Notice of RetractionTechnological innovation and learning of industrial cluster as a complex adaptive system

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

The objective of the paper is to provide a theoretical model of technological innovation and learning of industrial cluster as a complex adaptive system (CAS). It argues that a cluster is a CAS with a multi-level, multi-subsystem structure. In agent-and-layer modeling (ALM) given by authors, the various agents are initiative to adapt complex environments inside and outside the cluster, which exchange materials, information, technologies and values via the core network, support networks and external networks as well, and acquire knowledge and accumulate experiences from technological learning to form a dynamic, self-adaptive system. The paper examines the motivation for independent and interacting firms in clusters to learn technologies comes from seeking to increase and maximize their own revenues from technological learning. Entrepreneurs in the cluster CAS are driving force of innovation and learning in the whole process.