A method for predicting the probability of business network profitability |
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Authors: | Pontus Johnson Maria Eugenia Iacob Margus Välja Marten van Sinderen Christer Magnusson Tobias Ladhe |
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Affiliation: | 1. Department of Industrial Information and Control Systems, Royal Institute of Technology (KTH), Stockholm, Sweden 2. Centre for Telematics and Information Technology, University of Twente, Enschede, The Netherlands 3. Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden
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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. |
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