Abstract
Behavioral economics has shown that in many situations, people’s behavior differs from what is predicted by simple traditional utility-maximization economic models. It is therefore desirable to be able to accurately describe people’s actual behavior. In some cases, the difference from the traditional models is caused by bounded rationality—our limited ability to process information and to come up with a truly optimal solutions. In such cases, predicting people’s behavior is difficult. In other cases, however, people actually optimize—but the actual expression for utility is more complicated than in the traditional models. In such case, it is, in principle, possible to predict people’s behavior. In this paper, we show that two phenomena—reciprocity and temptation—can be explained by optimizing a complex utility expression. We hope that this explanation will eventually lead to accurate prediction of these phenomena.
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Acknowledgements
This work was supported in part by the National Science Foundation grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science) and HRD-1242122 (Cyber-ShARE Center of Excellence). It was also supported by the program of the development of the Scientific-Educational Mathematical Center of Volga Federal District No. 075-02-2020-1478.
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Bokati, L., Kosheleva, O., Kreinovich, V., Thach, N.N. (2022). Economics of Reciprocity and Temptation. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Credible Asset Allocation, Optimal Transport Methods, and Related Topics. TES 2022. Studies in Systems, Decision and Control, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-030-97273-8_3
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