A universal middleware streaming framework and data analytics: Analysing their economic feasibility in road transport planning


== Abstract ==

   The individual paths followed by road transport operators in adopting and using information and communication technologies (ICT) result in heterogeneous planning practices. This includes working with multiple IT systems, data sources and applications. There is no coordination or standardisation that ensures a straightforward approach to develop and implement cross-sector IT solutions. Different integrative state-of-the-art solutions are sub-optimal, not flexible and relatively expensive to maintain.  The proposed methodology starts by investigating the current working practices of a road transport operator. It reports on an own exploration initiative conducted by researchers in logistics and computer science, and brings together their complementary expertise. It identifies firstly the ICT solutions used at an operational level and points out the necessities for further integration, functionalities or application development. Secondly, it develops a theoretical model that assists road transport operators in checking whether using a uniform integration layer and data analytics tools is economically feasible. The model shows the fleet size from which significant costs reductions are made. These costs reductions are enabled by implementing a middleware framework and data analytics algorithm that assists human operators in operational planning.


== Original document ==

The different versions of the original document can be found in:

* [https://doi.org/10.1016/j.rtbm.2019.100424 https://doi.org/10.1016/j.rtbm.2019.100424]

* [https://hdl.handle.net/10067/1655590151162165141 https://hdl.handle.net/10067/1655590151162165141]

* [https://api.elsevier.com/content/article/PII:S2210539519302184?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S2210539519302184?httpAccept=text/xml],
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: [http://dx.doi.org/10.1016/j.rtbm.2019.100424 http://dx.doi.org/10.1016/j.rtbm.2019.100424] under the license https://www.elsevier.com/tdm/userlicense/1.0/

* [https://www.sciencedirect.com/science/article/pii/S2210539519302184 https://www.sciencedirect.com/science/article/pii/S2210539519302184],
: [https://academic.microsoft.com/#/detail/3003923667 https://academic.microsoft.com/#/detail/3003923667]