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Our analyses of 841 two-partner technology alliances within the ICT industry indicate that alliances between firms with moderate-to-high degrees of technological overlap favor high levels of knowledge acquisition across partnering firms while alliances among firms sharing either low or high levels of technological overlap are well-suited for complementary specialization.
In contrast, the best model for complementary specialization (H 2 ′ ) included only invasion level (χ = 0.11, d.f.
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At the network level, we used the operational concept of "complementary specialization" to test for interaction specialization in the community as a whole.
The low level of complementary specialization observed in bat-fruit networks was similar to values from bird-fruit networks (median close to 0.30) [46].
While alliances are widely acknowledged to facilitate knowledge transfers across firms, alliances also allow partnering firms to combine technological capabilities toward joint innovation outcomes through complementary specialization.
We examine how technological overlap and alliance experience – widely recognized antecedents of external knowledge utilization – influence the extent of knowledge acquisition and complementary specialization in alliances.
Our results also suggest that the likelihood of an alliance to simultaneously exhibit knowledge acquisition and complementary specialization improves as partnering firms' technological overlap and alliance experience increase.
Furthermore, complementary specialization was also significant (H2' = 0.37±0.10, all P<0.001).
All analyses on complementary specialization were made in R with the package bipartite.
Ultimately, the combination of high nestedness, low complementary specialization, and low clustering should lead to high robustness in bat-fruit networks, as has been suggested for other kinds of mutualistic networks [28].
Intermediate nestedness, low complementary specialization and low modularity seem to lead to a cohesive structure with a balance between redundancy within modules and complementarity among modules, because some key bat genera are responsible mainly for dispersing their preferred plant genera, and so each network is composed of modules with a phylogenetic signal.
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