NetLogo User Community Models
(back to the NetLogo User Community Models)
by Elio Marchione
WHAT IS IT?
This Model qualifies and extends March’s (1991)
model regarding the exploration-exploitation
trade-off in organizational learning. Whereas
March’s model portrayed all learning in an organi-
zation as mediated by its organizational code, Miller and al. (2006)
add direct interpersonal learning. By allowing for
interpersonal learning, Miller and al. recognize that face-to-
face interaction can be critical to knowledge trans-
fer. Interpersonal learning is a
decentralized process that takes place without the
mediation of an organizational code. Miller and al. also incor-
porate the insight that location matters to learn-
ing—a contention wholly consistent with Levinthal
and March’s (1993) notion of “spatial myopia.”
This spatial dimension allows one to consider both
local and distant search as distinct aspects of the
process of interpersonal learning.
HOW IT WORKS
• The n individuals are situated within a grid
in which each has four neighbors (north, east,
south, and west). Unlike Axelrod (1997), Miller and al. de-
signed a grid without edges, so that all individuals
have the same number of neighbors.
• Individuals learn through engaging in local
and distant search. Local search involves finding
the best performer among one’s four neighbors and
then updating each belief to that of the superior
neighbor with probability P5. If two or more neigh-
bors have equally good performance, one of them is
chosen randomly as the superior. If the best-per-
forming neighbor has knowledge inferior to the
searcher’s, then the individual engages in distant
search. Distant search involves randomly drawing
four individuals from the population and choosing
the best performer among them. If the knowledge of
this best performer is superior to that of the searcher,
then the searcher adopts each of the
source’s beliefs with probability P6.
• A proportion P7 (0 ≤ P7 ≤ 1) of the m beliefs are
tacit. The organizational code conveys only explicit
knowledge and remains agnostic regarding the tacit
elements of knowledge. Miller and al. model this feature by
assigning permanent zeros for all tacit elements in
the organizational code, thus limiting the transmis-
sion of tacit knowledge to interpersonal exchanges.
We always choose P7 so that P7*m is an integer.
• Learning by and from the code is episodic.
Every P8 periods, the explicit elements of the organ-
izational code are updated and individuals learn
from this updated code within the same period.
Between such periods of code updating, they ded-
icate their attention to learning from other individ-
uals. Varying P8 reflects differences in the frequency
with which norms and beliefs are codified and
disseminated within organizations.
HOW TO USE IT
Varyng the Parameters:
Probability of socialization & learning from OC = socialization.P1
Probability of Organizational Code learning = learning.P2
Probability of personnel turnover = turnover.P3
Probability of reality turbulence = turbolence.P4
Probability of interpersonal local learning = face.to.face.P5
Probability of interpersonal distant learning = face.to.distance.P6
Proportion of Individuals tacit knowledge/beliefs = tacit.dimensions.P7
Time interval of Organization Code updating = episodic.learning.P8
Reality Complexity = reality-dimension
Size of Organization = actors-number
(if you change Reality Complexity and/or Size of Organization, remember to set a new world-size-x and world-size-y)
Press setup and go, and observe organizational behaviour.