Geography Reference
In-Depth Information
Appendix: Simulation of knowledge l ow
A simple simulation of knowledge l ow serves two purposes. It clarii es further why the
value of social proximity reaches its peak in the transfer of knowledge with intermedi-
ate interdependence. It also identii es the range of empirical results consistent with our
theoretical model. Specii cally, the theoretical model yields a unique prediction about the
impact of knowledge interdependence on the
gap
between citation rates of socially close
actors and socially distant actors, but can encompass a range of i ndings about the ef ect
of interdependence on close-actor citation rates alone or on distant-actor rates alone.
Model
Superstructure
The model employs Kauf man's (1993) NK approach, which a growing
number of researchers have used to simulate technological or organizational search. The
simulation unfolds as follows. First, we choose two parameters:
N
, the number of com-
ponents or ingredients that comprise a piece of knowledge, and
K
, the degree to which
those components interact in determining the utility of the knowledge. Using techniques
described below, a simulation then generates - in a stochastic manner - a mapping from
each possible way of coni guring the
N
components (i.e. each conceivable recipe) to a
measure of utility. One can visualize the mapping as a landscape in a high-dimensional
space. Each discrete component constitutes a 'horizontal' axis, and each possible manner
of using the component represents a point along that axis. The vertical axis records the
usefulness of the resulting piece of knowledge.
Next, we assume that some i rm has happened upon the most useful possible piece of
knowledge - the best way to coni gure the components (i.e. the template described in
the main chapter).
1
Two new parties then enter the landscape. One party, a close actor,
has access to the owner of the template, presumably through a social tie, while the
other, a distant actor, cannot access the original template through his social network.
Both strive to rediscover the original success - the model's equivalent to the ef orts to
receive and build on knowledge discussed in the main text. Thanks to its superior access
to the template, the close actor enjoys an advantage in this search process. The close
actor may begin its search closer to the original success, rel ecting the better information
it receives or its superior ability to interpret the transmission. Or, it may move toward
the success with greater speed and accuracy, rel ecting its ability to seek advice from the
owner of the template. The simulation models these mechanisms and records the rela-
tive success of the close actor and the distant actor in rediscovering the original piece
of knowledge.
Following this i rst iteration, the simulation generates a second mapping that, though
it dif ers in its particulars, has the same degree of interdependence as the i rst. A second
pair of close and distant actors tackle the second problem, and the program records
their relative success. The simulation iterates through this process hundreds of times.
From the repetition emerges a proi le of how close and distant actors fare relative to
one another for a given degree of interdependence. We then adjust
K
, the parameter
that governs interdependence, and repeat the process. By doing so, we build an under-
standing of how interdependence af ects the relative ability of close and distant actors to
rediscover the original success.
This description of the model's superstructure leaves two aspects of the simulation
