Titlebook: Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net; Gülay Canbalo?lu,Jan Treur,Anna Wiew

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書目名稱Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net影響因子(影響力)




書目名稱Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net影響因子(影響力)學科排名




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書目名稱Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net讀者反饋




書目名稱Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net讀者反饋學科排名

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大炮

Using Self-modeling Networks to Model Organisational Learningg individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organisation is created, which after its formation can then be adopted by individuals. This provides mechanisms for organisational learning. These mechanisms have been used as a

大炮

Organisational Learning and Usage of Mental Models for a Team of Match Officials: A Second-Order Adaearning in team-related performances. The chapter describes the value of using shared mental models to illustrate the concept of organisational learning, and factors that influence team performances by using the analogy of a team of match officials during a game of football and show their behavior i

Vulvodynia

Heuristic Context-Sensitive Control of Mental Model Aggregation for Multilevel Organisational Learnicess. This aggregation process usually does not only depend on the mental models used as input for it, but also on several context factors that may vary over circumstances and time. This means that for computational modeling of organisational learning by adaptive networks, where the formation of a s

NOVA

Adaptive Mental Model Aggregation in Organisational Learning Using Boolean Propositions of Context F. This aggregation process usually does not only depend on the mental models used as input for it, but also on several context factors that may vary over circumstances and time. This means that for computational modeling of organisational learning the aggregation process better can be modeled as an

Consequence