Knowledge Creation and Diffusion in a Multi-Regional Setting: Conceptual Foundations for an Agent-Based Model

Network externalities (where the value of a practice is a function of network alters that have already adopted the practice) are mechanisms that exacerbate social inequality under the condition of homophily (where advantaged individuals poised to be primary adopters are socially connected to other advantaged individuals). The authors use an agent-based model of diffusion on a real-life population for empirical illustration and, thus, do not consider consolidation (correlation between traits), a population parameter that shapes network structure and diffusion. Using an agent-based model, this article shows that prior findings linking homophily to segregated social ties and to differential diffusion outcomes are contingent on high levels of consolidation. Homophily, under low consolidation, is not sufficient to exacerbate existing differences in adoption probabilities across groups and can even end up alleviating intergroup inequality by facilitating diffusion.

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Regional Knowledge Creation and R&D Collaboration in Europe: Specification of an Empirical Agent-Based Model

SSRN Electronic Journal ◽

10.2139/ssrn.3456085 ◽

2018 ◽

Author(s):

Martina Duenser ◽

Manfred F. Paier ◽

Astrid Unger ◽

Michael J. Barber ◽

Thomas Scherngell

Keyword(s):

Knowledge Creation ◽

Agent Based Model ◽

Agent Based

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Knowledge Creation, Growth, and Transfer within Industrial Networks of Practices

Relational Methodologies and Epistemology in Economics and Management Sciences - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-4666-9770-6.ch012 ◽

2016 ◽

pp. 313-347

Author(s):

Lucio Biggiero ◽

Mario Basevi

Keyword(s):

Absorptive Capacity ◽

Knowledge Creation ◽

Real Data ◽

Industrial Cluster ◽

Competitive Advantages ◽

Agent Based ◽

Scale Free ◽

Industrial Networks ◽

Structural Variables ◽

And Diffusion

In this chapter we test the hypothesis that uneven links distributions and uneven absorptive capacity between an industrial cluster members provide some kind of competitive advantages. Through an agent-based model has been built and calibrated on real data taken from an aerospace industrial cluster, that hypothesis is contrasted against the normal, the uniform, and the U-shaped distribution. The focus of the model is on knowledge variables, agents' learning capacities, and structural variables, like firms size and proximity. Physical production is not considered, excepted for its degree of complexity, which determines also the degree of knowledge complexity. This work shows that, actually, the best performance in terms of cluster knowledge creation, growth and diffusion is obtained when firms connectedness and absorptive capacity are distributed in a scale-free way. More generally, the more unbalanced are these two variables (especially absorptive capacity), the better is knowledge performance. These results are rather robust, and obtained while keeping all other variables very balanced at the beginning of each simulation.

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