An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implement methodologies to assist in the construction of an evolutionary process of knowledge creation and diffusion aimed at sustainable growth and innovation. The theory of complex social networks has been applied in several fields to help understand organizational cognitive processes. However, these approaches still insipiently consider the analysis of the nestedness and modularity of the studied networks. In this article, we presented an approach that sought to identify patterns of nestedness and modularity in networks of affiliation of people in projects in the organizational context. The study sought to identify these patterns in affiliation networks in a public organization providing information technology services in the period from 2006 to 2013. The detection of these patterns was performed using the NODF (Nestedness metric based on Overlap and Decreasing Fill) algorithm described by [1]. The nestedness and modularity metrics can influence patterns of knowledge creation and diffusion in formal and informal networks constituted for the execution of projects in organizations. This study showed that the network structures of the organization during the study period presented a high degree of nestedness, and it was possible to identify combined structures of nestedness and modularity.
References
[1]
Almeida-Neto, M., et al. (2008) A Consistent Metric for Nestedness Analysis in ecological Systems: Reconciling Concept and Measurement. OIKOS, 117, 1227-1239. https://doi.org/10.1111/j.0030-1299.2008.16644.x
[2]
Lewinsohn, T.M., Loyola, R.D. and Prado, P.I. (2006) Matrizes, redes e ordenações: a detecção de estrutura em comunidades interativas. Oecologia Brasiliensis, 10, 90-104. https://doi.org/10.4257/oeco.2006.1001.06
[3]
Hidalgo, C A and Hausmann, R. (2009) The Building Blocks of Economic Complexity. Proceedings of the National Academy of Sciences of the United States of America, Cambridge, 106, 10570-10575. https://doi.org/10.1073/pnas.0900943106
[4]
Pietronero, L., Cristelli, M. and Tacchella, A. (2013) New Metrics for Economic Complexity: Measuring the Intangible Growth Potential of Countries. .
[5]
Bastos, V.B., and Santos, M.V. (2007) Redes sociais informais e compartilhamento de significados sobre mudança organizacional. Revista de Administração de Empresas, 47, 27-39. https://doi.org/10.1590/S0034-75902007000300003
[6]
Borgatti, S.P. and Halgin, D. (2003) Analyzing Affiliation Networks.
[7]
Wasserman, S. and Faust, K. (1994) Social Network Analysis. Cambridge University Press, New York. https://doi.org/10.1017/CBO9780511815478
[8]
Bascompte, J., et al. (2003) The Nested Assembly of Plant-Animal Mutualistic Networks. (2003) Proceedings of the National Academy of Sciences of the United States of America, 100, 9383-9387. https://doi.org/10.1073/pnas.1633576100
[9]
Patterson, B.D. and Atmar, W. (1986) Nested Subsets and the Structure of Insular Mammalian Faunas and Archipelagos. American Heart Journal, 90, 795-803.
[10]
Danon, L., Albert, D. and Duch, J. (2005) Comparing Community Structure Identification. Journal of Statistical Mechanics: Theory and Experiment, 2005, P09008. https://doi.org/10.1088/1742-5468/2005/09/P09008
[11]
Almeida-Neto, M., Guimarães Jr., P.R. and Lewinsohn, T.M (2007) On Nestedness Analyses: Rethinking Matrix Temperature and Anti-Nestedness. Oikos, 116, 716-722. https://doi.org/10.1111/j.0030-1299.2007.15803.x
[12]
Ulrich, W. (2009) Nestedness Analysis as a Tool to Identify Ecological Gradients. Ecological Questions, 11, 27-34. https://doi.org/10.12775/v10090-009-0015-y
[13]
Serpro, S.F., De, P. and De, D. (2016) Site Institucional. www.serpro.gov.br
[14]
Flores, C.O., Poisot, T., Valverde, S. and Weitz, J.S. (2016) BiMat: A MATLAB Package to Facilitate the Analysis of Bipartite Networks. Methods in Ecology and Evolution, 7, 127-132. https://doi.org/10.1111/2041-210X.12458
[15]
Bustos, S., et al. (2012) The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems. PLoS ONE, 7, e49393. https://doi.org/10.1371/journal.pone.0049393
[16]
Nonaka, I. and Takeuchi, H. (1997) Criação de conhecimento na empresa: como as empresas japonesas geram a dinamica da inovação. Rio de Janeiro.
[17]
Dos Santos, J.L. and Sampaio, R.R. (2019) Temporal Analysis of the Diffusion of Knowledge in Networks of Software Maintenance and Development Project Team. Social Networking, 8, 122-146. https://doi.org/10.4236/sn.2019.83009
[18]
Pires, M.M., et al. (2011) The Nested Assembly of Individual-Resource Networks. Journal of Animal Ecology, 80, 896-903. https://doi.org/10.1111/j.1365-2656.2011.01818.x
