Quantification of fairness bias in relation to decisions using a relativistic fairness-equity model

Authors

  • Nicoladie Tam Dept. of Biological Sciences University of North Texas Denton, Texas 76203

DOI:

https://doi.org/10.14738/assrj.14.292

Keywords:

Fairness bias, equity, egalitarianism, monetary gain, ultimatum game, decision

Abstract

This study quantifies the fairness bias in relation to decision by a stimulus-response function using a relativistic fairness-equity model.  The interrelationship between fairness and decision is quantified by using an Ultimatum Game (UG) experimental paradigm, in which an amount of money is shared between two parties, while the human subjects are asked to accept or reject the share.  The results showed that the fairness perception is shifted upward (toward a higher positive fairness baseline in the y-intercept of the stimulus-response function) for acceptance trials, without changing the slope (which corresponds to the fairness sensitivity).  On the other hand, the fairness perception is shifted downward (toward a negative fairness baseline in the y-intercept) for the rejection trials.  The analysis also showed that the fairness crossover point is shifted to the left for the acceptance trials, while the fairness crossover point is shifted to the right for the rejection trials.  This suggests that human subjects were more lenient to fairness when they considered slightly inequitable offers as fair in their decision to accept the offers (quantified by the fairness crossover point being shifted to the left for the acceptance trials).  On the other hand, it suggests that they were greedy when they considered hyper-equitable offers as unfair (quantified by the fairness crossover point being shifted to the right for the rejection trials).  The analysis also showed that there is a singularity point, in which the most equitable offer (even-split) is always considered as the fairest, even when they rejected the offers.  This absolute equity is rated as the fairest (even fairer than any of the hyper-equitable offers) independent of whether the subjects decided to accept or reject the offers.  These results suggested that when human subjects decided to accept or reject the offer, they included both self-regarding and other-regarding concerns, by using both self-centered and other-centered frames of reference in assessing fairness.  The inclusiveness of both parties in the fairness consideration provides an optimal solution to maximize the gains for both parties at the most equitable offer (even-split) without creating conflict-of-interest.  The changes in fairness perception are quantified by the shifting of the stimulus-response curve up/down (changing the fairness baseline) or left/right (changing the fairness leniency), without changing the slope (the fairness sensitivity), when the decision is made to accept or reject the offers.

Author Biography

Nicoladie Tam, Dept. of Biological Sciences University of North Texas Denton, Texas 76203

Professor Nicoladie Tam has research interests in computational neuroscience, neurophysiology, neuropsychology, spike train analysis, emotional processing, decision, cognition, motor control, neuro-prosthetics, exercise neurophysiology, gender dimorphism, EEG, near-infrared brain imaging.

more about her research

Her list of publications can be seen at this link

References

Singer, T., H.D. Critchley, and K. Preuschoff, A common role of insula in feelings, empathy and uncertainty. Trends Cogn Sci, 2009. 13(8): p. 334-340.

Singer, T., et al., Empathic neural responses are modulated by the perceived fairness of others. Nature, 2006. 439(7075): p. 466-469.

Tabibnia, G., A.B. Satpute, and M.D. Lieberman, The sunny side of fairness: preference for fairness activates reward circuitry (and disregarding unfairness activates self-control circuitry). Psychol Sci, 2008. 19(4): p. 339-347.

Pillutla, M.M. and J.K. Murnighan, Unfairness, Anger, and Spite: Emotional Rejections of Ultimatum Offers. Org Behav Human Decis Proc, 1996. 68(3): p. 208-224.

Güroğlu, B., W. van den Bos, and E.A. Crone, Fairness considerations: increasing understanding of intentionality during adolescence. J Exp Child Psychol, 2009. 104(4): p. 398-409.

Güroğlu, B., et al., Unfair? It depends: neural correlates of fairness in social context. Soc Cogn Affect Neurosci, 2010. 5(4): p. 414-423.

Seip, E.C., W.W. van Dijk, and M. Rotteveel, On hotheads and Dirty Harries: the primacy of anger in altruistic punishment. Ann N Y Acad Sci, 2009. 1167: p. 190-196.

Sanfey, A.G., et al., The neural basis of economic decision-making in the Ultimatum Game. Science, 2003. 300(5626): p. 1755-1758.

Rilling, J.K., B. King-Casas, and A.G. Sanfey, The neurobiology of social decision-making. Curr Opin Neurobiol, 2008. 18(2): p. 159-165.

Reuben, E. and F. van Winden, Fairness perceptions and prosocial emotions in the power to take. J Econ Psych, 2010. 31: p. 908–922.

Fehr, E. and S. Gächter, Altruistic punishment in humans. Nature, 2002. 415(6868): p. 137-40.

Takagishi, H., et al., Theory of mind enhances preference for fairness. J Exp Child Psychol, 2010. 105(1-2): p. 130-137.

Güth, W., R. Schmittberger, and B. Schwarze, An experimental analysis of ultimatum bargaining. J Econ Behav Organization, 1982. 3(4): p. 367–388.

Ochs, J. and A.E. Roth, An experimental study of sequential bargaining. Am Econ Review, 1989. 79(3): p. 355–384.

Rabin, M., Incorporating fairness into game theory and economics. Am Econ Review, 1993. 83(5): p. 1281–1302.

Fehr, E. and K.M. Schmidt, A theory of fairness, competition, and cooperation. Quarterly J Econ, 1999. 114: p. 817–868.

Falk, A., E. Fehr, and U. Fuschbacher, On the nature of fair behavior. Econ Inquiry, 2003. 41(1): p. 20–26.

Konow, J., Which is the fairest one of all? A positive analysis of justice theories. J Econ Lit, 2003. 41: p. 1186–1239.

Rawls, J., A theory of justice1971, Cambridge: Harvard University Press.

Brosnan, S.F. and F.B. De Waal, Monkeys reject unequal pay. Nature, 2003. 425(6955): p. 297-299.

Page, K.M. and M.A. Nowak, A generalized adaptive dynamics framework can describe the evolutionary Ultimatum Game. J Theor Biol, 2001. 209(2): p. 173-179.

Braun, D.A., P.A. Ortega, and D.M. Wolpert, Nash equilibria in multi-agent motor interactions. PLoS Comput Biol, 2009. 5(8): p. e1000468.

Killingback, T. and E. Studer, Spatial Ultimatum Games, collaborations and the evolution of fairness. Proc Biol Sci, 2001. 268(1478): p. 1797-1801.

Nowak, M.A., K.M. Page, and K. Sigmund, Fairness versus reason in the ultimatum game. Science, 2000. 289(5485): p. 1773-1775.

Page, K.M., M.A. Nowak, and K. Sigmund, The spatial ultimatum game. Proc Biol Sci, 2000. 267(1458): p. 2177-2182.

Sigmund, K., C. Hauert, and M.A. Nowak, Reward and punishment. Proc Natl Acad Sci U S A, 2001. 98(19): p. 10757-10762.

Duan, W.Q. and H.E. Stanley, Fairness emergence from zero-intelligence agents. Phys Rev E Stat Nonlin Soft Matter Phys, 2010. 81(2 Pt 2): p. 026104.

Li, X. and L. Cao, Largest Laplacian eigenvalue predicts the emergence of costly punishment in the evolutionary ultimatum game on networks. Phys Rev E Stat Nonlin Soft Matter Phys, 2009. 80(6 Pt 2): p. 066101.

Sánchez, A. and J.A. Cuesta, Altruism may arise from individual selection. J Theor Biol, 2005. 235(2): p. 233-40.

Bolton, G.E., A comparative model of bargaining: theory and evidence. Am Econ Rev, 1991. 81: p. 1096–1136.

Tam, D.N., Contributing factors in judgment of fairness by monetary value. BMC Neuroscience, 2011. 12(Suppl 1): p. P329.

Tam, D.N., Quantification of fairness bias by a Fairness-Equity Model. BMC Neuroscience, 2011. 12(Suppl 1): p. P327.

Tam, N.D., Quantification of fairness perception by including other-regarding concerns using a relativistic fairness-equity model. Advances in Social Sciences Research Journal, submitted.

von Neumann, J., O. Morgenstern, and A. Rubinstein, Theory of games and economic behavior1953, Princeton, NJ: Princeton University Press.

Camerer, C., Behavioral game theory: Experiments in strategic interaction2003: Princeton University Press.

Kagel, J.H. and A.E. Roth, The handbook of experimental economics1995: PRINCETON University Press.

Rilling, J.K., et al., The neural correlates of theory of mind within interpersonal interactions. Neuroimage, 2004. 22(4): p. 1694-703.

Takagishi, H., et al., Neural correlates of the rejection of unfair offers in the impunity game. Neuro Endocrinol Lett, 2009. 30(4): p. 496-500.

Yamagishi, T., et al., The private rejection of unfair offers and emotional commitment. Proc Natl Acad Sci U S A, 2009. 106(28): p. 11520-11523.

Singer, T. and N. Steinbeis, Differential roles of fairness- and compassion-based motivations for cooperation, defection, and punishment. Ann N Y Acad Sci, 2009. 1167: p. 41-50.

Komorita, S.S., Attitude content, intensity, and the neutral point on a Likert scale. J Soc Psychol, 1963. 61: p. 327-34.

Civai, C., et al., Are irrational reactions to unfairness truly emotionally-driven? Dissociated behavioural and emotional responses in the Ultimatum Game task. Cognition, 2010. 114(1): p. 89-95.

Koenigs, M. and D. Tranel, Irrational economic decision-making after ventromedial prefrontal damage: evidence from the Ultimatum Game. J Neurosci, 2007. 27(4): p. 951-6.

Bolton, G.E. and R. Zwick, Anonymity versus punishment in ultimatum bargaining. Games Econ Behav, 1995. 10: p. 95–121.

Camerer, C. and R.H. Thaler, Anomalies: Ultimatums, dictators, and manner. J Econ Persp, 1995. 9: p. 209–219.

Grinband, J., J. Hirsch, and V.P. Ferrera, A neural representation of categorization uncertainty in the human brain. Neuron, 2006. 49(5): p. 757-63.

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Published

2014-07-28

How to Cite

Tam, N. (2014). Quantification of fairness bias in relation to decisions using a relativistic fairness-equity model. Advances in Social Sciences Research Journal, 1(4), 169–178. https://doi.org/10.14738/assrj.14.292