Knowledge creation: revisiting the 'ba' humbug people and 'latent' knowledge in organizational learning

Knowledge management theory has struggled with the concept of `knowledge creation'. Since the seminal article of Nonaka in 1991, an industry has grown up seeking to capture the knowledge in the heads and hearts of individuals so as to leverage them for organizational learning and growth. But the process of Socialization, Externalization, Combination and Internalization (SECI) outlined by Nonaka and his colleagues has essentially dealt with knowledge transfer rather than knowledge creation. This paper attempts to fill the gap in the process - from Nonaka's own addition of the need for "ba" to Snowden's suggestion of that we consider "Cynefin" as a space for knowledge creation. Drawing upon a much older theoretical frame - work the Johari Window developed in group dynamics, this paper suggests an alternative concept - latent knowledge - and introduces a different model for the process of knowledge creation.

A multi-agent-based evolution model of innovation networks in dynamic environments

An innovation network can be considered as a complex adaptive system with evolution affected by dynamic environments. This paper establishes a multi-agent-based evolution model of innovation networks under dynamic settings through computational and logical modeling, and a multi-agent system paradigm. This evolution model is composed of several sub-models of agents' knowledge production by independent innovations in dynamic situations, knowledge learning by cooperative innovations covering agents' heterogeneities, decision-making for innovation selections, and knowledge update considering decay factors. On the basis of above-mentioned sub-models, an evolution rule for multi-agent based innovation network system is given. The proposed evolution model can be utilized to simulate and analyze different scenarios of innovation networks in various dynamic environments and support decision-making for innovation network optimization.