Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces

Junius Gunaratne, Oded Nov

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Can human-computer interaction help people make informed and effective decisions about their retirement savings? We applied the behavioral economic theories of endowment effect and loss aversion to the design of novel retirement saving user interfaces. To examine effectiveness, we conducted an experiment in which 487 participants were exposed to one of three experimental user interface designs of a retirement saving simulator, representing endowment effect, loss aversion and control. Users made 34 yearly asset allocation decisions. We found that designs informed by the endowment effect and loss aversion theories and which communicated to savers the long-term implications of their asset allocation choices, led users to adjust their behavior, make larger and more frequent asset allocation changes, and achieve their saving goals more effectively.

    Original languageEnglish (US)
    Title of host publicationCHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings
    PublisherAssociation for Computing Machinery
    Pages917-920
    Number of pages4
    Volume2015-April
    ISBN (Print)9781450331456
    DOIs
    StatePublished - Apr 18 2015
    Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015 - Seoul, Korea, Republic of
    Duration: Apr 18 2015Apr 23 2015

    Other

    Other33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015
    CountryKorea, Republic of
    CitySeoul
    Period4/18/154/23/15

    Fingerprint

    User interfaces
    Economics
    Human computer interaction
    Simulators
    Experiments

    Keywords

    • Behavior change
    • Behavioral economics
    • Financial literacy
    • Personal finance
    • Persuasive technology
    • Retirement saving

    ASJC Scopus subject areas

    • Human-Computer Interaction
    • Computer Graphics and Computer-Aided Design
    • Software

    Cite this

    Gunaratne, J., & Nov, O. (2015). Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. In CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings (Vol. 2015-April, pp. 917-920). Association for Computing Machinery. https://doi.org/10.1145/2702123.2702408

    Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. / Gunaratne, Junius; Nov, Oded.

    CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Vol. 2015-April Association for Computing Machinery, 2015. p. 917-920.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Gunaratne, J & Nov, O 2015, Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. in CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. vol. 2015-April, Association for Computing Machinery, pp. 917-920, 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015, Seoul, Korea, Republic of, 4/18/15. https://doi.org/10.1145/2702123.2702408
    Gunaratne J, Nov O. Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. In CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Vol. 2015-April. Association for Computing Machinery. 2015. p. 917-920 https://doi.org/10.1145/2702123.2702408
    Gunaratne, Junius ; Nov, Oded. / Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Vol. 2015-April Association for Computing Machinery, 2015. pp. 917-920
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