Computational Model Library

Displaying 4 of 4 results computational organization theory clear search

A generalized organizational agent- based model (ABM) containing both formal organizational hierarchy and informal social networks simulates organizational processes that occur over both formal network ties and informal networks.

Peer reviewed Emergence of Organizations out of Garbage Can Dynamics

Guido Fioretti | Published Monday, April 20, 2020 | Last modified Sunday, April 26, 2020

The Garbage Can Model of Organizational Choice (GCM) is a fundamental model of organizational decision-making originally propossed by J.D. Cohen, J.G. March and J.P. Olsen in 1972. In their model, decisions are made out of random meetings of decision-makers, opportunities, solutions and problems within an organization.
With this model, these very same agents are supposed to meet in society at large where they make decisions according to GCM rules. Furthermore, under certain additional conditions decision-makers, opportunities, solutions and problems form stable organizations. In this artificial ecology organizations are born, grow and eventually vanish with time.

Peer reviewed The Garbage Can Model of Organizational Choice

Guido Fioretti | Published Monday, April 20, 2020 | Last modified Thursday, April 23, 2020

The Garbage Can Model of Organizational Choice is a fundamental model of organizational decision-making originally proposed by J.D. Cohen, J.G. March and J.P. Olsen in 1972. In the 2000s, G. Fioretti and A. Lomi presented a NetLogo agent-based interpretation of this model. This code is the NetLogo 6.1.1 updated version of the Fioretti-Lomi model.

Perceived Scientific Value and Impact Factor

Davide Secchi Stephen J Cowley | Published Wednesday, April 12, 2017 | Last modified Monday, January 29, 2018

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept