Conference paper Open Access

Big data analytics in e-commerce logistics: Findings from a systematic review and a case study

Eleni Zampou; Christina Milioti; Aggelos Liapis; Vega Rodrigalvarez; Florian Flocke; George Dimitrakopoulos; George Bravos


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  <dc:creator>Eleni Zampou</dc:creator>
  <dc:creator>Christina Milioti</dc:creator>
  <dc:creator>Aggelos Liapis</dc:creator>
  <dc:creator>Vega Rodrigalvarez</dc:creator>
  <dc:creator>Florian Flocke</dc:creator>
  <dc:creator>George Dimitrakopoulos</dc:creator>
  <dc:creator>George Bravos</dc:creator>
  <dc:date>2018-04-16</dc:date>
  <dc:description>Digital evolution has significantly changed consumer shopping habits and expectations resulting in a major growth of e-commerce. The immediate outcome of this growth was the creation of a dynamic and turbulent environment with increasing density of the distribution network. This environment consists of many delivery points, multiple delivery channels and last-mile delivery requirements. Due to its complexity and the proliferation of data challenges, e-commerce logistics is an area where the application of Big data analytics can be proven to be extremely fertile. Despite the growing interest, there are limited studies that investigate the role of Big data. By using a design science approach, we clarified the current e-commerce logistics practices as well as the envisioned ones that can, to a large extent, be supported by appropriate big data technologies. We concluded to a set of business requirements that express the needs towards the e-commerce logistics. Then, the requirements were translated into a set of use case scenarios to demonstrate how they could be supported by big data analytics. We conclude by proposing a conceptual architecture of a big data analytics artefact that could cover the e-commerce logistics requirements.</dc:description>
  <dc:identifier>https://zenodo.org/record/1491581</dc:identifier>
  <dc:identifier>10.5281/zenodo.1491581</dc:identifier>
  <dc:identifier>oai:zenodo.org:1491581</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.1491580</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/tra2018</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode</dc:rights>
  <dc:subject>big data, business analytics, e-commerce logistics, collaboration, requirements</dc:subject>
  <dc:title>Big data analytics in e-commerce logistics: Findings from a systematic review and a case study</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
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