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285 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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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
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