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Supply Chain Modelling Using Data Science

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Business Information Systems Workshops (BIS 2018)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 339))

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Abstract

The paper describes a research results in the field of supply chain modelling. The supply chain topology model, which will be the base for further analysis, is modelled as a network where nodes represent entities and business processes between them are presented as edges. A convenience stores network with a franchising business model was chosen for the model evaluation. The analysis uncovers conflicting goals between the franchisees and the franchise holder that must be taken into account. To conduct the research the Data Mining techniques, especially Process Mining (process design, process improvement, process analysis) will be used. First insight into Information needs is described.

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Notes

  1. 1.

    Fast Moving Consumer Goods.

  2. 2.

    http://www.zabka.pl.

  3. 3.

    https://www.circlek.com/.

  4. 4.

    https://www.7-eleven.com/.

  5. 5.

    Warehouse Management System.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Faculty of Informatics and Electronic Economy, Poznań University of Economics, al. Niepodleglości 10, 61-875, Poznań, Poland

    Szczepan Górtowski

  2. Żabka Polska, Plac Andersa 7, 61-894, Poznań, Poland

    Szczepan Górtowski

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  1. Szczepan Górtowski
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Correspondence to Szczepan Górtowski .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Witold Abramowicz

  2. Fraunhofer FOKUS, Berlin, Berlin, Germany

    Adrian Paschke

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Górtowski, S. (2019). Supply Chain Modelling Using Data Science. In: Abramowicz, W., Paschke, A. (eds) Business Information Systems Workshops. BIS 2018. Lecture Notes in Business Information Processing, vol 339. Springer, Cham. https://doi.org/10.1007/978-3-030-04849-5_54

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  • DOI: https://doi.org/10.1007/978-3-030-04849-5_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04848-8

  • Online ISBN: 978-3-030-04849-5

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