Business model risk analysis: Predicting the probability of business network profitability
2013 (English)In: Lecture Notes in Business Information Processing, 2013, 118-130 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
2013. 118-130 p.
, Lecture Notes in Business Information Processing, ISSN 1865-1348 ; 144
goal interoperability, probabilistic inference, profitability, risk analysis, value networks, Architecture modeling, Business collaboration, Business networks, Collaboration projects, Modeling languages, Object Constraint Language, Value network, Forecasting, Industry, Interoperability
IdentifiersURN: urn:nbn:se:kth:diva-134655DOI: 10.1007/978-3-642-36796-0-11ISI: 000345294000011ScopusID: 2-s2.0-84875641908ISBN: 978-3-642-36796-0ISBN: 978-3-642-36795-3OAI: oai:DiVA.org:kth-134655DiVA: diva2:678093
5th International IFIP Working Conference on Enterprise Interoperability, IWEI 2013, 27 March 2013 through 28 March 2013, Enschede
QC 201312112013-12-112013-11-272015-01-15Bibliographically approved