The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.
Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles
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Citations
Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Prospect theory: An analysis of decision under risk
Kahneman, D., & Tversky, A. (1988) · Decision, Probability and Utility · doi:10.1017/cbo9780511609220.014 · Cited by 32,474
(1980) · Medical Entomology and Zoology · Cited by 25,810
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
A Theory of Cognitive Dissonance
(2017) · Macat Library eBooks · doi:10.4324/9781912282432 · Cited by 18,122
(1997) · Naming the Mind: How Psychology Found its Language · doi:10.4135/9781446221815.n7 · Cited by 15,148
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60214-2 · Cited by 8,822 · cited 3×
“Much of the work on individual differences in persuasion has directly drawn on dual-process models (for example the Elaboration Likelihood Model (ELM), see Petty and Cacioppo, 1986; Petty and Wegener, 1999) to work out how new or established traits could moderate persuasion.”
BackgroundA very brief measure of the Big-Five personality domains
Gosling, S. D., Rentfrow, P. J., & Swann, W. B. (2003) · Journal of Research in Personality · doi:10.1016/s0092-6566(03)00046-1 · Cited by 8,307
The Transtheoretical Model of Health Behavior Change.
Prochaska, J. O., & Velicer, W. F. (1997) · American Journal of Health Promotion · doi:10.4278/0890-1171-12.1.38 · Cited by 7,782
Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013) · Annals of Behavioral Medicine · doi:10.1007/s12160-013-9486-6 · Cited by 7,629
Cited by
Usage impact on data center electricity needs: A system dynamic forecasting model
Koot, M., & Wijnhoven, F. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.116798 · Cited by 403
Zhang, J., Oh, Y. J., Lange, P., Yu, Z., & Fukuoka, Y. (2020) · Journal of Medical Internet Research · doi:10.2196/22845 · Cited by 363
Persuasive technology in mobile applications promoting physical activity: a systematic review
Matthews, J., Win, K. T., Oinas-Kukkonen, H., & Freeman, M. (2016) · Journal of Medical Systems · doi:10.1007/s10916-015-0425-x · Cited by 239
The personalization-privacy paradox: Implications for new media
Aguirre, E., Roggeveen, A. L., Grewal, D., & Wetzels, M. (2016) · Journal of Consumer Marketing · doi:10.1108/jcm-06-2015-1458 · Cited by 251
Empirical validation of the Gamification User Types Hexad scale in English and Spanish
Tondello, G. F., Mora, A., Marczewski, A., & Nacke, L. E. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2018.10.002 · Cited by 185
“…personalization has been demonstrated in the contexts of user interface design (Arazy et al., 2015; Nov and Arazy, 2013), persuasive technology (Kaptein et al., 2015, 2012), games (Bakkes et al., 2012; Connolly et al., 2012; Orji et al., 2014, 2013), and recently also in gamification (Orji et…”
Background
Metadata
- Authors
- Kaptein, M., Markopoulos, P., de Ruyter, B., & Aarts, E.
- Venue
- International Journal of Human-Computer Studies
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 77
- Pages
- 38-51
- ISSN
- 1071-5819 (ISSN-L)
- OpenAlex
- W2043002652
- Cited by
- 314
- References
- 135
- FWCI
- 43.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles. https://app.cochat.ai/papers/10.1016/j.ijhcs.2015.01.004
- The paper
- Kaptein, M., Markopoulos, P., de Ruyter, B., & Aarts, E. (2015). Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles. International Journal of Human-Computer Studies. https://doi.org/10.1016/j.ijhcs.2015.01.004
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
