Degree-Degree Correlation in Networks with Preferential Attachment Based Growth

Mironov, Sergei V.; Sidorov, Sergei; Malinskii, Igor

doi:10.1007/978-3-030-81854-8_5

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…The value of γ is 3 for the Barabasi-Albert model. It should be noted that simply preferential attachment is not enough to obtain the scale-free property, as growth is also required [28]. Both of these can be expected in real-life small-to mid-sized organizations that are increasing in business size and sales, and, therefore, number of employees.…”

Section: Scale-free Networkmentioning

confidence: 99%

Investigating the Effect of Organization Structure and Cognitive Profiles on Engineering Team Performance Using Agent-Based Models and Graph Theory

Estes,

Pandey

2023

Mathematics

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In large engineering firms, most design projects are undertaken by teams of individuals. From the perspective of senior management, the overall project team must maintain scheduling, investment and return on the investment discipline while solving technical problems. Various tools exist in systems engineering (SE) that can reflect the value provided by the resources invested; however, the involvement of human decision makers complicates most types of analyses. A critical ingredient in this challenge is the interplay of the cognitive attributes of team members and the relationships that exist between them. This aspect has not been fully addressed in the literature, rendering many studies relatively oblivious to team dynamics and organization structures. To this end, we propose a framework to incorporate organization structure using a graph representation. This is then used to inform an agent-based model where team dynamics are simulated to understand the effects of cognitive attributes and team member relationships. In this work, we aim to understand team dynamics in the context of product development. The organization is modeled using the Barabasi–Albert scale-free network. The information regarding member relationships can be acquired through graph metrics such as the various centrality measures associated with the members and the distance between them. This is then used to model the dynamics of the members when they work on a technical problem, in conjunction with their other cognitive attributes. We present some results and discuss avenues for future work.

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Section: Scale-free Networkmentioning

confidence: 99%