Business Model Risk Analysis: Predicting the Probability of Business Network Profitability

  • Pontus Johnson
  • Maria Eugenia Iacob
  • Margus Välja
  • Marten van Sinderen
  • Christer Magnusson
  • Tobias Ladhe
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 144)

Abstract

In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business’ present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the Predictive, Probabilistic Architecture Modeling Framework (P2AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P2AMF-based approach for profitability risk prediction is also based on the e3-value modeling language and on the Object Constraint Language (OCL). The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case.

Keywords

value networks profitability risk analysis probabilistic inference goal interoperability 

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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Pontus Johnson
    • 1
  • Maria Eugenia Iacob
    • 2
  • Margus Välja
    • 1
  • Marten van Sinderen
    • 2
  • Christer Magnusson
    • 3
  • Tobias Ladhe
    • 3
  1. 1.Department of Industrial Information and Control SystemsRoyal Institute of Technology (KTH)StockholmSweden
  2. 2.Centre for Telematics and Information TechnologyUniversity of TwenteEnschedeThe Netherlands
  3. 3.Department of Computer and Systems SciencesStockholm UniversityStockholmSweden

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