Simulation of Corruption Decisions—An Agent-Based Approach

Richard Kasa (), Gábor Réthi, György Hauber and Krisztina Szegedi
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Richard Kasa: Department of Management, Budapest Business School, H-1055 Budapest, Hungary
Gábor Réthi: Department of Management, Budapest Business School, H-1055 Budapest, Hungary
György Hauber: Department of Management, Budapest Business School, H-1055 Budapest, Hungary
Krisztina Szegedi: Department of International Commerce and Logistics, CESIBUS, Budapest Business School, H-1055 Budapest, Hungary

Sustainability, 2023, vol. 15, issue 3, 1-18

Abstract: Corruption is one of the biggest barriers to sustainable development. Several objectives of the Sustainable Development Goals (SDGs) are directly linked with the fight against corruption, as it has an influence on the achievement of every single development goal. The aim of this research is to examine decision-making patterns in a typical corruption situation. The following research questions have been formulated: (1) what kind of decision-making approaches are effective against partners maintaining different strategies, and how do these relate to certain generations? (2) Is there a difference between the behavior patterns of employees of SMEs, large corporations, and the public sector in a situation that provides the opportunity for corruption? To answer these research questions, an agent-based corruption experiment was conducted, building on the prisoner’s dilemma. The relationship between cooperation and corruption was examined through the analysis of decision-making situations to uncover when and with which partners (artificial agents) the participants first start to cooperate or become corrupt. The results show that there is a significant difference in the propensity to cheat among different generations. Furthermore, the behavior patterns of employees of large corporations, SMEs, and the public sector also show deviation in a corruption situation.

Keywords: sustainability; UN sustainable development goals; corruption; fraud; public procurement; agent-based experiment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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