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whether the various forms of cooperation support imitation, with the imitation net-
work being the dependent variable. The results of a series of multiple network
regression models (MRQAP, see Krackhardt, 1988) have shown that bilateral proj-
ect cooperation and exchange of knowledge significantly increase the propensity of
two partners to learn from each other through successful imitation. Model 1 illus-
trates the significant positive association between knowledge exchange and success-
ful imitation (Table 13.2), a finding also reflected by an interview in which a network
member told of the effect that collaboration had had on imitation.
There is an online shop called Magento…, and all of these member firms that I just men-
tioned use Magento. There’s a lot of transfer here because the employees ask people, “Tell
me, have you already written a plug-in for Magento? It can do such and such.” And they say,
“Yes, we’ve done that.” (Interview, July 2010)
As with knowledge exchange, cooperation in projects also promoted imitation
between companies (model 2). In projects, knowledge from different companies
was merged and further developed to create new solutions. Companies reported that
the newly developed solutions were stored not in a joint program library, as is often
the case in the software industry or development syndicates, but rather in the com-
panies participating in the projects. This practice may be due to two facts: (a) the
use of standardized shop systems in the e-commerce industry, and (b) the use of
many different software systems. In the Comra.de network, for example, more than
six different shop systems were in use, with business firms mastering more than ten
different development environments if one includes programming language as well.
Therefore, the joint projects allowed the simplified development of specialist appli-
cations such as the use of new security systems on different standardized systems
that were equally used by a large number of companies. The new media industry
was characterized by standardization, modularization, and the accumulation of
knowledge. However, this knowledge was stored in and used by the individual com-
panies, not jointly (Grabher, 2004). Clearly, projects promoted the transfer of codi-
fied knowledge for the companies involved.
The fact that firms were engaged in employee-lending seems unrelated to the
probability of their learning from each other (model 3, Table 13.2). The multivariate
Table 13.2 MRQAP: Effects of forms of cooperation on the dyadic imitation of solutions
Variable Model 1 Model 2 Model 3 Model 4
Knowledge exchange 0.394** 0.370**
(0.042)a 0.036)
Employee-lending 0.045 −0.170*
(0.047) (0.042)
Project collaboration 0.327** 0.292**
(0.038) (0.039)
adj. R2 0.153 0.105 −0.001 0.228
p 0.000 0.000 0.319 0.000
aStandard deviations are in parentheses. *p < 0.05. **p < 0.001. N = 20 members, 380 observations,
5000 permutations. Dependent variable: imitation network. Adapted from Glückler et al. (2012,
p. 179). Reprinted with permission of Springer
13 Connectivity in Contiguity
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Buch Knowledge and Networks"
Knowledge and Networks
- Titel
- Knowledge and Networks
- Autoren
- Johannes Glückler
- Emmanuel Lazega
- Ingmar Hammer
- Verlag
- Springer Open
- Ort
- Cham
- Datum
- 2017
- Sprache
- deutsch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-319-45023-0
- Abmessungen
- 15.5 x 24.1 cm
- Seiten
- 390
- Schlagwörter
- Human Geography, Innovation/Technology Management, Economic Geography, Knowledge, Discourse
- Kategorie
- Technik