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Event-Driven Business Intelligence Architecture for Real-Time Process Execution in Supply Chains

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Business Information Systems (BIS 2010)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 47))

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Abstract

This paper gives an insight perspective for developing a business intelligence architecture to satisfy permanently growing controlling requirements in complex distribution networks. Supply Chain Management (SCM), as a part of management science concerning intelligent synchronization of supply and demand, is the basis for the development of flexible, proactive and adaptive real-time information systems, called Operational Business Intelligence (OpBI) systems, which offer a significant support for decision making on operational level. Application scenarios including concrete decision-problems are analyzed regarding system implementation and in consideration of supply chain performance. The conclusion reflects the development process in order to allow a foresight.

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Author information

Authors and Affiliations

  1. Mercator School of Management, Department of Technology and Operations Management, Chair of Information Systems and Operations Research, University of Duisburg-Essen, Lotharstraße 63, 47057, Duisburg, Germany

    Markus Linden, Sebastian Neuhaus, Daniel Kilimann, Tanja Bley & Peter Chamoni

Authors
  1. Markus Linden
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  2. Sebastian Neuhaus
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  3. Daniel Kilimann
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  4. Tanja Bley
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  5. Peter Chamoni
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Editor information

Editors and Affiliations

  1. Department of Information Systems, Poznań University of Economics, Al. Niepodległości 10, 61-875, Poznań, Poland

    Witold Abramowicz

  2. Institut für Informatik, Freie Universität Berlin, Takustr. 9, 14195, Berlin, Germany

    Robert Tolksdorf

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Linden, M., Neuhaus, S., Kilimann, D., Bley, T., Chamoni, P. (2010). Event-Driven Business Intelligence Architecture for Real-Time Process Execution in Supply Chains. In: Abramowicz, W., Tolksdorf, R. (eds) Business Information Systems. BIS 2010. Lecture Notes in Business Information Processing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12814-1_24

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  • DOI: https://doi.org/10.1007/978-3-642-12814-1_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12813-4

  • Online ISBN: 978-3-642-12814-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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