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Download If clicking does not initiate a download, try right clicking or control clicking and choosing "Save" or "Download".(The run link is disabled for this model because it was made in a version prior to NetLogo 6.0, which NetLogo Web requires.) |
WHAT IS IT?
This Model qualifies and extends MarchÕs (1991) model regarding the exploration-exploitation trade-off in organizational learning. Whereas MarchÕs 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- ingÑa contention wholly consistent with Levinthal and MarchÕs (1993) notion of Òspatial myopia.Ó 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 oneÕs 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 searcherÕs, 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 sourceÕs beliefs with probability P6. ¥ A proportion P7 (0 ² P7 ² 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.
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