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A model of dynamic rewiring and knowledge exchange in R&D networks | | Mario Vincenzo Tomasello
; Claudio Juan Tessone
; Frank Schweitzer
; | | Date: |
7 May 2015 | | Abstract: | This paper investigates the process of knowledge exchange in inter-firm
Research and Development (R&D) alliances by means of an agent-based model.
Extant research has pointed out that firms select alliance partners considering
both network-related and network-unrelated features (e.g. social capital versus
complementary knowledge stocks). In our agent-based model, firms are located in
a metric knowledge space. The interaction rules incorporate an exploration
phase and a knowledge transfer phase, during which firms search for a new
partner and then evaluate whether they can establish a profitable alliance to
mutually exchange their knowledge stocks. The model parameters determining the
overall system properties are the rate at which alliances form and disappear
and the agents’ interaction radius. Next, we define a novel indicator of
performance, based on the distance traveled by the firms in the knowledge
space. Remarkably, we find that - depending on the alliance formation rate and
the interaction radius - firms tend to cluster around one or a few attractors
in the knowledge space, whose position is an emergent property of the system.
And, more importantly, we find that there exist optimal values for both
parameters maximizing the network performance. | | Source: | arXiv, 1505.1756 | | Services: | Forum | Review | PDF | Favorites | |
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