Abstract
In this paper we present an event existence classification framework based on five business criteria. As a result we are able to distinguish thirteen event types distributed over four categories, i.e. truthful, invisible, false and unobserved events. Currently, several of these event types are not commonly dealt with in business process analytics research. Based on the proposed framework we situate the different business process analytics research areas and indicate the potential issues for each field. A real world case will be elaborated to demonstrate the relevance of the event classification framework.
Recommended Citation
Caron, Filip; vanden Broucke, Seppe; Vanthienen, Jan; and Baesens, Bart, "On the Distinction between Truthful, Invisible, False and Unobserved Events An Event Existence Classification Framework and the Impact on Business Process Analytics Related Research Areas" (2012). AMCIS 2012 Proceedings. 24.
https://aisel.aisnet.org/amcis2012/proceedings/DecisionSupport/24
On the Distinction between Truthful, Invisible, False and Unobserved Events An Event Existence Classification Framework and the Impact on Business Process Analytics Related Research Areas
In this paper we present an event existence classification framework based on five business criteria. As a result we are able to distinguish thirteen event types distributed over four categories, i.e. truthful, invisible, false and unobserved events. Currently, several of these event types are not commonly dealt with in business process analytics research. Based on the proposed framework we situate the different business process analytics research areas and indicate the potential issues for each field. A real world case will be elaborated to demonstrate the relevance of the event classification framework.