Geography Reference
In-Depth Information
to innovation become l eeting at best. As rivals imitate new products and processes, the
degree of dif erentiation or cost advantage accruing to the innovator erodes. The busi-
ness literature thus urges managers to defend against spillovers (Kogut and Zander,
1992; Lippman and Rumelt, 1982).
Though their prescriptions dif er, economists, sociologists, strategists, and students
of technology management all seek a better understanding of why some knowledge dis-
perses widely while other knowledge does not. In this quest, some scholars have focused
on the attributes of the knowledge itself. For example, highly specii c knowledge may
l ow slowly because few parties other than the initial innovator either have the baseline
knowledge and skills necessary to absorb it (Cohen and Levinthal, 1990) or can benei t
from its application (Henderson and Cockburn, 1996; McEvily and Chakravarthy,
2002). Other studies focus on how social networks structure the l ow of knowledge (e.g.
Coleman et al., 1957; Hansen, 1999; Singh, 2005), implicitly attributing the rate of dif u-
sion to the locus of innovation in the network.
This chapter seeks to augment our understanding of knowledge l ow by examining
the interplay between two features: social proximity and the complexity of the underly-
ing knowledge.
1
Social proximity here refers to the distance between two parties in a
social network; for example, one would consider those who have a direct relationship to
each other to be closer than those who have a mutual acquaintance but have never met.
We meanwhile dei ne complexity in terms of the level of interdependence inherent in
the subcomponents of a piece of knowledge (Kauf man, 1993; Simon, 1962; cf. Zander
and Kogut, 1995). Interdependence arises when a subcomponent signii cantly af ects
the contribution of one or more other subcomponents to the functionality of a piece of
knowledge. When subcomponents are interdependent, a change in one may require the
adjustment, inclusion or replacement of others for a piece of knowledge to remain ef ec-
tive.
Consider then an actor who is a source of knowledge and two potential recipients
of that knowledge - one socially close to the source and one further away. When
does the proximate actor have the greatest advantage over the distant in receiving
and building on the knowledge? We argue that
the advantage should peak when the
underlying knowledge is of moderate complexity
. Our expectation emerges from the
recognition that receiving and building on knowledge frequently requires the recipi-
ent to engage in search to i ll in gaps and correct transmission errors in the knowl-
edge conveyed - the cost and dii culty of which increase with knowledge complexity.
Social proximity reduces the need for search by facilitating high-i delity transmission
(i.e. complete information with negligible noise). On the other hand, as the social
distance separating the source and the would-be receiver grows, unaided search plays
an increasingly important role in dif usion. Under such conditions, simple knowledge
should l ow universally - to actors near and far - because search can easily substitute
for high-i delity transmission. Highly interdependent knowledge meanwhile dei es
dif usion, regardless of whether one relies on search or social proximity. For knowl-
edge of moderate complexity, however, a gap emerges between the ability of close
actors, relative to that of distant actors, to receive and build on knowledge. High-
i delity transmission gives proximate actors sui cient insight that they can succeed in
receiving and building on knowledge, even where more distant actors, who rely more
heavily on search, fail.
