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Group Decision and Negotiation

, Volume 27, Issue 4, pp 543–571 | Cite as

No Rage Against the Machine: How Computer Agents Mitigate Human Emotional Processes in Electronic Negotiations

  • Marc T. P. Adam
  • Timm Teubner
  • Henner Gimpel
Article
  • 188 Downloads

Abstract

With the proliferation of information technology and artificial intelligence in society, human users have started to engage in social interactions with computer agents. In this study, we conducted a laboratory experiment in which neurophysiological measurements were used to investigate the effect of computer agents on the affective processes and behavior of human negotiators. Participants engaged in alternating-offer bargaining over the partition of a pie with either human or computer counterparts and under different levels of urgency to reach an agreement. Overall, our data show that the subjects claimed significantly higher proportions for themselves when they made opening offers to computer agents than when bargaining with human counterparts, regardless of the degree of urgency in the negotiation. However, when the subjects responded to computer-issued offers the picture was more complex. Whereas under high-level urgency, the subjects were more likely to accept offers made by computer agents than by human counterparts, we observed the opposite effect for low-level urgency, where they were less likely to accept the offers of computer agents. In combination, these behavioral patterns lead to the use of computer agents yielding an increase in economic efficiency. Further, the subjects exhibited less emotionally charged behavior when facing computer agents than when facing human counterparts, as the intensity of affective processes was lower and the relationship between arousal and offer acceptance was observable only when the counterparts were human. The results of our study shed light on the potential benefits and intricacies of employing computer agents in electronic negotiations.

Keywords

Bargaining Computer agents Emotions Experiment 

Notes

Acknowledgements

The authors would like to thank Rebecca Dorner, Hanns-Maximilian Schmidt, and Markus Weiler for their invaluable help with preparing and conducting the experiments.

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.The University of NewcastleNewcastleAustralia
  2. 2.TU BerlinBerlinGermany
  3. 3.University of AugsburgAugsburgGermany

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