Abstract
Purpose
In 1988, Donald Cressey published a previously overlooked article. According to Cressey, there was a lack in the agenda of corporate crime research concerning theory and conceptual precision of what exactly the scientific object was and how it could reinforce the understanding of white-collar criminality. Cressey stated the idea that a fictitious person, such as a corporation, upon which were bestowed properties such as a will of its own (intentions and motivations) and a consciousness to act morally and ethically have a responsibility to follow the order of law, leds to a fundamental theoretical problem in terms of discovering the causes of crimes committed by such a fictitious person. I follow this line of thought about the arguments made by representatives of corporate crime. Specifically, I follow the concept of “decoupling,” by using various techniques of formal logic. The conclusion is that the concept of corporate crime is a logical contradiction (an eternal false statement), but the research has one analytical point which must be incorporated into the research of white-collar criminality: how structural conditions of a corporation’s policy and strategy “produce” or influence the individuals within the corporation to make decisions. The aim of the paper is to prove on logical grounds that the direction of research on corporate crime is on the wrong track to find the truth (basic elements and mechanisms) about white-collar crime.
Design/methodology/approach
Using formal logic, specifically modal logic.
Findings
The concept “corporate crime” is a logical contradiction.
Research limitations/implications
Concerning the conclusion, the implications has to be that corporate crime is a misleading concept in the research agenda of white-collar crime.
Practical implications
The authors have to reconsider the whole research field of corporate crime research.
Originality/value
To best of my knowledge, no one has before done a critic of corporate crime concept by formal logic.
Subject
Law,General Economics, Econometrics and Finance
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