iBusiness, 2012, 4, 256-259
http://dx.doi.org/10.4236/ib.2012.43032 Published Online September 2012 (http://www.SciRP.org/journal/ib)
Study on Team Stability Based on the Perspective of
Knowledge Potential*
Yi Huang, Jinfu Ye, Zhi Gao
Knowledge of Management, Northwestern Polytechnical University, Xi’an, China.
Email: dxx9664@126.com, yjf@nwpu.edu.cn, dazhi1217@163.com
Received May 24th, 2012; revised June 24th, 2012; accepted July 24th, 2012
ABSTRACT
Based on the knowledge potential, we analyze the stability of team. Using Logistic rule simulation knowledge of alli-
ance competition process, we draw stable solution of knowledge shift in the team; through the system MATLAB simu-
lation, it shows that stability of team has something to do with length of cooperation. Research results can provide refer-
ence for promoting the stability of team and internal knowledge sharing.
Keywords: Knowledge Potential; Stability; Knowledge Shift; Team
1. Introduction
In modern society, high pressure fills market environ-
ment and global economy. Knowledge has become the
key of economy resources as well as the dominant source
of competitive edge. It is necessary to explore effectively
the members’ knowledge position, to achieve the indi-
vidual knowledge shift in research team. Thus improving
innovative level and promoting exploratory speed, which
will play a crucial role in new products exploitation. On
account of the members in workgroup who has satisfy
the senior professional knowledge technical skills, which
means they can keep the initiative in their own hands to a
great extent; concurrently, the innovation is very impor-
tant in their job, furthermore quick rhythm and high stress.
They bring up an instability situation in workgroup be-
tween individuality and entirety; otherwise it would exert
adverse influence on information interchanged in work-
group.
Nowadays, Zhou Na [1], Zhou Mi [2] have been doing
research in this region, also they have made a great deal
of efforts doing practice research in personal relationship.
In other ways, previously, the research about information
transfer of individuality and entirety always focuses on
conciseness, avoiding duplication and originality, the point
of view of research focuses on drifted mechanism and
procedure, emphasizes emphatically individual charac-
teristic, for instances personal skills, knowledge and as-
piration, the feature of knowledge, the social relations of
two parties and its influence on knowledge transfer, nev-
ertheless, some researches were found in relationship be-
tween team and personality when transference is com-
pleted. It is an overwhelming major circumstance in con-
temporary time that the individuality acquires knowledge
from internal team, thus he can promote personal compe-
tition, in this process, individual would not be satisfied
with the existing team, therefore they would select other
team to cooperate, on this occasion they pose a threat to
stable relationship between individual and entirety, the
team eventually would disintegrate. That is the major
impediment to transfer knowledge in internal team. The
views on individual, adoption of the new environment
would expend a great deal of time and energy, mean-
while it would have negative influence on knowledge
transference in the scope of team. The research by Wei
Jiang [3] demonstrated that knowledge position leads to
knowledge transference in internal team, therefore, it can
improve the team’s stability. Nonetheless, the general re-
search is not concentrated on “how the knowledge posi-
tion influences over knowledge team’s stability”.
From the above, based on the angle of knowledge po-
sition, this article is to analyze knowledge shared situa-
tion in knowledge team, which includes different knowl-
edge position individual in principal knowledge, to in-
vestigate how it can preserve the stable and permanent
relationship of team by main part of knowledge, and im-
prove stability in knowledge team.
2. The Theory of the Knowledge Position
Polanyi (1967) separated knowledge which “tacit knowl-
edge” and “explicit knowledge” based on the knowledge
pattern. Inside, explicit knowledge means being capable
of encoding, which can be illustrated by text, data, for-
*This research was supported by Fund of the China Shang Fei company
management innovation mode research under grant NAEK0001.
Copyright © 2012 SciRes. IB
Study on Team Stability Based on the Perspective of Knowledge Potential 257
mula, specification, brochure and number; tacit knowl-
edge means based on persons, being not able to encode,
difficult to obtain by normal approach. From one of sub-
division and profession technical region, the knowledge
quality and number by knowledge subject were different
in strategy union, for that reason, comparative “advan-
tage individual” and “disadvantage individual” both ex-
ist.
Advantage knowledge position demonstrates the depth
and extent of knowledge in enterprise, furthermore, the
depth and width of knowledge illustrate a great deal of
knowledge stock, which means formidable power of
competition. Chen Feixiang [4] and others introduce phy-
sical concept (potential energy, potential difference, en-
ergy transform) to research of knowledge diffusion, Chen
regards the persons who possess advantage knowledge as
an entirety. They were originally spreading sources in
knowledge diffusion theory. Li Li [5] made a deep inves-
tigation and study in the relation between knowledge po-
sition and knowledge diffusion based on the net envi-
ronment, Li regards the knowledge diffusion by knowl-
edge subject mainly influence their internal knowledge
region (knowledge depth (KD) and knowledge width
(KW)). Therefore, taking account of discrepancy of
knowledge width and depth would result in knowledge
location, consequently knowledge always moves from
advantage position to disadvantage position.
Advantage object considers out of individual profit.
They were not willing to share knowledge with disad-
vantage object. Yang Xun and Shi Ping [6] were investi-
gated the tacit knowledge spreading conditions and acti-
vation by employee, investigation indicates the key to
spread knowledge were aspiration and ability by advan-
tage knowledge object. Tao Houyong and Liu Hong [7]
provided that through sharing mechanism, knowledge
can achieve connection among advantage object, disad-
vantage object and organization environment, neverthe-
less, distinct sharing mechanism results in different effect,
thence shall construct reasonable sharing mechanism on
their individual pattern, bring knowledge sharing initia-
tive into effect, promote the effect of knowledge sharing
and achieve maximum group profit. The knowledge ob-
ject in strategic league can be regarded as a mixture by
knowledge position from variable region, different re-
gions consist of dissimilar knowledge position, otherwise
the knowledge object perhaps is provider (advantage) or
receiver (disadvantage) in particular region. The Figures
1(a) and (b) provided that when a team is a member,
choose his partner. The ordinary selection is based on
knowledge position to take effective measures. Reason-
able potential difference, equitable knowledge sharing,
which can foster knowledge connection and innovation,
furthermore improve whole efficiency and are beneficial
Knowledge
flow
(a)
a
KW
a
b
c
KD
b
c
(b)
KW
KD
Figure 1. (a) Team A; (b) Team B.
for constructing stable knowledge league. Whether the
knowledge sharing was overheated, it will cause oppor-
tunism, the advantage objects outflow eventually their
central knowledge, to decline team’s competition; other-
wise, whether the knowledge sharing was insufficient, it
will result in competitive learning ability and additional
purchase, thence the league’s productiveness can not be
realized, eventually disintegrate the team. Consequently,
how to conduct shared knowledge with colleague as well
as grasp the certain extent, this is mainly based on team’s
stability. Therefore, in this article it would draw support
from the members of mathematical analysis team. To ex-
plore the process of competition and cooperation in their
knowledge transference, therefore, discover the method
to maintain stable team from it.
3. Modeling and Simulation
3.1. Logistic Rule
In nature, if only a biological community survive, people
commonly choose Logistic model to describe the species
of the evolution process of the population, namely
 
11
x
t
xt rxtN

 


x
t is the number of species. r is inherent growth rate.
N is the environment resources allowing the biggest
population quantity. The following of this paper will use
Copyright © 2012 SciRes. IB
Study on Team Stability Based on the Perspective of Knowledge Potential
258
a Logistic research on individual and team stability.
3.2. Model Construction
Generally, individuals have a strong dependence on the
team, a good team can accelerate the development of
individuals, and a bad team can have the opposite effect
on the individuals. Therefore, the team and individual
can not exist with interdependence. However, due to the
external environment changes and fierce competition, the
number of individuals to the knowledge of the team en-
sures the stability of the team and individuals to develop
it. Here we are on this issue being discussed by the
mathematical model.
A set body of knowledge can exist independently, his
knowledge of the stock increased in accordance with the
laws Logistic, B is the body of knowledge providing a
body of knowledge A knowledge of the stock, the body
of knowledge helping the growth of A’s stock of knowl-
edge, knowledge, knowledge of the main A increase the
stock of the knowledge we can write
  
12
111 1
12
11
x
txt
xt rxts
NN
 

(1)
r1 (r1 as

1
x
t is intrinsic growth rate of the stock of
knowledge), N1, N2 (N1, N2 is A, B of the largest stock of
knowledge), the mean of 1
s
is knowledge of the main
body of knowledge A, which is supplied stock of
knowledge by B, that is 1
s
times for A knowledge of
the main body of knowledge supply consumed the stock
of knowledge A. s2 A supply B of the stock knowledge is
s2 that the stock of knowledge consumed by B.
Knowledge of B will perish without knowledge of the
main A, The mortality rate is set as
2
r
 
22
1
2
trx
 t (2)
Knowledge A provides knowledge to the knowledge B.
The right of Equation (1) plus the growth knowledge of
A promotes B get
 
1
222 2
1
11
x
t
xtrxts N


 


(3)
only when

1
2
1
1
xt
sN, the stock of knowledge that the
number of the knowledge B will only increase, and have
competitive, and at the same time the stock of the
knowledge B growth, will be affected by their own block
function, so the Equation (3) will become
 
12
222 2
12
11
x
x
xt rxts
NN




(4)
Simultaneous Equation (3) and Equation (4) get equa-
tions
 
 
12
111 2
12
12
222 2
12
11
11
x
txt
xt rxts
NN
xx
xt rxts
NN

 






Through analysis balance, discuss after long enough
time, two of the main body of knowledge change trend.
From Table 1 we can see stable point p2, A and B can
depend on each other’s symbiosis.
3.3. Analog Emulation
According to the study, we have hypothesis that 10.1x
.
20.1x
, 12.5r
, 21.8r
, 1, 2, p1, p
2, 1.6N1N
respectively assign s1, s
2. Use of MATLAB simulation
subject knowledge the stock of knowledge that the chan-
ges with time trend.
Through Figures 2 and 3 research we can see, knowl-
edge is a main body organization, individual came into
the organization, in the stock of knowledge that the team
will be significantly reduced. After a period of time, the
team will constantly pick up knowledge, but in some
Figure 2.
1=0.5s, .
2=1.6s
Figure 3.
1=0.3s, .
2=1s
Copyright © 2012 SciRes. IB
Study on Team Stability Based on the Perspective of Knowledge Potential
Copyright © 2012 SciRes. IB
259
Table 1. A and B stable solution.
Balance P q Stability conditions

11
,0pN
122
1rrs

122 1rr s
212
1, 1sss


1122
2
12 12
11
,
11
NsNs
pss ss






1122
12
11
1
rsrs
ss

 
121 2
12
11
1
rrs s
ss

1212
1, 1,1ssss



30,0p 12
rr
 12
rr
Unstable
period, the rapid growth of the personal knowledge be-
comes very fast. Stock of team knowledge, begins to
drop constantly. Because of people in the whole team
slowly began to absorb the knowledge of operation and
this is the second peak time. So we can see the relation-
ship between team and individual, there will be two
times for absorbing the knowledge of the peak. The two
peaks will enhance the stock of the individual knowledge.
After the stock of the individual and team knowledge that
will also begin to increase. In the two times of individual
rapid knowledge absorbing from the team, and it is the
time for individual to grow faster. The internal culture of
concept is formed by the organization and the individual
also is the fastest absorption. So this time the organiza-
tion shall intensify the personal training, make people
more quickly into the organization of the atmosphere,
and promote organization knowledge transfer efficiency.
4. Conclusions
In this paper, Logistic principle is made use of simulating
the competition and cooperation process, and the knowl-
edge sharing stable solution is obtained; meanwhile, it is
proved that there is some connection between team sta-
bility and time through system simulation and algorithm
calculation.
Team stability is improved by improvement of team
knowledge transfer, the next step of research, quantita-
tive research will be done on factors of algorithm based
on demonstration.
REFERENCES
[1] N. Zhou and J. A. Zhong, “Team Difference and Personal
Innovation Behavior: Adjust Dependence as Variab,” Un-
derstand Science of China, Vol. 17, No. 1, 2007, pp. 27-
30.
[2] M. Zhou, X. P. Zhao and W. Li, “Individual and Team
Performance Related Knowledge Transfer Effect, Team
Performance Relations,” Intelligence Magazine of China,
Vol. 12, No. 12, 2006, pp. 24-27.
[3] J. Du and J. Wei, “The Stock of Knowledge Increasing
Mechanism Analysis,” Understand Science of China, Vol.
10, No. 7, 2004, pp. 24-27.
[4] F. X. Chen, L. Zhang and J. Hu, “Knowledge Diffusion,
the Establishment of the Field and Empirical Analysis,”
Studies in Science of China, Vol. 23, No. 2, 2005, pp.
253-257.
[5] L. Li, X. H. Dang and S. K. Zhang, “Based on the Knowl-
edge of the Potential of the Technology Innovation Co-
operation Study Knowledge Diffusion,” Understand Sci-
ence of China, Vol. 14, 2007, pp. 20-26.
[6] X. Yang and P. Shi, “Staff Personal Knowledge Diffusion
Conditions and Incentive,” Journal of Ocean University
of China, Vol. 20, No. 4, 2005, pp. 50-53.
[7] H. Y. Tao and H. Liu, “Knowledge Sharing Mechanism
of Group Study on the Impact of Performance,” Scientific
Research Management of China, Vol. 29, No. 3, 2008, p.
53.