Heuristic Context-Sensitive Control of Mental Model Aggregation for Multilevel Organisational Learning

Abstract

Within organisational learningOrganisational learning, aggregationAggregation of developed individual mental modelsIndividual mental model to obtain shared mental modelsShared mental model for the organisationOrganisation is a crucial process. This aggregationAggregation process usually does not only depend on the mental modelsMental model used as input for it, but also on several context factorsContext factor that may vary over circumstances and time. This means that for computational modelingComputational modeling of organisational learningOrganisational learning by adaptive networksAdaptive network, where the formation of a shared mental modelShared mental model is a form of networkNetwork adaptationAdaptation, the underlying aggregationAggregation process better can be controlled by a second-order adaptive dynamical process to obtain a context-sensitiveContext-sensitive way of aggregationAggregation. In this chapter it is explored how context factorsContext factor can be used to model this form of second-order networkNetwork adaptationAdaptation. Indeed, using self-modeling networksSelf-modeling network, mental modelMental model adaptationAdaptation by learningLearning, formation or aggregationAggregation can be modeled in an appropriate manner at a first-order adaptive self-model level, whereas the controlControl over such processes can be modeled at a second-order adaptive self-model level. In this chapter it is shown how by a second-order self-modelSecond-order self-model in such a networkNetwork, contextContext-rich knowledge can be specified that is used to controlControl the aggregationAggregation with the first-order self-modelFirst-order self-model in a context-sensitiveContext-sensitive manner. This is illustrated for heuristicHeuristic knowledge. Based on this controlControl knowledge such an adaptive network modelAdaptive network models can exert context-sensitive controlContext-sensitive control over the mental model aggregationMental model aggregation process. Thus, a computational networkNetwork modeling approach of organisational learningOrganisational learning is presented in which the process of aggregationAggregation of individual mental modelsIndividual mental model to form shared mental modelsShared mental model is controlled in an adaptive context-dependentContext-dependent manner based on heuristicHeuristic knowledge.