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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References
Barlow, H. B. (1961). Possible principles underlying the transformation of sensory messages. Sensory Communication, 217-234.
Brayanov, J. B., & Smith, M. A. (2010). Bayesian and “anti-Bayesian” biases in sensory integration for action and perception in the size–weight illusion. Journal of Neurophysiology, 103(3), 1518-1531.
Deliza, R., & MacFie, H. J. H. (1996). The generation of sensory expectation by external cues and its effect on sensory perception and hedonic ratings: a review. Journal of Sensory Studies, 11(2), 103-128.
Demir, E., Desmet, P., & Hekkert, P. (2009). Appraisal patterns of emotions in human-product interaction. International Journal of Design, 3(2), 41-51.
Ernst, M. O., & Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature, 415(6870), 429-433.
Flanagan, J. R., & Beltzner, M. A. (2000). Independence of perceptual and sensorimotor predictions in the size-weight illusion. Nature Neuroscience, 3(7), 737-741. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10862708
Itti, L., & Baldi, P. (2009). Bayesian surprise attracts human attention. Vision Research, 49(10), 1295-1306.
Krippendorff, K. (2005). The semantic turn: A new foundation for design: CRC.
Ludden, G. D. S., Schifferstein, H. N. J., & Hekkert, P. (2012). Beyond surprise: A longitudinal study on the experience of visual-tactual incongruities in products. International Journal of Design, 6(1), 1-10.
Murakami, T., Nakagawa, S., & Yanagisawa, H. (2011). Proposal of “Expectlogy” as design methodology. Paper presented at the International Conference on Engineering Design 2011.
Oliver, R. L. (1977). Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. Journal of Applied Psychology, 62(4), 480-486.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 460-469.
Shannon, C. E., Weaver, W., Blahut, R. E., & Hajek, B. (1949). The mathematical theory of communication (Vol. 117): University of Illinois press Urbana.
Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. The Journal of Marketing, 15-32.
Strange, B. A., Duggins, A., Penny, W., Dolan, R. J., & Friston, K. J. (2005). Information theory, novelty and hippocampal responses: unpredicted or unpredictable? Neural Networks, 18(3), 225-230. doi: http://dx.doi.org/10.1016/j.neunet.2004.12.004
Wei, X.-X., & Stocker, A. (2012). Bayesian Inference with Efficient Neural Population Codes. In A. P. Villa, W. Duch, P. Érdi, F. Masulli, & G. Palm (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2012 (Vol. 7552, pp. 523-530): Springer Berlin Heidelberg.
Yanagisawa, H., & Takatsuji, K. (2015a). Effects of visual expectation on perceived tactile perception: An evaluation method of surface texture with expectation effect. International Journal of Design, 9(1), 39-51.
Yanagisawa, H., & Takatsuji, K. (2015b). Expectation effect of perceptual experience in sensory modality transitions: modeling with information theory. Journal of Intelligent Manufacturing, 1-10. doi:10.1007/s10845-015-1096-7
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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