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International Conference on Enterprise Information Systems

ICEIS 2018: Enterprise Information Systems pp 158–172Cite as

Collectively Constructing the Business Ecosystem: Towards Crowd-Based Modeling for Platforms and Infrastructures

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 363))

Abstract

In this conceptual article, we highlight group modeling and crowd-based modeling as an approach for collectively constructing business ecosystem models. Based on case study examples, we showcase how engaging in the collective activity of crowd-based modeling supports the creation of value propositions in business ecosystems. Such collective activity creates shared, IS-embedded resources on the network level that align the diverse set of ecosystem stakeholders such as firms, public actors, citizens, and other types of organizations. Based on extant research, we describe the roles involved in building ecosystem models that inform and reconfigure shared infrastructures and platforms.

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Author information

Authors and Affiliations

  1. Technical University of Munich, Boltzmannstrasse 3, 85748, Garching, Germany

    Anne Faber, Adrian Hernandez-Mendez & Florian Matthes

  2. WHU - Otto Beisheim School of Management, Burgplatz 2, 56179, Vallendar, Germany

    Sven-Volker Rehm

Authors
  1. Anne Faber
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  2. Sven-Volker Rehm
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  3. Adrian Hernandez-Mendez
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  4. Florian Matthes
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Corresponding author

Correspondence to Anne Faber .

Editor information

Editors and Affiliations

  1. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. MODESTE/ESEO, Angers, France

    Olivier Camp

  4. INSTICC and Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Faber, A., Rehm, SV., Hernandez-Mendez, A., Matthes, F. (2019). Collectively Constructing the Business Ecosystem: Towards Crowd-Based Modeling for Platforms and Infrastructures. In: Hammoudi, S., Śmiałek, M., Camp, O., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2018. Lecture Notes in Business Information Processing, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-030-26169-6_8

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  • DOI: https://doi.org/10.1007/978-3-030-26169-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26168-9

  • Online ISBN: 978-3-030-26169-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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