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DC Field | Value | Language |
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dc.contributor.author | Sarkar, Sumit | |
dc.contributor.author | Chakraborty, Soumyakanti | |
dc.date.accessioned | 2021-08-26T06:03:27Z | - |
dc.date.available | 2021-08-26T06:03:27Z | - |
dc.date.issued | 2019 | |
dc.identifier.uri | https://www.igi-global.com/article/stakeholder-fairness-under-an-induced-veil-of-ignorance/219239 | |
dc.identifier.uri | https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1115 | - |
dc.description | Sumit Sarkar, XLRI, Jamshedpur, India; Soumyakanti Chakraborty, Department of Management Information Systems, Indian Institute of Management, Calcutta, India | |
dc.description | DOI - 10.4018/IJSDS.2019010105 | |
dc.description.abstract | John Rawls introduced the �veil of ignorance' in social contract theory to bring about a common conception of justice, and hypothesized that it will enable rational individuals to choose distributive shares on basis of �maximin' principle. R. E. Freeman conceptualised stakeholder fairness using the Rawlsian �veil of ignorance'. In contrast to Rawls' theory, John Harsanyi postulated that rational individuals behind the �veil of ignorance' will choose allocation to maximise expected utility. This article investigates how subjects choose allocations behind the �veil of ignorance,' in a laboratory experiment, and interprets the findings in light of stakeholder fairness. The �veil of ignorance' was induced on randomly paired and mutually anonymous subjects, who were asked to choose allocations in a simultaneous move discrete choice Nash demand game. Both �maximin' principle and expected utility maximisation was found to be used by the subjects. Choice of allocations where no one is worse off vis-�-vis status quo was salient. This is consistent with Freeman's Principle of Governance | |
dc.publisher | AR-IIMC | |
dc.publisher | International Journal of Strategic Decision Sciences (IJSDS) | |
dc.relation.ispartofseries | 10(1) | |
dc.title | Stakeholder Fairness under an Induced 'Veil of Ignorance': Findings From a Laboratory Experiment | |
dc.type | Article | |
Appears in Collections: | Management Information Systems |
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