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An Agent-Based Model of Administrative Corruption in Hierarchical Organisations

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Corruption is a familiar and pressing problem in the performance of administrative bureaucracies. Changing the organisational structure is one way ventured to combat corrupt practices within a hierarchical organisation. Previous works have studied organisational change from various lenses, including equation-based modelling. We address the question of what level of hierarchy is optimal in such an organisation by means of agent-based simulation. We argue that agent-based models are uniquely suited for the exploratory modelling of corruption due to their capturing of localised, individualised behaviours. Our preliminary findings are that a less hierarchical organisational structure: 1) tend to lead to less corrupt acts committed, and 2) tends to lead to more societal welfare generated – however, 3) less corruption and more societal welfare do not always go hand in hand. We begin to reconcile these seemingly paradoxical results using theories from developmental economics.

Original languageEnglish
Title of host publicationMulti-Agent-Based Simulation 26 - 26th International Workshop, MABS 2025, Revised Selected Papers
EditorsAlicia Vidler, Samarth Swarup
PublisherSpringer
Pages77-88
Number of pages12
ISBN (Print)9783032163271
DOIs
Publication statusPublished - 2026
Event26th International Workshop on Multi-Agent-Based Simulation, MABS 2025 - Detroit, United States
Duration: 19 May 202519 May 2025

Publication series

NameLecture Notes in Computer Science
Volume16227 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Workshop on Multi-Agent-Based Simulation, MABS 2025
Country/TerritoryUnited States
CityDetroit
Period19/05/2519/05/25

Keywords

  • Administrative Corruption
  • Agent-Based Models
  • Collusion
  • Complex Adaptive Systems
  • Mesa
  • Organisation Structure

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