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We develop an agent-based model to reproduce the size distribution of R\&Dalliances of firms. Agents are uniformly selected to initiate an alliance andto invite collaboration partners. These decide about acceptance based on anindividual threshold that is compared with the utility expected from joiningthe current alliance. The benefit of alliances results from the fitness of theagents involved. Fitness is obtained from an empirical distribution of agent'sactivities. The cost of an alliance reflects its coordination effort. Two freeparameters $a_{c}$ and $a_{l}$ scale the costs and the individual threshold. Ifinitiators receive $R$ rejections of invitations, the alliance formation stopsand another initiator is selected. The three free parameters $(a_{c},a_{l},R)$are calibrated against a large scale data set of about 15,000 firms engaging inabout 15,000 R\&D alliances over 26 years. For the validation of the model wecompare the empirical size distribution with the theoretical one, usingconfidence bands, to find a very good agreement. As an asset of our agent-basedmodel, we provide an analytical solution that allows to reduce the simulationeffort considerably. The analytical solution applies to general forms of theutility of alliances. Hence, the model can be extended to other cases ofalliance formation. While no information about the initiators of an alliance isavailable, our results indicate that mostly firms with high fitness are able toattract newcomers and to establish larger alliances.

Modeling the formation of R\&D alliances: An agent-based model with empirical validation