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Knowledge to manage the knowledge society

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Purpose ‐ The purpose of this research is to make evident the inadequateness of concepts and language based on industrial knowledge still used in current practices by managers to cope with problems of the post-industrial societies characterised by non-linear process of emergence and acquisition of properties. The purpose is to allow management to use language and concepts more appropriate to deal with complexity, i.e. to represent, induce and orient processes of chance, and second, to outline a theory of practice guiding their efforts. The purpose is also to underline the urgency of a new general management education. Design/methodology/approach ‐ The methodology is based on contrasting concepts and their linguistic representations of the industrial age to the related post-industrial ones. The approach is based on representing processes by using a more appropriate language, cultural aspect of science of complexity, able to deal with processes of emergence. Findings ‐ Suitable, appropriate and open linguistic representations allow effective management of complex social systems where processes of emergence, i.e. acquisition of properties, occur. Current educational process for managers should be rethought. Learning relates to design new suitable models. Research limitations/implications ‐ One limit of this approach is given by the fact that it is not easy to implement, it cannot be considered a tool and imbalances are inevitable due to differences and inhomogeneous assumption of this new thinking. Practical implications ‐ It is a potential guide in helping practitioners in recognizing, inducing and managing complexity of processes and change. Originality/value ‐ The paper presents a new way to recognise and see reciprocal-relational forces within a cultural-social-political context by using suitable translations of concepts and approaches introduced in science of complexity, such as in physics, mathematics, biology, and chemistry.
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Keywords: Coherence; Complexity; Constructivism; Emergence; Knowledge; Language; Learning; Management; Model; Observer; Reductionism

Document Type: Research Article

Publication date: May 18, 2012

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