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A framework for the taxonomy and assessment of new and emerging transport technologies and trends

Abstract

This paper focuses on the development of a taxonomy framework for new and emerging technologies and trends in the transport sector. This framework is proposed towards the assessment and monitoring of the acceptance, impact and diffusion of technologies and trends, together with a scoring system and a front–end visualisation of the outcomes. In this context, an overview of the transport technology hype over the last years and the establishment of future transport technologies and trends is provided. Issues arising from different constraints, including technological and technical, are taken into account, also considering the transport sector’s interconnection with other sectors and potentially related bottlenecks and drawbacks. The paper outcome is a methodological framework for the creation of different taxonomies for new and emerging transport technologies and trends, achieved through the quantitative assessment of the attractiveness and competitiveness, in terms of diffusion potential, of emerging transport technologies and trends, by associating explicit indices to the various elements of the taxonomies. The proposed taxonomy, assessment and monitoring framework supports innovation management through the identification and evaluation of new and emerging technologies and trends in the field of transport at various levels, thus providing insights to the sector’s stakeholders, while backing the current transport systems’ transformation through technological advances.


First published online 10 May 2019

Keyword : transport sector, technological innovation, taxonomy, new emerging technologies, technology hype, disruptive innovation, knowledge management

How to Cite
Gkoumas, K., & Tsakalidis, A. (2019). A framework for the taxonomy and assessment of new and emerging transport technologies and trends. Transport, 34(4), 455-466. https://doi.org/10.3846/transport.2019.9318
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Sep 12, 2019
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References

Ahmed, E.; Yaqoob, I.; Hashem, I. A. T.; Khan, I.; Ahmed, A. I. A.; Imran, M.; Vasilakos, A. V. 2017. The role of big data analytics in internet of things, Computer Networks 129: 459–471. https://doi.org/10.1016/J.COMNET.2017.06.013

Ajzen, I. 1991. The theory of planned behavior, Organizational Behavior and Human Decision Processes 50(2): 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Ajzen, I. 1985. From intentions to actions: a theory of planned behavior, in J. Kuhl, J. Beckmann (Eds.). Action Control, 11–39. https://doi.org/10.1007/978-3-642-69746-3_2

Arbib, J.; Seba, T. 2017. Rethinking Transportation 2020–2030: The Disruption of Transportation and the Collapse of the Internal-Combustion Vehicle and Oil Industries. RethinkX. 162 p.

Auvinen, H.; Tuominen, A. 2014. Future transport systems: longterm visions and socio-technical transitions, European Transport Research Review 6(3): 343–354. https://doi.org/10.1007/s12544-014-0135-3

Axsen, J.; Kurani, K. S. 2012. Interpersonal influence within car buyers’ social networks: applying five perspectives to plug-in hybrid vehicle drivers, Environment and Planning A: Economy and Space 44(5): 1047–1065. https://doi.org/10.1068/a43221x

Bailey, K. D. 1994. Typologies and Taxonomies: An Introduction to Classification Techniques. SAGE Publications. 96 p.

Bąk, M.; Borkowski, P. 2015. Applicability of ICT solutions in passenger transport – case studies from different European backgrounds, Transport 30(3): 372–381. https://doi.org/10.3846/16484142.2015.1079552

Bakker, S. 2010. The car industry and the blow-out of the hydrogen hype, Energy Policy 38(11): 6540–6544. https://doi.org/10.1016/j.enpol.2010.07.019

Campani, M.; Vaglio, R. 2015. A simple interpretation of the growth of scientific/technological research impact leading to hype-type evolution curves, Scientometrics 103(1): 75–83. https://doi.org/10.1007/s11192-015-1533-6

Cascetta, E. 2001. Transportation Systems Engineering: Theory and Methods. Springer. 710 p. https://doi.org/10.1007/978-1-4757-6873-2

Crainic, T. G.; Perboli, G.; Rosano, M. 2018. Simulation of intermodal freight transportation systems: a taxonomy, European Journal of Operational Research 270(2): 401–418. https://doi.org/10.1016/J.EJOR.2017.11.061

De Rose, A.; Buna, M.; Strazza, C.; Olivieri, N.; Stevens, T.; Peeters, L.; Tawil-Jamault, D. 2017. Technology Readiness Level Guidance Principles for Renewable Energy Technologies: Final Report. Luxembourg: Publications Office of the European Union. 51 p. https://doi.org/10.2777/577767

Dedehayir, O.; Steinert, M. 2016. The hype cycle model: a review and future directions, Technological Forecasting and Social Change 108: 28–41. https://doi.org/10.1016/J.TECHFORE.2016.04.005

EC. 2017a. TRIMIS: Transport Research and Innovation Monitoring and Information System. European Commission (EC). Available from Internet: https://trimis.ec.europa.eu

EC. 2017b. Research & Innovation: Research and Innovation Observatory – Horizon 2020 Policy Support Facility. European Commission (EC). Available from Internet: https://rio.jrc.ec.europa.eu

EC. 2017c. Mobility and Transport: EU Transport Scoreboard. European Commission (EC). Available from Internet: https://ec.europa.eu/transport/facts-fundings/scoreboard_en

EC. 2017d. SETIS: Strategic Energy Technologies Information System. European Commission (EC). Available from Internet: https://setis.ec.europa.eu

EC. 2017e. Europe on the Move: An Agenda for a Socially Fair Transition Towards Clean, Competitive and Connected Mobility for All. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions COM/2017/0283 Final. European Commission (EC). 18 p. Available from Internet: https://eur-lex.europa.eu/legal-con-tent/EN/TXT/PDF/?uri=CELEX:52017DC0283&from=EN

EC. 2016a. Economics of Industrial Research and Innovation. Joint Research Centre (JRC), European Commission (EC). Available from Internet: http://iri.jrc.ec.europa.eu

EC. 2016b. Tools for Innovation Monitoring. Joint Research Centre (JRC), European Commission (EC). Available from Internet: http://www.timanalytics.eu

EC. 2016c. Innovation Union: Aims of the Innovation Union, State of Progress and Related Policy. European Commission (EC). Available from Internet: https://ec.europa.eu/info/research-and-innovation/strategy/goals-research-and-innovation-policy/innovation-union_en

EC. 2016d. The Implementation of the 2011 White Paper on Transport “Roadmap to a Single European Transport Area – Towards a Competitive and Resource-Efficient Transport System” Five Years After its Publication: Achievements and Challenges. Commission Staff Working Document SWD(2016)226/F1. European Commission (EC). 55 p. Available from Internet: http://ec.europa.eu/transparency/regdoc/rep/10102/2016/EN/10102-2016-226-EN-F1-1.PDF

EC. 2015. Towards an Integrated Strategic Energy Technology (SET) Plan: Accelerating the European Energy System Transformation. Communication from the Commission C(2015)6317/F1. European Commission (EC). 17 p. Available from Internet: https://setis.ec.europa.eu/system/files/Communication_SET-Plan_15_Sept_2015.pdf

Fenn, J.; Raskino, M.; Burton, B. 2013. Understanding Gartner’s Hype Cycles. G00251964. Gartner Inc. 35 p. Available from Internet: https://www.gartner.com/doc/2538815/understanding-gartners-hype-cycles

Fuest, T.; Sorokin, L.; Bellem, H.; Bengler, K. 2018. Taxonomy of traffic situations for the interaction between automated vehicles and human road users, Advances in Intelligent Systems and Computing 597: 708–719. https://doi.org/10.1007/978-3-319-60441-1_68

Gartner Inc. 2018. Gartner Hype Cycle. Available from Internet: https://www.gartner.com/en/research/methodologies/gartner-hype-cycle

Gotthelf, A.; Lennox, J. G. (Eds.). 1987. Philosophical Issues in Aristotle’s Biology. Cambridge University Press. 462 p. https://doi.org/10.1017/CBO9780511552564

Grübler, A. 1998. Technology and Global Change. Cambridge University Press. 452 p. https://doi.org/10.1017/CBO9781316036471

Haimes, Y. Y. 2008. Models for risk management of systems of systems, International Journal of System of Systems Engineering 1(1–2): 222–236. https://doi.org/10.1504/IJSSE.2008.018138

Heiskanen, E.; Hyvönen, K.; Niva, M.; Pantzar, M.; Timonen, P.; Varjonen, J. 2007. User involvement in radical innovation: are consumers conservative?, European Journal of Innovation Management 10(4): 489–509. https://doi.org/10.1108/14601060710828790

INTEND. 2018. D2.1: Transport Projects & Future Technologies Synopses Handbook. INtentify future Transport rEsearch NeeDs (INTEND) Project. 282 p. Available from Internet: https://intend-project.eu/wp-content/uploads/2018/05/intend-d-2.1-transport-projects-future-technologies-synopses-handbook.pdf

Jun, S.-P. 2012. An empirical study of users’ hype cycle based on search traffic: the case study on hybrid cars, Scientometrics 91(1): 81–99. https://doi.org/10.1007/s11192-011-0550-3

Kashyap, V.; Ramakrishnan, C.; Thomas, C.; Sheth, A. 2005. TaxaMiner: an experimentation framework for automated taxonomy bootstrapping, International Journal of Web and Grid Services 1(2): 240–266. https://doi.org/10.1504/IJWGS.2005.008322

Katsumi, M.; Fox, M. 2018. Ontologies for transportation research: a survey, Transportation Research Part C: Emerging Technologies 89: 53–82. https://doi.org/10.1016/j.trc.2018.01.023

Kemper, S. 2003. Code Name Ginger: The Story behind Segway and Dean Kamen’s Quest to Invent a New World. Harvard Business Review Press. 336 p.

Koh, H.; Magee, C. L. 2006. A functional approach for studying technological progress: application to information technology, Technological Forecasting and Social Change 73(9): 1061–1083. https://doi.org/10.1016/j.techfore.2006.06.001

Letunic, I.; Bork, P. 2016. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees, Nucleic Acids Research 44(W1): W242–W245. https://doi.org/10.1093/nar/gkw290

Linnaeus, C. 1758. Systema naturae per regna tria naturae: secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Holmiae: Laurentii Salvii. 824 p. https://doi.org/10.5962/bhl.title.542 (in Latine).

Mai, T. 2012. Technology Readiness Level. Available from Internet: https://www.nasa.gov/directorates/heo/scan/engineering/technology/txt_accordion1.html

Mayr, E. 1981. Biological classification: toward a synthesis of opposing methodologies, Science 214: 510–516. https://doi.org/10.1126/science.214.4520.510

Mazzarino, M. 2012. Strategic scenarios of global logistics: what lies ahead for Europe?, European Transport Research Review 4(1): 1–18. https://doi.org/10.1007/s12544-011-0069-y

Moro, A.; Aycart, J.; Bardizza, G.; Bielewski, M.; Lopez-Garcia, J.; Taylor, N. 2017. First Workshop on Identification of Future Emerging Technologies for Low Carbon Energy Supply. 1 December 2016, Ispra, Italy. Luxembourg: Publications Office of the European Union. 56 p. https://doi.org/10.2760/644289

National Academy of Sciences. 2017. TRID: Transport Research International Documentation. National Academy of Sciences, Washington, DC, US. Available from Internet: https://trid.trb.org

Navas, H. V. G.; Cruz-Machado, V. A. 2015. “The lifeline” of technical systems in a TRIZ-LEAN environment, Procedia Engineering 131: 232–236. https://doi.org/10.1016/J.PROENG.2015.12.383

O’Hara, R. J. 1988. Homage to Clio, or, toward an historical philosophy for evolutionary biology, Systematic Biology 37(2): 142–155. https://doi.org/10.2307/2992272

OECD. 2016. OECD Science, Technology and Innovation Outlook 2016. Organisation for Economic Cooperation and Development (OECD). https://doi.org/10.1787/sti_in_outlook-2016-en

Padian, K. 1999. Charles Darwin’s views of classification in theory and practice, Systematic Biology 48(2): 352–364. https://doi.org/10.1080/106351599260337

Psaraftis, H. N.; Kontovas, C. A. 2013. Speed models for energy-efficient maritime transportation: A taxonomy and survey, Transportation Research Part C: Emerging Technologies 26: 331–351. https://doi.org/10.1016/J.TRC.2012.09.012

REFINET. 2017. D3.3: Catalogue of Technologies for Multimodal Transport Infrastructures. REthinking Future Infrastructure NETworks (REFINET) Project. 147 p. Available from Internet: http://infrastructure.ectp.org/fileadmin/user_upload/documents/REFINET/Deliverables/REFINET_D3.3_Cata-logue-Technologies_MMTI_v3.pdf

Rogers, E. M. 2003. Diffusion of Innovations. Free Press. 576 p.

Rusitschka, S.; Curry, E. 2016. Big data in the energy and transport sectors, in: J. Cavanillas, E. Curry, W. Wahlster (Eds.). New Horizons for a Data-Driven Economy, 225–244. https://doi.org/10.1007/978-3-319-21569-3_13

SAE. 2014. Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. SAE Standard J3016_201609. Society of Automotive Engineers (SAE) International. https://doi.org/10.4271/J3016_201609

Sauser, B.; Verma, D.; Ramirez-Marquez, J.; Gove, R. 2006. From TRL to SRL: the concept of systems readiness levels, in Conference on Systems Engineering Research, 7–8 April 2006, Los Angeles, CA, US, 1–10.

Schröder-Hinrichs, J.-U.; Hollnagel, E.; Baldauf, M.; Hofmann, S.; Kataria, A. 2013. Maritime human factors and IMO policy, Maritime Policy & Management: the Flagship Journal of International Shipping and Port Research 40(3): 243–260. https://doi.org/10.1080/03088839.2013.782974

Sgambi, L.; Gkoumas, K.; Bontempi, F. 2012. Genetic algorithms for the dependability assurance in the design of a long‐span suspension bridge, Computer‐Aided Civil and Infrastructure Engineering 27(9): 655–675. https://doi.org/10.1111/j.1467-8667.2012.00780.x

Shaukat, N.; Khan, B.; Ali, S. M.; Mehmood, C. A.; Khan, J.; Farid, U.; Majid, M.; Anwar, S. M.; Jawad, M.; Ullah, Z. 2018. A survey on electric vehicle transportation within smart grid system, Renewable and Sustainable Energy Reviews 81: 1329–1349. https://doi.org/10.1016/J.RSER.2017.05.092

Shemshadi, A.; Sheng, Q. Z.; Qin, Y.; Sun, A.; Zhang, W. E.; Yao, L. 2017. Searching for the internet of things: where it is and what it looks like, Personal and Ubiquitous Computing 21(6): 1097–1112. https://doi.org/10.1007/s00779-017-1034-0

Shorrock, S. T.; Kirwan, B. 2002. Development and application of a human error identification tool for air traffic control, Applied Ergonomics 33(4): 319–336. https://doi.org/10.1016/S0003-6870(02)00010-8

Simon, H. A. 1962. The architecture of complexity, Proceedings of the American Philosophical Society 106(6): 467–482.

Smiraglia, R. P. 2014. The Elements of Knowledge Organization. Springer. 101 p. https://doi.org/10.1007/978-3-319-09357-4

Stanton, N. A.; Salmon, P. M. 2009. Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems, Safety Science 47(2): 227–237. https://doi.org/10.1016/J.SSCI.2008.03.006

Sussman, J. M.; Dodder, R. S.; McConnel, J. B.; Mostashari, A.; Sgouridis, S. 2009. The “CLIOS Process”: a User’s Guide. Massachusetts Institute of Technology. 42 p. Available from Internet: http://web.mit.edu/hsr-group/documents/clios.pdf

Tsakalidis, A.; Gkoumas, K.; Pekar, F.; Grosso, M.; Haq, G.; Marelli, L. 2018a. Towards an integrated European platform for monitoring and analysing transport research and innovation (TRIMIS), in Proceedings of 7th Transport Research Arena TRA 2018, 16–19 April 2018, Vienna, Austria, 1–10. https://doi.org/10.5281/zenodo.1473539

Tsakalidis, A.; Gkoumas, K.; Pekar, F.; Grosso, M.; Haq, G.; Marelli, L. 2018b. EU Transport Research & Innovation Status Assessment Report 2017: an Overview Based on the Transport Research and Innovation Monitoring and Information System (TRIMIS) Database. Luxembourg: Publications Office of the European Union. 66 p. https://doi.org/10.2760/331714

US DoT. 2012. Taxonomy of Intelligent Transportation Systems Applications. US Department of Transportation (US DoT), Washington, DC, US. Available from Internet: https://www.itsbenefits.its.dot.gov/its/benecost.nsf/images/Reports/$File/Taxonomy.pdf

Venkatesh, V.; Morris, M. G.; Davis, G. B.; Davis, F. D. 2003. User acceptance of information technology: toward a unified view, MIS Quarterly 27(3): 425–478. https://doi.org/10.2307/30036540

Weber, M.; Hoogma, R.; Lane, B.; Schot, J. W. 1999. Experimenting with Sustainable Transport Innovations: a Workbook for Strategic Niche Management. University of Twente, Enschede, Netherlands. 96 p. Available from Internet: https://research.tue.nl/en/publications/experimenting-with-sustainable-transport-innovations-a-workbook-f

Wiesenthal, T.; Condeço-Melhorado, A.; Leduc, G. 2015. Innovation in the European transport sector: a review, Transport Policy 42: 86–93. https://doi.org/10.1016/j.tranpol.2015.05.003

Yeo, W.; Kim, S.; Park, H.; Kang, J. 2015. A bibliometric method for measuring the degree of technological innovation, Technological Forecasting and Social Change 95: 152–162. https://doi.org/10.1016/J.TECHFORE.2015.01.018