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Uncertainty reduces rejections of unfair offers in the ultimatum game

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Abstract

Considerable Ultimatum Game studies suggest that individuals tend to reject unfair offers even at the cost of personal financial loss. Different from prior studies in which the ultimatum game allocations are often certain (e.g., $2: $8), the current research examines whether uncertain allocations (e.g., $1–$3: $7–$9) alter the rejections in two incentive compatible studies. That is, whether unfair offers influence rejection rates in ultimatum game decisions. Study 1 showed that decision makers are generally less likely to reject unfair offers when they are uncertain (between $1 and $3) rather than certain ($2). Study 2 replicated the effect and further revealed a boundary: when the range of the uncertain offer includes zero such that there is a possibility of receiving nothing, decision makers exhibited similar rejection rates for uncertain and certain unfair offers.

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Data Availability

All the data in the current study are available from the first author upon request.

Notes

  1. We used a deceptive design in the current study for three reasons: (1) Because we also examined the offer size as the moderator, and it is important to have an equal sample size at each offer level. Offers from a predetermined algorithm instead of human proposers ensure equal distribution at all offer sizes. (2) The primary focus of the current study is uncertain offers’ influence on rejection decisions of the recipients, but not on the proposers’ allocation decisions, including human partners would double the required sample size and thus cause potential wastes of resources. (3) In the current study, telling recipients that offers were from a human partner did not confound the main effect of offer uncertainty. Therefore, we consider the deception was necessary. We did not seek IRB approval because there was no Institutional Review Board in the authors’ colleges/schools. However, regarding the nature of the current research, we consider the deception poses minimal risk to participants and causes no physical or emotional harm.

  2. At the end of the experiment, all participants were debriefed that the offers were actually from a predetermined algorithm, and they could decide whether to have their data withdrawn from the study. No participants asked to withdraw their data.

  3. When time was up and no decision was made, that trial was recorded as missing value in the dataset.

  4. We used G*Power 3.1.9.7 to conduct the sensitive power analysis (F-tests; ANOVA: Repeated measures, between factors; Effect size specification: as in Cohen).

  5. We also compared the rejection rates in the current research to prior literature (online appendix).

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Funding

This research was supported by the National Natural Science Foundation of China (71502080) to the second author.

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Authors and Affiliations

  1. School of Management, Xi’an Jiaotong University, Xi’An, China

    Yuanyuan Liu

  2. Information System and Management Engineering, College of Business, Southern University of Science and Technology, Shenzhen, China

    Yuanyuan Jamie Li

  3. School of Management, Xi’an Jiaotong University, Xi’An, China

    Huili Zhang

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  1. Yuanyuan Liu
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Correspondence to Yuanyuan Jamie Li.

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All experimental procedures conducted in the current study involving human participants were in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments.

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Liu, Y., Li, Y.J. & Zhang, H. Uncertainty reduces rejections of unfair offers in the ultimatum game. Curr Psychol 42, 17977–17984 (2023). https://doi.org/10.1007/s12144-022-03004-2

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