INFORMAL SOCIAL NETWORK AND TECHNICAL KNOWLEDGE TRANSFER IN R&amp;D

Theres a growing interest in Knowledge Management (KM) in the corporate world. The companys ability to compile the accrued knowledge, organize are valued by what they know. Knowing the organization, its culture and how your employees relate themselves formal or informally, became fundamental for elaborating strategies for an efficient KM application. The formal relationship is easily recognized in the organizational charts of any organization type; however the informal relationships, which generate high synergy, are not much explored as a manner of knowledge sharing. The present article has the purpose of presenting how the interpersonal relationship occurs in a general management of CENPES (Research Center Leopoldo Américo Miguez de Mello) which develops basic engineering projects for the oil and gas industry, identifying its key actors through the Social Network Analysis (SNA). We aimed to reveal how the employee sample is organized, considering four analysis factors: information, knowledge, friendship and trust. For data source, a survey was performed through questionnaires applied for the employees of the studied unit. For the analysis, UCINET and NETDRAW tools were used. As results, the key actors were identified for the four analysis factors and which is the relationship among the group. We have verified a bottleneck in information and knowledge transfer as well as little interaction among the groups of studied management teams.

Knowledge management; Social Network Analysis; Information and Knowledge

Macro structure	Definition	What represents in the network
Density	Is the quotient between the number of existing connections by the number of possible connections in a determined network.	Density represents the network potential concerning information flow, i. e. the largest the density, more intense is the information exchange
Geodesic distance	It is the shortest way between two actors.	Generally, it is the most efficient connection between two actors.
Diameter	It is the largest geodesic distance between any two pairs of actors in a network.	This measurement tells us how many steps are required to move from one side of the network to the other.
Micro structure	Definition	What represents in the network
Cohesion	Average of shortest ways between each pair of actors in the network.	It concerns the strong relationship between actors of a network, forming subgroups with bonds established by affinity.
Cliques	Definition inherited from the graph theory, where two or more actors choose all in the subgroup as pairs in their connections. The n-clicks, n-clans and k-plexes concepts are derivations of clicks.	Informally known as "cliques" in organizations.

Centrality Types	Definition	What represents in the network
Centrality	It is the measure of how accessible a determined actor is for the remaining actors of a network.	Actors with several connections with other actors have an advantage for owning multiple connection possibilities, generally, they are
In-degree Centrality	It is the measure of the number of connections that an actor receives from other actors.	Actors with high in-degree centrality are usually actors with high prestige in the network.
Out-degree Centrality	It is the measure of the number of connections that an actor establishes with other actors.	Actors with high out-degree centrality are usually power to influence in the network.
Closeness Centrality	It is the measure of the minimum number of connections that an actor needs to perform in order to establish a relation with any other actor of this network.	Actors with high level of proximity tend to receive information before other actors.
Betweenness Centrality	It is the measure based on the control performed by an actor over the interactions between two other actors.	The largest participation of an actor in the interaction control the highest is his power within the network.
Bonacich Centrality	It is the qualitative measure of centrality. since it considers not only the number of connections that an actor receives, but also analyzes which is connectivity of these other actors in the network.	A high Bonacich level indicates that an actor, in addition to having prestige, has power within the network The quality of connections is more important than their quantity.

SNA Metrics	Analysis Factors
	Information		Knowledge	Trust	Friendship
	Entry Information	Exit Information	Knowledge	Trust	Friendship
Macro Structure Analysis
Geodesic Distance
Diameter
Density %
Ego Centered Analysis
In-degree Centrality
Betweenneess Centrality
Closeness Centrality

Network Information
SNA Metrics	EI_Entry Information	ExI_Exit Information
Geodesic Distance	2.217	2.058
Diameter	5	4
Density	14.70%	18.34°o

EI	GG	GPEP	EPEP	EN	EG	FP	PPEP
GG	83%	25%	14%	18%	22%	15%	15%
GPEP	26%	27%	8%	5%	7%	13%	13%
EPEP	8%	3%	21%	1%	0%	2%	11%
EN	13%	5%	2%	35%	15%	1%	4%
EG	17%	12%	2%	12%	31%	3%	3%
FP	17%	19%	4%	9%	4%	55%	29%
PPEP	15%	19%	12%	7%	6%	23%	42%

ExI	GG	GPEP	EPEP	EN	EG	FP	PPEP
GG	83%	36%	19%	21%	22%	17%	15%
GPEP	31%	39%	12%	9%	10%	18%	16%
EPEP	17%	10%	42%	5%	4%	5%	18%
EN	18%	9%	1%	41%	22%	2%	3%
EG	17%	10%	1%	6%	30%	1%	2%
FP	28%	23%	7%	8%	6%	59%	25%
PPEP	25%	22%	16%	7%	6%	22%	55%

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[TFN1] Source: Adapted from Lago (2005)LAGO JÚNIOR, M.W. Redes Sociais Informais Intra-organizacionais e os Processos de Mudanças Organizacionais: Estudo em uma Empresa de Tecnologia da Informação. 2005. 251 f. Dissertação (Mestrado Profissional em Administração) - Universidade Federal da Bahia, Salvador, 2005.