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Response time and click position: cheap indicators of preferences

Published online by Cambridge University Press:  01 January 2025

Fadong Chen*
Affiliation:
Department of Economics, University of Konstanz, Universitätsstr. 10, 78457 Konstanz, Germany Thurgau Institute of Economics, Hauptstr. 90, 8280 Kreuzlingen, Switzerland Graduate School of Decision Science, University of Konstanz, Universitätsstr. 10, 78457 Konstanz, Germany
Urs Fischbacher*
Affiliation:
Department of Economics, University of Konstanz, Universitätsstr. 10, 78457 Konstanz, Germany Thurgau Institute of Economics, Hauptstr. 90, 8280 Kreuzlingen, Switzerland

Abstract

This paper investigates how process data like response time and click position relates to economic decisions. We use a social value orientation experiment, which can be considered as a prototypical multi-attribute decision problem. We find that in the social value orientation task more individualistic subjects have shorter response times than prosocial subjects. Individualistic subjects click more often on their own payoffs than on the others’ payoffs, and they click more often on their own payoffs than prosocial subjects. Moreover, the response time information and the click position information are complementary in explaining subjects’ preferences. These results show that response times and click positions can be used as indicators of people’s preferences.

Type
Original Paper
Copyright
Copyright © Economic Science Association 2016

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Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s40881-016-0026-6) contains supplementary material, which is available to authorized users.

References

Achtziger, A., Alós-Ferrer, C. (2014). Fast or rational? A response-times study of Bayesian updating. Management Science, 60(4), 923938. 10.1287/mnsc.2013.1793CrossRefGoogle Scholar
Ackermann, K. A., Fleiß, J., Murphy, R. O. (2016). Reciprocity as an individual difference. Journal of Conflict Resolution, 60(2), 340367. 10.1177/0022002714541854CrossRefGoogle Scholar
Brocas, I., Carrillo, J. D., Wang, S. W., Camerer, C. F. (2014). Imperfect choice or imperfect attention? Understanding strategic thinking in private information games. Review of Economic Studies, 81(3), 944970. 10.1093/restud/rdu001CrossRefGoogle Scholar
Chen, F., & Fischbacher, U. (2015). Cognitive processes of distributional preferences: A response time study. TWI Working Paper.Google Scholar
Evans, A. M., Dillon, K. D., Rand, D. G. (2015). Fast but not intuitive, slow but not reflective: Decision conflict drives reaction times in social dilemmas. Journal of Experimental Psychology: General, 144(5), 951966. 10.1037/xge0000107CrossRefGoogle Scholar
Fiedler, S., Glöckner, A., Nicklisch, A., Dickert, S. (2013). Social value orientation and information search in social dilemmas: An eye-tracking analysis. Organizational Behavior and Human Decision Processes, 120(2), 272284. 10.1016/j.obhdp.2012.07.002CrossRefGoogle Scholar
Fischbacher, U. (2007). z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171178. 10.1007/s10683-006-9159-4CrossRefGoogle Scholar
Greiner, B. (2015). Subject pool recruitment procedures: Organizing experiments with ORSEE. Journal of the Economic Science Association, 1(1), 114125. 10.1007/s40881-015-0004-4CrossRefGoogle Scholar
Guo, F., Li, L., & Faloutsos, C. (2009). Tailoring click models to user goals. Paper read at Proceedings of the 2009 workshop on Web Search Click Data.CrossRefGoogle Scholar
Hutcherson, C. A., Bushong, B., Rangel, A. (2015). A neurocomputational model of altruistic choice and its implications. Neuron, 87(2), 451462. 10.1016/j.neuron.2015.06.031CrossRefGoogle ScholarPubMed
Jiang, T., Potters, J., & Funaki, Y. (2016). Eye tracking social preferences. Journal of Behavioral Decision Making, 29, 157168.CrossRefGoogle Scholar
Kieslich, P. J., Hilbig, B. E. (2014). Cognitive conflict in social dilemmas: An analysis of response dynamics. Judgment & Decision Making, 9(6), 510522.CrossRefGoogle Scholar
Koop, G. J., Johnson, J. G. (2011). Response dynamics: A new window on the decision process. Judgment & Decision Making, 6(8), 750758.CrossRefGoogle Scholar
Krajbich, I., Armel, C., Rangel, A. (2010). Visual fixations and the computation and comparison of value in simple choice. Nature Neuroscience, 13(10), 12921298. 10.1038/nn.2635CrossRefGoogle ScholarPubMed
Krajbich, I., Bartling, B., Hare, T., Fehr, E. (2015). Rethinking fast and slow based on a critique of reaction-time reverse inference. Nature Communications, 6, 7455. 10.1038/ncomms8455CrossRefGoogle ScholarPubMed
Krajbich, I., Oud, B., Fehr, E. (2014). Benefits of neuroeconomic modeling: new policy interventions and predictors of preference. American Economic Review, 104(5), 501506. 10.1257/aer.104.5.501CrossRefGoogle Scholar
Liebrand, W. B. G., McClintock, C. G. (1988). The ring measure of social values: A computerized procedure for assessing individual differences in information processing and social value orientation. European Journal of Personality, 2(3), 217230. 10.1002/per.2410020304CrossRefGoogle Scholar
Liu, J., Dolan, P., & Pedersen, E. R. (2010). Personalized news recommendation based on click behavior. Paper read at Proceedings of the 15th international conference on intelligent user interfaces.CrossRefGoogle Scholar
Murphy, R. O., Ackermann, K. A., Handgraaf, M. J. J. (2011). Measuring social value orientation. Judgment & Decision Making, 6(8), 771781.CrossRefGoogle Scholar
Payne, J. W., Bettman, J. R., Johnson, E. J. (1993). The Adaptive Decision Maker, New York: Cambridge University Press 10.1017/CBO9781139173933CrossRefGoogle Scholar
Piovesan, M., Wengström, E. (2009). Fast or fair? A study of response times. Economics Letters, 105(2), 193196. 10.1016/j.econlet.2009.07.017CrossRefGoogle Scholar
Rand, D. G., Greene, J. D., Nowak, M. A. (2012). Spontaneous giving and calculated greed. Nature, 489(7416), 427430. 10.1038/nature11467CrossRefGoogle ScholarPubMed
Reutskaja, E., Nagel, R., Camerer, C. F., Rangel, A. (2011). Search dynamics in consumer choice under time pressure: An eye-tracking study. American Economic Review, 101(2), 900926. 10.1257/aer.101.2.900CrossRefGoogle Scholar
Rubinstein, A. (2007). Instinctive and cognitive reasoning: A study of response times. The Economic Journal, 117(523), 12431259. 10.1111/j.1468-0297.2007.02081.xCrossRefGoogle Scholar
Schulz, J. F., Fischbacher, U., Thöni, C., Utikal, V. (2014). Affect and fairness: Dictator games under cognitive load. Journal of Economic Psychology, 41, 7787. 10.1016/j.joep.2012.08.007CrossRefGoogle Scholar
Smith, A., Bernheim, B. D., Camerer, C. F., Rangel, A. (2014). Neural activity reveals preferences without choices. American Economic Journal: Microeconomics, 6(2), 136.Google ScholarPubMed
Spiliopoulos, L., & Ortmann, A. (2015). The BCD of response time analysis in experimental economics. Working Paper. SSRN 2401325.Google Scholar
Spivey, M. J., Grosjean, M., Knoblich, G. (2005). Continuous attraction toward phonological competitors. Proceedings of the National Academy of Sciences of the United States of America, 102(29), 1039310398. 10.1073/pnas.0503903102CrossRefGoogle ScholarPubMed
Wang, Joseph Tao-Yi, Spezio, Michael, Camerer, Colin F. (2010). Pinocchio’s pupil: Using eyetracking and pupil dilation to understand truth telling and deception in sender-receiver games. American Economic Review, 100(3), 9841007. 10.1257/aer.100.3.984CrossRefGoogle Scholar
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