ITS taxonomy

Technological taxonomy, friendly browser or smart search engine are some key supporting tools attracting the end-users interest to navigate efficiently through classification schemes at domain or application level.

Despite there are several extensive studies on classification mechanisms in different domains, not many works have been conducted on taxonomy development in the ITS domain. Existing taxonomy approaches of related studies in smart city and city logistics (Benjelloun et al., 2010, Perboli et al., 2014) focus on high-level initiatives at the macro-level. Unfortunately, in the ITS field there is a lack of criteria that could fulfill end-user classification expectatives. The U.S. Department of Transportation’s research (RITA US DoT, 2015) developed a taxonomy of the ITS field considering several Levels of Detail, and Rafiq et al. (2013) proposed two taxonomies of EU ITS projects and initiatives under the FP6 and FP7 funding schemes. Consider for example the ITS Toolkit, which rely on a 4-dimension taxonomy to search for evaluation reports of case studies (El-Araby et al., 2010), and an additional 4-dimension in the output (Technical, Legal/Regulatory, Financial, Business model).

In NEWBITS, it has been considered several open questions to develop a useful taxonomy in ITS, considering for example:

  • Can we find the relevant dimensions/axes that categorise the different characteristics of ITS case studies?
  • Can the relevant criteria identified support a socio-technical approach to the development of new business models considering the network value flows (ie. Business ecosystem)?
  • Is the information required for the taxonomy tree obtainable from the analysis of case studies?

In Newbits, it has been implemented a well-accepted approach to taxonomy development (Nickerson et al., 2013) that combines two strategies (conceptualisation/deduction and empiricism/induction) into a single method in an iterative manner to allow for the flexibility in getting the best usable taxonomy.

And the resultant Taxonomy is summarized in the next table:

This taxonomy has been validated by means of 4 different case studies providing a well-balanced picture of the different transport modes (road, water, and rail) and types (personal, public, and freight), so they can be used in further analysis such as a conjoint analyses to show the preferences of the users in different case studies or in deploying a network-based business modelling approach for a better understanding of the competitive environment

PD: You can see more details in NEWBITS deliverable 2.3

References:

  • Benjelloun, A., Crainic, T. G., & Bigras, Y. (2010). Towards a taxonomy of City Logistics projects. Procedia-Social and Behavioral Sciences, 2(3), 6217-6228.
  • Perboli, G., De Marco, A., Perfetti, F., & Marone, M. (2014). A new taxonomy of smart city projects. Transportation Research Procedia, 3, 470-478.
  • RITA U.S. DoT, U. (2015), Taxonomy of intelligent transportation systems application. http://www.itslessons.its.dot.gov
  • Rafiq, G., Talha, B., Patzold, M., Luis, J. G., Ripa, G., Carreras, I., … & Desaeger, M. (2013). What’s new in intelligent transportation systems?: An overview of european projects and initiatives. IEEE Vehicular Technology Magazine, 8(4), 45-69.
  • El-Araby, K., Dinkel A., Kulmala R., & Magerl E. (2010). D1.1 – Selection criteria and classification of ITS applications. Toolkit for sustainable decision making in ITS deployment, 2DECIDE, 1-78.
  • Nickerson, R. C., Varshney, U., & Muntermann, J. (2013). A method for taxonomy development and its application in information systems. European Journal of Information Systems, 22(3), 336-359.
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