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Evaluating design approaches for encouraging behavior change in editors: exploring a digital nudging strategy in a non-personalized recommender system to promote adoption of augmented analytics

Published online by Cambridge University Press:  16 May 2024

Tanja Heinrich  and
Oliver Szasz
Tanja Heinrich*
Affiliation:
Macromedia University of Applied Sciences, Germany Ippen Digital, Germany
Oliver Szasz
Affiliation:
Macromedia University of Applied Sciences, Germany
*
tanja.heinrich94@gmx.de

Abstract

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In the age of digitalization, navigating through vast amounts of data is a challenge. Augmented analytics, which often goes unnoticed by employees, has the potential to support effective decision-making. This study examines the impact of digital nudging on editors' cognitive load and behavioral change towards augmented analytics, providing insights into behavior change design. Combining theory with expert interviews and workshops, this study results in five nudging strategies. The findings reveal varied triggers influencing behavioral change, emphasizing stakeholder involvement in the process.

Keywords

behavioural designdecision makingdigital nudginguser-centred design

Information

Type
Human Behaviour and Design Creativity
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 985 - 994
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

References

Alghamdi, N.A. and Al-Baity, H.H. (2022), “Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence”, Sensors, Multidisciplinary Digital Publishing Institute, Vol. 22 No. 20, p. 8071, https://dx.doi.org/10.3390/s22208071.Google Scholar
Andriole, S.J. (2019), “Artificial Intelligence, Machine Learning, and Augmented Analytics [Life in C-Suite]”, IT Professional, presented at the IT Professional, Vol. 21 No. 6, pp. 56–59, https://dx.doi.org/10.1109/MITP.2019.2941668.Google Scholar
Caraban, A., Karapanos, E., Gonçalves, D. and Campos, P. (2019), “23 Ways to Nudge: A Review of Technology-Mediated Nudging in Human-Computer Interaction”, Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, presented at the CHI ’19: CHI Conference on Human Factors in Computing Systems, ACM, Glasgow Scotland Uk, pp. 1–15, https://dx.doi.org/10.1145/3290605.3300733.CrossRefGoogle Scholar
Caraban, A., Konstantinou, L. and Karapanos, E. (2020), “The Nudge Deck: A Design Support Tool for Technology-Mediated Nudging”, Proceedings of the 2020 ACM Designing Interactive Systems Conference, presented at the DIS ’20: Designing Interactive Systems Conference 2020, ACM, Eindhoven Netherlands, pp. 395–406, https://dx.doi.org/10.1145/3357236.3395485.CrossRefGoogle Scholar
Creswell, J.W. (2007), Qualitative Inquiry and Research Design: Choosing among Five Approaches, 2nd Ed, Sage Publications, Inc, Thousand Oaks, CA, US, pp. xvii, 395.Google Scholar
Dalecke, S. and Karlsen, R. (2020), “Designing Dynamic and Personalized Nudges”, Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics, presented at the WIMS 2020: The 10th International Conference on Web Intelligence, Mining and Semantics, ACM, Biarritz France, pp. 139–148, https://dx.doi.org/10.1145/3405962.3405975.CrossRefGoogle Scholar
Dolan, P., Hallsworth, M., Halpern, D., King, D., Metcalfe, R. and Vlaev, I. (2012), “Influencing behaviour: The mindspace way”, Journal of Economic Psychology, Vol. 33 No. 1, pp. 264–277, https://dx.doi.org/10.1016/j.joep.2011.10.009.CrossRefGoogle Scholar
Eichhorn, D. and Ott, I. (2019), iga.Report 38. Nudging im Unternehmen - Den Weg für gesunde Entscheidungen bereiten, iga, Dresden.Google Scholar
Gartner. (2017a), “Definition of Augmented Analytics - Gartner Information Technology Glossary”, Gartner, available at: https://www.gartner.com/en/information-technology/glossary/augmented-analytics (accessed 26 May 2023).Google Scholar
Gartner. (n.d.). “Data and Analytics: Everything You Need to Know”, Gartner, available at: https://www.gartner.com/en/topics/data-and-analytics (accessed 13 May 2023).Google Scholar
Gena, C., Grillo, P., Lieto, A., Mattutino, C. and Vernero, F. (2019), “When Personalization Is Not an Option: An In-The-Wild Study on Persuasive News Recommendation”, Information, Multidisciplinary Digital Publishing Institute, Vol. 10 No. 10, p. 300, https://dx.doi.org/10.3390/info10100300.Google Scholar
Ghavami, P. (2020), Big Data Analytics Methods: Analytics Techniques in Data Mining, Deep Learning and Natural Language Processing, Second edition., De Gruyter, Boston.Google Scholar
Guarda, T. and Lopes, I. (2023), “Augmented Analytics an Innovative Paradigm”, in Abraham, A., Bajaj, A., Gandhi, N., Madureira, A.M. and Kahraman, C. (Eds.), Innovations in Bio-Inspired Computing and Applications, Springer Nature Switzerland, Cham, pp. 725–733, https://dx.doi.org/10.1007/978-3-031-27499-2_67.CrossRefGoogle Scholar
Hunnes, M.G. (2016), “Nudging: How human behavior is affected by design”, Annual Review of Policy Design, Vol. 4 No. 1, pp. 1–10.Google Scholar
Jesse, M. and Jannach, D. (2021), “Digital Nudging with Recommender Systems: Survey and Future Directions”, Computers in Human Behavior Reports, Vol. 3, p. 100052, https://dx.doi.org/10.1016/j.chbr.2020.100052.CrossRefGoogle Scholar
Karlsen, R. and Andersen, A. (2019), “Recommendations with a Nudge”, Technologies, Vol. 7 No. 2, pp. 1–16, https://dx.doi.org/10.3390/technologies7020045.CrossRefGoogle Scholar
Karlsen, R. and Andersen, A. (2022), “The Impossible, the Unlikely, and the Probable Nudges: A Classification for the Design of Your Next Nudge”, Technologies, Vol. 10 No. 6, p. 110, https://dx.doi.org/10.3390/technologies10060110.CrossRefGoogle Scholar
Khan, Z. and Newman, L. (2021), Building Behavioral Science in an Organization, Action Design Press.Google Scholar
Lockton, D. (2012), “Cognitive Biases, Heuristics and Decision-Making in Design for Behaviour Change”, SSRN Electronic Journal, pp. 1–19, https://dx.doi.org/10.2139/ssrn.2124557.CrossRefGoogle Scholar
Mejía, G.M. (2021), “Theory-Driven or Theory-Informed? A Review of Behavioural Economics in Design”, The Design Journal, Vol. 24 No. 4, pp. 567–587, https://dx.doi.org/10.1080/14606925.2021.1935089.CrossRefGoogle Scholar
Meske, C. and Potthoff, T. (2017), “The DINU-Model – A Process Model for the Design of Nudges”, Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal.Google Scholar
Mirsch, T., Jung, R., Rieder, A. and Lehrer, C. (2018), “Mit Digital Nudging Nutzererlebnisse verbessern und den Unternehmenserfolg steigern”, Controlling, Vol. 30 No. 5, pp. 12–18, https://dx.doi.org/10.15358/0935-0381-2018-5-12.CrossRefGoogle Scholar
Mirsch, T., Lehrer, C. and Jung, R. (2018), “Making Digital Nudging Applicable: The Digital Nudge Design Method”, presented at the CIS 2018 Proceedings. 5, pp. 1–16.Google Scholar
Roy, E.D., Jang, C., Krüger, C., Lugger, M., Moussas, F., Muthike, W., Ojha, A., et al. (2021), “Behavioural science, decision making and climate investments”, IEU Learning Paper, pp. 1–31.Google Scholar
Sobolev, M. (2021), “Digital Nudging: Using Technology to Nudge for Good”, SSRN Electronic Journal, pp. 1–7, https://dx.doi.org/10.2139/ssrn.3889831.CrossRefGoogle Scholar
Spreer, P. (2018), PsyConversion: 101 Behavior Patterns Für Eine Bessere User Experience Und Höhere Conversion-Rate Im E-Commerce, Springer Gabler, Wiesbaden [Heidelberg], https://dx.doi.org/10.1007/978-3-658-21726-6.CrossRefGoogle Scholar
Strübing, J. (2022), “Grounded Theory und Theoretical Sampling”, in Baur, N. and Blasius, J. (Eds.), Handbuch Methoden der empirischen Sozialforschung, Springer Fachmedien Wiesbaden, Wiesbaden, pp. 587–606, https://dx.doi.org/10.1007/978-3-658-37985-8_37.CrossRefGoogle Scholar
Thaler, R.H. and Sunstein, C.R. (2008), Nudge.Google Scholar
Vassakis, K., Petrakis, E. and Kopanakis, I. (2018), “Big Data Analytics: Applications, Prospects and Challenges”, in Skourletopoulos, G., Mastorakis, G., Mavromoustakis, C.X., Dobre, C. and Pallis, E. (Eds.), Mobile Big Data: A Roadmap from Models to Technologies, Springer International Publishing, Cham, pp. 3–20, https://dx.doi.org/10.1007/978-3-319-67925-9_1.CrossRefGoogle Scholar
Weinmann, M., Schneider, C. and vom Brocke, J. (2016), “Digital Nudging”, Business & Information Systems Engineering, Vol. 58 No. 6, pp. 433–436, https://dx.doi.org/10.1007/s12599-016-0453-1.CrossRefGoogle Scholar