Networks in the balance: an agent-based model of optimal exploitation

Fernando Anjos, Ray Reagans

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Using an agent-based simulation, we illustrate how goal-seeking behavior affects network formation, learning, and performance. Our organization has one manager, who decides where to invest financial capital; individual workers, who decide where to work and prefer projects with larger budgets; and projects, which vary in quality. Our manager discovers high-quality projects from interactions with workers and allocates more capital to high-quality projects. When given an opportunity, our workers move to bigger-budget projects. We let our manager vary in terms of how much she exploits what she learns and allow our workers vary in terms of how sensitive they are to differences in capital. Our results highlight a contingency which shapes how goal-seeking behavior affects learning. The contingency is network fragility. Fragile connections decay quickly when individuals are not working together, while robust relationships decay more slowly. When relationships are robust, exploitation by our manager leads to a dense organizational network, improving information quality, and performance. Decisions by self-interested individuals (our manager and our workers) produce a virtuous learning cycle. When relationships are fragile, exploitation by our manager produces a sparse network, reducing information quality, and undermining performance. When network connections are fragile, the manager must find the right balance of exploitation and exploration, a balance which limits the rate at which workers move from one project to the next, allowing the manager to exploit some of what she knows, without undermining the very network which allows for useful information to be obtained.

Original languageEnglish
Article number20
JournalJournal of Organization Design
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020

Keywords

  • Exploitation
  • Exploration
  • Learning
  • Mobility
  • Organizational networks

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