16949:2009. Quality Management Systems.
Jazairy, A.; Von Haartman, R. 2021. Measuring the gaps between shippers and logistics service providers on green logistics throughout the logistics purchasing process, International Journal of Physical Distribution & Logistics Management 51(1): 25–47. https://doi.org/10.1108/IJPDLM-08-2019-0237
Johnson, H.; Styhre, L. 2015. Increased energy efficiency in short sea shipping through decreased time in port, Transportation Research Part A: Policy and Practice 71: 167–178. https://doi.org/10.1016/j.tra.2014.11.008
Liotta, G.; Stecca, G.; Kaihara, T. 2015. Optimisation of freight flows and sourcing in sustainable production and transportation networks, International Journal of Production Economics 164: 351–365. https://doi.org/10.1016/j.ijpe.2014.12.016
Lister, J.; Poulsen, R. T.; Ponte, S. 2015. Orchestrating transnational environmental governance in maritime shipping, Global Environmental Change 34: 185–195. https://doi.org/10.1016/j.gloenvcha.2015.06.011
McKinnon, A. 2014. The possible influence of the shipper on carbon emissions from deep-sea container supply chains: an empirical analysis, Maritime Economics & Logistics 16(1): 1–19. https://doi.org/10.1057/mel.2013.25
Moon, D. S.-H.; Woo, J. K. 2014. The impact of port operations on efficient ship operation from both economic and environmental perspectives, Maritime Policy & Management: the Flagship Journal of International Shipping and Port Research 41(5): 444–461. https://doi.org/10.1080/03088839.2014.931607
Muñoz-Torres, M. J.; Fernández-Izquierdo, M. Á.; Rivera-Lirio, J. M.; Ferrero-Ferrero, I.; Escrig-Olmedo, E. 2021. Sustainable supply chain management in a global context: a consistency analysis in the textile industry between environmental management practices at company level and sectoral and global environmental challenges, Environment, Development and Sustainability 23(3): 3883–3916. https://doi.org/10.1007/s10668-020-00748-4
OHSAS 18001:2007. Health and Safety Management System.
Peng, Y.; Li, X.; Wang, W.; Liu, K.; Li, C. 2018. A simulation-based research on carbon emission mitigation strategies for green container terminals, Ocean Engineering 163: 288–298. https://doi.org/10.1016/j.oceaneng.2018.05.054
Persdotter Isaksson, M.; Hulthén, H.; Forslund, H. 2019. Environmentally sustainable logistics performance management process integration between buyers and 3PLs, Sustainability 11(11): 3061. https://doi.org/10.3390/su11113061
Poulsen, R. T.; Ponte, S.; Lister, J. 2016. Buyer-driven greening? Cargo-owners and environmental upgrading in maritime shipping, Geoforum 68: 57–68. https://doi.org/10.1016/j.geoforum.2015.11.018
Poulsen, R. T.; Sornn-Friese, H. 2015. Achieving energy efficient ship operations under third party management: How do ship management models influence energy efficiency?, Research in Transportation Business & Management 17: 41–52. https://doi.org/10.1016/j.rtbm.2015.10.001
Rahim, M. M.; Islam, M. T.; Kuruppu, S. 2016. Regulating global shipping corporations’ accountability for reducing greenhouse gas emissions in the seas, Marine Policy 69: 159–170. https://doi.org/10.1016/j.marpol.2016.04.018
Saeedi, H.; Behdani, B.; Wiegmans, B.; Zuidwijk, R. 2019. Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach, Transportation Research Part E: Logistics and Transportation Review 126: 66–86. https://doi.org/10.1016/j.tre.2019.04.003
Sun, H.; Yang, J. 2021. Optimal decisions for competitive manufacturers under carbon tax and cap-and-trade policies, Computers & Industrial Engineering 156: 107244. https://doi.org/10.1016/j.cie.2021.107244
Sun, Y.; Lang, M.; Wang, D. 2015. Optimization models and solution algorithms for freight routing planning problem in the multi-modal transportation networks: a review of the state-of-the-art, The Open Civil Engineering Journal 9: 714–723. https://doi.org/10.2174/1874149501509010714
Toro, E. M.; Franco, J. F.; Echeverri, M. G.; Guimarães, F. G.; Gallego Rendón, R. A. 2017. Green open location-routing problem considering economic and environmental costs, International Journal of Industrial Engineering Computations 8(2): 203–216. https://doi.org/10.5267/j.ijiec.2016.10.001
UNFCCC. 2012. Doha Amendment to the Kyoto Protocol to the United Nations Framework Convention on Climate Change. United Nations Framework Convention on Climate Change Secretariat. 6 p. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/files/kyoto_protocol/doha_amendment/application/pdf/attachment_sg_letter_doha_amendment.pdf
UNFCCC. 2009. Information provided by Parties to the Convention relating to the Copenhagen Accord. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/process/conferences/pastconferences/copenhagen-climate-change-conference-december-2009/statements-and-resources/information-provided-by-parties-to-the-convention-relating-to-the-copenhagen-accord
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UNFCCC. 2015. The Paris Agreement. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/process-and-meetings/the-paris-agreement
Vukić, L.; Poletan Jugović, T.; Guidi, G.; Oblak, R. 2020. Model of determining the optimal, green transport route among alternatives: data envelopment analysis settings, Journal of Marine Science and Engineering 8(10): 735. https://doi.org/10.3390/jmse8100735
Wan, J.; Wei, S. 2019. Multi-objective multimodal transportation path selection based on hybrid algorithm, Journal of Tianjin University (Science and Technology) (3): 285–292. (in Chinese).
Yang, Y.-C. 2017. Operating strategies of CO2 reduction for a container terminal based on carbon footprint perspective, Journal of Cleaner Production 141: 472–480. https://doi.org/10.1016/j.jclepro.2016.09.132
Zhang, G.; Cheng, P.; Sun, H.; Shi, Y.; Zhang, G.; Kadiane, A. 2021. Carbon reduction decisions under progressive carbon tax regulations: A new dual-channel supply chain network equilibrium model, Sustainable Production and Consumption 27: 1077–1092. https://doi.org/10.1016/j.spc.2021.02.029
Zhang, H.; Yang, K. 2020. Multi-objective optimization for green dual-channel supply chain network design considering transportation mode selection, in Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications, 382–404. https://doi.org/10.4018/978-1-7998-0945-6.ch019
Alberini, A.; Bigano, A.; Ščasný, M.; Zvěřinová, I. 2018. Preferences for energy efficiency vs. renewables: what is the willingness to pay to reduce CO2 emissions?, Ecological Economics 144: 171–185. https://doi.org/10.1016/j.ecolecon.2017.08.009
Barzinpour, F.; Taki, P. 2018. A dual-channel network design model in a green supply chain considering pricing and transportation mode choice, Journal of Intelligent Manufacturing 29(7): 1465–1483. https://doi.org/10.1007/s10845-015-1190-x
Bask, A.; Rajahonka, M.; Laari, S.; Solakivi, T.; Töyli, J.; Ojala, L. 2018. Environmental sustainability in shipper-LSP relationships, Journal of Cleaner Production 172: 2986–2998. https://doi.org/10.1016/j.jclepro.2017.11.112
Baykasoğlu, A.; Subulan, K. 2016. A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application, Transportation Research Part E: Logistics and Transportation Review 95: 207–247. https://doi.org/10.1016/j.tre.2016.09.011
Bemporad, R.; Baranowski, M. 2007. Conscious Consumers Are Changing the Rules of Marketing. Are You Ready? Highlights from the BBMG Conscious Consumer Report. Bemporad Baranowski Marketing Group (BBMG). 6 p. Available from Internet: https://www.fmi.org/docs/sustainability/BBMG_Conscious_Consumer_White_Paper.pdf
Beškovnik, B.; Golnar, M. 2020. Evaluating the environmental impact of complex intermodal transport chains, Environmental Engineering and Management Journal 19(7): 1131–1141. https://doi.org/10.30638/eemj.2020.107
Björklund, M.; Forslund, H. 2019. Challenges addressed by Swedish third-party logistics providers conducting sustainable logistics business cases, Sustainability 11(9): 2654. https://doi.org/10.3390/su11092654
Bosona, T.; Gebresenbet, G.; Nordmark, I.; Ljungberg, D. 2011. Integrated logistics network for the supply chain of locally produced food, part I: location and route optimization analyses, Journal of Service Science and Management 4(2): 174–183. https://doi.org/10.4236/jssm.2011.42021
Caris, A.; Macharis, C.; Janssens, G. K. 2008. Planning problems in intermodal freight transport: accomplishments and prospects, Transportation Planning and Technology 31(3): 277–302. https://doi.org/10.1080/03081060802086397
Carvalho, H.; Govindan, K.; Azevedo, S. G.; Cruz-Machado, V. 2017. Modelling green and lean supply chains: an eco-efficiency perspective, Resources, Conservation and Recycling 120: 75–87. https://doi.org/10.1016/j.resconrec.2016.09.025
Cho, J. H.; Kim, H. S.; Choi, H. R. 2012. An intermodal transport network planning algorithm using dynamic programming – a case study: from Busan to Rotterdam in intermodal freight routing, Applied Intelligence 36(3): 529–541. https://doi.org/10.1007/s10489-010-0223-6
Darvish, M.; Archetti, C.; Coelho, L. C. 2019. Trade-offs between environmental and economic performance in production and inventory-routing problems, International Journal of Production Economics 217: 269–280. https://doi.org/10.1016/j.ijpe.2018.08.020
Dutta, J.; Barma, P. S.; Mukherjee, A.; Kar, S.; De, T.; Pamučar, D.; Šukevičius, Š.; Garbinčius, G. 2022. Multi-objective green mixed vehicle routing problem under rough environment, Transport 37(1): 51–63. https://doi.org/10.3846/transport.2021.14464
Gibbs, D.; Rigot-Muller, P.; Mangan, J.; Lalwani, C. 2014. The role of sea ports in end-to-end maritime transport chain emissions, Energy Policy 64: 337–348. https://doi.org/10.1016/j.enpol.2013.09.024
Gong, M.; Gao, Y.; Koh, L.; Sutcliffe, C.; Cullen, J. 2019. The role of customer awareness in promoting firm sustainability and sustainable supply chain management, International Journal of Production Economics 217: 88–96. https://doi.org/10.1016/j.ijpe.2019.01.033
Hrušovský, M.; Demir, E.; Jammernegg, W.; Van Woensel, T. 2018. Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty, Flexible Services and Manufacturing Journal 30(3): 486–516. https://doi.org/10.1007/s10696-016-9267-1
Hulshof, D.; Mulder, M. 2020. Willingness to pay for CO2 emission reductions in passenger car transport, Environmental and Resource Economics 75(4): 899–929. https://doi.org/10.1007/s10640-020-00411-6
ISO 9001:2015/Amd 1:2024. Quality Management Systems. Requirements. Amendment 1: Climate Action Changes.
ISO 14001:2015. Environmental Management Systems. Requirements with Guidance for Use.
ISO 22000:2018/Amd 1:2024. Food Safety Management Systems. Requirements for Any Organization in the Food Chain. Amendment 1: Climate Action Changes.
ISO/IEC 27001:2022/Amd 1:2024. Information Security, Cybersecurity and Privacy Protection. Information Security Management Systems. Requirements. Amendment 1: Climate Action Changes.
ISO/TS 16949:2009. Quality Management Systems.
Jazairy, A.; Von Haartman, R. 2021. Measuring the gaps between shippers and logistics service providers on green logistics throughout the logistics purchasing process, International Journal of Physical Distribution & Logistics Management 51(1): 25–47. https://doi.org/10.1108/IJPDLM-08-2019-0237
Johnson, H.; Styhre, L. 2015. Increased energy efficiency in short sea shipping through decreased time in port, Transportation Research Part A: Policy and Practice 71: 167–178. https://doi.org/10.1016/j.tra.2014.11.008
Liotta, G.; Stecca, G.; Kaihara, T. 2015. Optimisation of freight flows and sourcing in sustainable production and transportation networks, International Journal of Production Economics 164: 351–365. https://doi.org/10.1016/j.ijpe.2014.12.016
Lister, J.; Poulsen, R. T.; Ponte, S. 2015. Orchestrating transnational environmental governance in maritime shipping, Global Environmental Change 34: 185–195. https://doi.org/10.1016/j.gloenvcha.2015.06.011
McKinnon, A. 2014. The possible influence of the shipper on carbon emissions from deep-sea container supply chains: an empirical analysis, Maritime Economics & Logistics 16(1): 1–19. https://doi.org/10.1057/mel.2013.25
Moon, D. S.-H.; Woo, J. K. 2014. The impact of port operations on efficient ship operation from both economic and environmental perspectives, Maritime Policy & Management: the Flagship Journal of International Shipping and Port Research 41(5): 444–461. https://doi.org/10.1080/03088839.2014.931607
Muñoz-Torres, M. J.; Fernández-Izquierdo, M. Á.; Rivera-Lirio, J. M.; Ferrero-Ferrero, I.; Escrig-Olmedo, E. 2021. Sustainable supply chain management in a global context: a consistency analysis in the textile industry between environmental management practices at company level and sectoral and global environmental challenges, Environment, Development and Sustainability 23(3): 3883–3916. https://doi.org/10.1007/s10668-020-00748-4
OHSAS 18001:2007. Health and Safety Management System.
Peng, Y.; Li, X.; Wang, W.; Liu, K.; Li, C. 2018. A simulation-based research on carbon emission mitigation strategies for green container terminals, Ocean Engineering 163: 288–298. https://doi.org/10.1016/j.oceaneng.2018.05.054
Persdotter Isaksson, M.; Hulthén, H.; Forslund, H. 2019. Environmentally sustainable logistics performance management process integration between buyers and 3PLs, Sustainability 11(11): 3061. https://doi.org/10.3390/su11113061
Poulsen, R. T.; Ponte, S.; Lister, J. 2016. Buyer-driven greening? Cargo-owners and environmental upgrading in maritime shipping, Geoforum 68: 57–68. https://doi.org/10.1016/j.geoforum.2015.11.018
Poulsen, R. T.; Sornn-Friese, H. 2015. Achieving energy efficient ship operations under third party management: How do ship management models influence energy efficiency?, Research in Transportation Business & Management 17: 41–52. https://doi.org/10.1016/j.rtbm.2015.10.001
Rahim, M. M.; Islam, M. T.; Kuruppu, S. 2016. Regulating global shipping corporations’ accountability for reducing greenhouse gas emissions in the seas, Marine Policy 69: 159–170. https://doi.org/10.1016/j.marpol.2016.04.018
Saeedi, H.; Behdani, B.; Wiegmans, B.; Zuidwijk, R. 2019. Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach, Transportation Research Part E: Logistics and Transportation Review 126: 66–86. https://doi.org/10.1016/j.tre.2019.04.003
Sun, H.; Yang, J. 2021. Optimal decisions for competitive manufacturers under carbon tax and cap-and-trade policies, Computers & Industrial Engineering 156: 107244. https://doi.org/10.1016/j.cie.2021.107244
Sun, Y.; Lang, M.; Wang, D. 2015. Optimization models and solution algorithms for freight routing planning problem in the multi-modal transportation networks: a review of the state-of-the-art, The Open Civil Engineering Journal 9: 714–723. https://doi.org/10.2174/1874149501509010714
Toro, E. M.; Franco, J. F.; Echeverri, M. G.; Guimarães, F. G.; Gallego Rendón, R. A. 2017. Green open location-routing problem considering economic and environmental costs, International Journal of Industrial Engineering Computations 8(2): 203–216. https://doi.org/10.5267/j.ijiec.2016.10.001
UNFCCC. 2012. Doha Amendment to the Kyoto Protocol to the United Nations Framework Convention on Climate Change. United Nations Framework Convention on Climate Change Secretariat. 6 p. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/files/kyoto_protocol/doha_amendment/application/pdf/attachment_sg_letter_doha_amendment.pdf
UNFCCC. 2009. Information provided by Parties to the Convention relating to the Copenhagen Accord. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/process/conferences/pastconferences/copenhagen-climate-change-conference-december-2009/statements-and-resources/information-provided-by-parties-to-the-convention-relating-to-the-copenhagen-accord
UNFCCC. 1998. Kyoto Protocol to the United Nations Framework Convention on Climate Change. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). 21 p. Available from Internet: https://unfccc.int/resource/docs/convkp/kpeng.pdf
UNFCCC. 2015. The Paris Agreement. United Nations Framework Convention on Climate Change Secretariat (UNFCCC). Available from Internet: https://unfccc.int/process-and-meetings/the-paris-agreement
Vukić, L.; Poletan Jugović, T.; Guidi, G.; Oblak, R. 2020. Model of determining the optimal, green transport route among alternatives: data envelopment analysis settings, Journal of Marine Science and Engineering 8(10): 735. https://doi.org/10.3390/jmse8100735
Wan, J.; Wei, S. 2019. Multi-objective multimodal transportation path selection based on hybrid algorithm, Journal of Tianjin University (Science and Technology) (3): 285–292. (in Chinese).
Yang, Y.-C. 2017. Operating strategies of CO2 reduction for a container terminal based on carbon footprint perspective, Journal of Cleaner Production 141: 472–480. https://doi.org/10.1016/j.jclepro.2016.09.132
Zhang, G.; Cheng, P.; Sun, H.; Shi, Y.; Zhang, G.; Kadiane, A. 2021. Carbon reduction decisions under progressive carbon tax regulations: A new dual-channel supply chain network equilibrium model, Sustainable Production and Consumption 27: 1077–1092. https://doi.org/10.1016/j.spc.2021.02.029
Zhang, H.; Yang, K. 2020. Multi-objective optimization for green dual-channel supply chain network design considering transportation mode selection, in Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications, 382–404. https://doi.org/10.4018/978-1-7998-0945-6.ch019