Abstract
A discrepancy between prior expectation and posterior experience evokes emotions, such as surprise, satisfaction, and disappointment, affecting the perceived product and service value. Furthermore, expectation affects perceived experience. This psychological phenomenon, called the expectation effect, is a key to designing the affective experience of a product and a service. Experimental findings of this effect exist in a variety of disciplines. In this chapter, the author presents computational models of the expectation effect using information theory and neural coding principles. These models estimate its occurrence conditions, its intensity, and two patterns of the expectation effect, i.e., contrast and assimilation. The author discusses an essential mechanism of human perceptions involving prior expectations based on simulation results of the models.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Number 15K05755, the Design Innovation (DI) Laboratory at the University of Tokyo (UTokyo) and its corporate partners. We would like to thank to Professor Tamotsu Murakami, Professor Satoshi Nakagawa, Dr. Kazutaka Ueda, Mr. Kenji Takatsuji, Mr. Natsu Mikami, and members of the Design Engineering Laboratory at UTokyo for supporting this project.
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Yanagisawa, H. (2016). Expectation Effect Theory and Its Modeling. In: Fukuda, S. (eds) Emotional Engineering Volume 4. Springer, Cham. https://doi.org/10.1007/978-3-319-29433-9_11
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DOI: https://doi.org/10.1007/978-3-319-29433-9_11
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