Using bayesian belief networks for modeling of communication service provider businesses

Pekka Kekolahti*

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review


This paper analyses the usage of Bayesian Belief Networks (BBNs) for Communication Service Provider (CSP) business modeling and simulation. Large and complex BBNs have been created to describe the causal relationships in CSP business domains. As a part of the study, a novel method to collect knowledge from a large number of independent experts living in different countries has been introduced. A BBN from each expert result was created (referred to here as a sub-BBN). Business model ontology was utilized to combine sub-BBNs together into a comprehensive model. The resulting BBN represents typical business circumstances in the European telecommunications domain. The experts participating in the study represented expertise in different business related categories such as technology, processes, customer experience, regulation, organization and products. Experts were asked to list causality triplets for business categories including causal connection strengths, in order to assess the belief part as well. The triplets were manually converted to a graphical causal map and conditional probability tables constructed. The benefit of the method is the capability to introduce rapidly a high number of variables and causal relationships. A challenge is that experts use different terms with the same underlying meaning.

Original languageEnglish
Pages (from-to)59-67
Number of pages9
JournalCEUR Workshop Proceedings
Publication statusPublished - 2011
MoE publication typeA4 Article in a conference publication


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