Purpose This paper has the purpose of exploring the significance of bounded rationality for innovation research. It does so by expounding the structure and the assumptions of an agent-based model where boundedly rational actors engage in knowledge development and imitation. It is a conceptual paper that illustrates the model but does not present its results. Design/methodology/approach This model explores the consequences of common theoretical hypotheses and empirical stylized facts regarding innovation, knowledge development and knowledge management by geographically clustered rival firms. Our model artificially generates innovations, unknown and unexpected to our artificial decision-makers. Since the set of possibilities is not known a priori to our agents, they cannot apply utility maximization. Bounded rationality enters this model both as behavioural rules of thumb and as cognitive constraints on their application. Originality/value This paper links innovation studies to the concept of bounded rationality. It shows what problems must be faced, and what issues must be addressed by an agent-based model on this subject.
Cristina Boari, Guido Fioretti, Vincenza Odorici (2017). A model of innovation and knowledge development among boundedly rational rival firms. TEAM PERFORMANCE MANAGEMENT, 23(1/2), 82-95 [10.1108/TPM-10-2015-0050].
A model of innovation and knowledge development among boundedly rational rival firms
BOARI, CRISTINA;FIORETTI, GUIDO;ODORICI, VINCENZA
2017
Abstract
Purpose This paper has the purpose of exploring the significance of bounded rationality for innovation research. It does so by expounding the structure and the assumptions of an agent-based model where boundedly rational actors engage in knowledge development and imitation. It is a conceptual paper that illustrates the model but does not present its results. Design/methodology/approach This model explores the consequences of common theoretical hypotheses and empirical stylized facts regarding innovation, knowledge development and knowledge management by geographically clustered rival firms. Our model artificially generates innovations, unknown and unexpected to our artificial decision-makers. Since the set of possibilities is not known a priori to our agents, they cannot apply utility maximization. Bounded rationality enters this model both as behavioural rules of thumb and as cognitive constraints on their application. Originality/value This paper links innovation studies to the concept of bounded rationality. It shows what problems must be faced, and what issues must be addressed by an agent-based model on this subject.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.