A method for predicting the probability of business network profitability

Pontus Johnson, Maria Eugenia Iacob, Margus Välja, Marten J. van Sinderen, Christer Magnusson, Tobias Ladhe

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)
18 Downloads (Pure)

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. 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.
Original languageEnglish
Pages (from-to)567-593
Number of pages27
JournalInformation systems and e-business management
Volume12
Issue number4
DOIs
Publication statusPublished - 4 Feb 2014

Keywords

  • SCS-Services
  • EWI-24704
  • Probabilistic inference
  • Profitability
  • Goal interoperability
  • Risk analysis
  • Value networks

Fingerprint Dive into the research topics of 'A method for predicting the probability of business network profitability'. Together they form a unique fingerprint.

  • Cite this