Abstract:
Given the central role of Business Models in company characterization, it is not surprising that a great deal of effort has been spent in studying suitable representations for them. Most of the proposed models, however, pursue a semi-formal human-readable graphical paradigm that is mainly meant to be discussed among stakeholders, rather than to be easily handled by information systems. In this paper we introduce a formal meta model that aspires to be general enough to capture the expressiveness of most currently adopted paradigms. At the same time, each produced Business Model instance is regular and structured enough to be processed through automated algorithms. Specifically, data are organized as a structured graph, allowing for the adoption of well-known graph-based mining techniques. The ability of the framework to deal with real-world scenarios is assessed by modelling several actual companies. Further, some examples of data processing are given, specifically with the aim of spotting common patterns within a data base of Business Models.
