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Facilitating Enhanced Decision Support Using a Social Norms Approach
Abstract
Social norms constrain behavior of individuals either through obligating or prohibiting certain types of behavior. Norm-based mechanisms have only recently found applications in enhancing decisions of knowledge workers in an automated business process management context. The norms inferred in the context of business process executions are then recommended to users so as to enable them to make informed decisions. The previous work on prohibition norm inference focused on identifying failure cases, which is now complemented by first inferring norms from the successful process execution cases and then inferring prohibition norms. This approach based on considering social feedback (i.e. inferring what is obliged and prohibited from history logs of process execution) shows encouraging results under uncertain business environments. Using simulation results the paper demonstrates that using the norm based mechanism results in reduced failure rates in the decision making of a knowledge worker while still providing maximum flexibility for the user to choose from a range of actions to execute.
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