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A method for predicting the probability of business network profitability
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0002-3293-1681
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0003-1464-6163
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2014 (English)In: Information Systems and E-Business Management, ISSN 1617-9846, E-ISSN 1617-9854, Vol. 12, no 4, 567-593 p.Article in journal (Refereed) Published
Abstract [en]

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. 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 study originated from the Stockholm Royal Seaport smart city project.

Place, publisher, year, edition, pages
2014. Vol. 12, no 4, 567-593 p.
Keyword [en]
Goal interoperability, Probabilistic inference, Profitability, Risk analysis, Value networks
National Category
Computer Systems
URN: urn:nbn:se:kth:diva-149175DOI: 10.1007/s10257-014-0237-4ISI: 000344741500005ScopusID: 2-s2.0-84912032840OAI: diva2:738218

QC 20141215

Available from: 2014-08-16 Created: 2014-08-16 Last updated: 2014-12-15Bibliographically approved

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