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Behavioral Business Ethics as a Method for Normative Business Ethics


Lorenzo Sacconi


University of Trento - Department of Economics and Management

Marco Faillo


University of Trento - Faculty of Economics

Pedro Frances-Gomez


affiliation not provided to SSRN

July 2, 2012

EconomEtica, Number 42, July 2012

Abstract:     
This paper aims at discussing the role of behavioral business ethics as a methodological approach that is valuable for the construction of a robust normative foundation for business ethics. In particular, we will focus on experiments – and, to a lesser extent, surveys, field research, and even the study of cognitive and neural mechanisms – as a research method suitable to improve our appraisal and knowledge of the prescriptive side of business ethics. We contend that there are two basic gains from the use of experimental methods in normative business ethics. First, we can improve the psychological realism of normative theory -this goes hand in hand with supporting the new paradigm of the organization, based on a more realistic view of human agency. Second, we can experimentally check some theoretical assumptions about moral reasoning, thus providing quasi-empirical support (or falsification) for particular normative theories.

Number of Pages in PDF File: 28

Keywords: experiments, social contract, realism, reflective equilibrium

JEL Classification: C92, D64, M14

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Date posted: July 25, 2012  

Suggested Citation

Sacconi, Lorenzo, Faillo, Marco and Frances-Gomez, Pedro, Behavioral Business Ethics as a Method for Normative Business Ethics (July 2, 2012). EconomEtica, Number 42, July 2012. Available at SSRN: http://ssrn.com/abstract=2116519 or http://dx.doi.org/10.2139/ssrn.2116519

Contact Information

Lorenzo Sacconi (Contact Author)
University of Trento - Department of Economics and Management ( email )
via Inama 5
I-38100 Trento
Italy
Marco Faillo
University of Trento - Faculty of Economics ( email )
Via Inama 5
I-38100 Trento
Italy
Pedro Frances-Gomez
affiliation not provided to SSRN
Feedback to SSRN (Beta)


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