Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41218

Overcoming Innovation Resistance beyond Status Quo Bias - A Decision Support System Approach (Research-in-Progress)

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dc.contributor.author Stryja, Carola
dc.contributor.author Dorner, Verena
dc.contributor.author Riefle, Lara
dc.date.accessioned 2016-12-29T00:18:09Z
dc.date.available 2016-12-29T00:18:09Z
dc.date.issued 2017-01-04
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41218
dc.description.abstract When innovative products and services are launched to the market, many consumers initially resist adopting them, even if the innovation is likely to enhance their life quality. Explanations for this behavior can also be found in specific personality traits and in general pitfalls of human decision-making. We believe that decision support systems (DSS) can help alleviate such innovation resistance. We propose a DSS design that addresses innovation resistance to complex innovations on an individual’s cognitive level. An experimental study will be conducted to test the influence of different DSS modifications on the perception and selection of complex innovations. We aim to identify levers for reducing innovation resistance and to derive DSS design implications. \
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject choice architecture
dc.subject decision design
dc.subject electric car
dc.subject experimental study
dc.title Overcoming Innovation Resistance beyond Status Quo Bias - A Decision Support System Approach (Research-in-Progress)
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2017.069
Appears in Collections: Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods Minitrack


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