This study was supported by a Grant-in-Aid under the Knowledge Cluster Initiative from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
The theoretical population ecology constructs of commensalism, parasitism, and amensalism are applied in an analysis of the Knowledge Cluster Initiative (KCI), a unique social experiment establishing university-business-government alliances for knowledge-intensive innovative clusters in Japan.
The data for this current analysis were retrieved from the Knowledge Cluster Initiative (KCI) in Japan.1 This initiative was implemented by the Japanese Ministry of Education, Culture, Sports, Science, and Technology (MEXT), which made the assessment data available to researchers to examine the performance of these alliances.
The thoughts presented in this work aim to stimulate researchers to pursue, in future studies, further details about the relationship between absorptive and desorptive capacity in mutually interacting knowledge clusters.
To our knowledge, the Knowledge based Cluster Ensemble (KCE) [ 14] is the only algorithm using prior knowledge in consensus clustering paradigm for gene expression datasets.
Every knowledge cluster and innovation network can also be understood as a subcomponent (sub-element) of a larger macro-level knowledge cluster or innovation network, in other words, innovation meta-networks and knowledge meta-clusters (see again Figure ten of Carayannis and Campbell (2006).
The authors of this special issue present cases of different countries and tentatively integrate frameworks such as ecosystems, triple helix university industry government relationships, and knowledge clusters in order to analyze the empirical complexity of political, societal, technological and ecological interaction in the evolutionary context of cities.
An ideal context sees the presence of innovation networks and knowledge clusters (Carayannis and Formica 2006; Dell'Anno 2008, 2010) in which knowledge is diffused within the network.
