人們透過網站及手持裝置應用程式在網路上下決定的情形逐漸上升。然而這些決定其實都被網站或應用程式呈現出來的環境所影響，因為在環境中並沒有一個完美的中立方式去安排選項。在這樣子的背景下，使用者體驗設計師成為了選項的建構者，使用者體驗設計師最好應該在人們知覺的情況下而不是潛移默化地影響了人們的決策，才能確保最後能夠得到有效益的結果。基於這個理由，近期「助推」被延伸使用到數位領域，根據自由主義家長式方法採用介面設計元素去引導使用者行為。此研究探討數位助推對於使用者根據與網站營運者的關係以及網站的個性化程度之間的效益，並將其與使用者感知資訊透明度及隱私權問題做連結。此研究主要探索助推可以如何被應用到數位環境的選擇中，並量化助推在不同實驗條件下透過組間設計從而得到的效益。該研究架構測試了許多假設，嘗試提高我們對於那些具有最大影響力的變數在某些數位環境選擇上的理解。該研究結果基於215份受測者，建議增加資訊透明度以及消費者與網站營運者的親密度將能大幅度地促進助推的效能。在另一方面，藉由增加資訊透明度也同時證明了隱私權問題將被逐漸減少，但資訊透明度對於助推的效益只占了次要的比重。最後，更高層級的個人化感知素質將可以更好地調節關係結構，因此能間接地對消費者對於助推的接受度施加影響。

Individuals make increasingly more decisions online through screens on websites and mobile applications. These decisions are influenced by the environment in which they are presented since there is no perfectly neutral way of arranging options. In this context, user experience designers become choice architects, that should better knowingly than unknowingly influence peoples’ decisions to ensure a beneficial outcome. For this reason, the nudging theory was recently extended into digital domains, employing interface design elements to guide user behavior according to a libertarian paternalistic approach. This study investigates the effectiveness of digital nudges for users depending on their relationship with the website operator as well as the extent of personalization applied to the website and links it with perceived information transparency and privacy concerns. It focuses on exploring how nudges can be deployed in digital choice environments and quantitatively measures their effectiveness in different experimental conditions through a between-subjects design. The research framework tests for several hypotheses, trying to improve our understanding of which variables carry the strongest influence within a certain choice environment. The results based on the data of 215 participants suggest that increasing information transparency and closeness between the consumer and website operator contribute significantly to the effectiveness of nudges. On the other hand, privacy concerns have been proven to diminish with increasing information transparency, but play only a secondary role with regard to nudge effectiveness. Higher levels of the perceived quality of personalization could furthermore be identified to moderate the relationship construct and therefore indirectly exert impact over the consumers’ acceptance of nudges.

Acquisti, A. (2009): Nudging Privacy. The behavioral economics of personal information. In IEEE security & privacy 7 (6), pp. 82–85.
Adjerid, I.; Acquisti, A.; Brandimarte, L.; Loewenstein, G. (Eds.) (2013): Sleights of privacy. Framing, disclosures and the limits of transparency. Symposium on Usable Privacy and Security (SOUPS). Newcastle, UK, July 24-26.
Awad, N. F.; Krishnan, M. S. (2006): he Personalization Privacy Paradox. An Empirical Evaluation of Information Transparency and the Willingness to Be Profiled Online for Personalization. In MIS Quarterly 30 (1), pp. 13–28.
Barnes, S. B. (2006): A privacy paradox: Social networking in the United States. In First Monday 11 (9).
Baron, R. M.; Kenny, D. A. (1986): The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. In Journal of personality and social psychology 51 (6), pp. 1173–1182.
Bartlett, J. E.; Kotrlik, J. W.; Higgins, C. C. (2001): Organizational Research. Determining Appropriate Sample Size in Survey Research. In Information Technology, Learning and Performance Journal 19 (1), pp. 43–50.
Barton, A.; Grüne-Yanoff, T. (2015): From Libertarian Paternalism to Nudging—and Beyond. In Rev.Phil.Psych. 6 (3), pp. 341–359. Baumeister, R. F.; Bratslavsky, E.; Muraven, M.; Tice, D. M. (1998): Ego depletion: is the active self a limited resource? In Journal of personality and social psychology 74 (5), pp. 1252–1265.
Blair, I. V. (2002): The Malleability of Automatic Stereotypes and Prejudice. In Personality and Social Psychology Review 6 (3), pp. 242–261.
Blumenthal-Barby, J. S.; Burroughs, H. (2012): Seeking better health care outcomes: the ethics of using the "nudge". In The American journal of bioethics: AJOB 12 (2), pp. 1–10.
Bolker, B. M.; Brooks, M. E.; Clark, C. J.; Geange, S. W.; Poulsen, J. R.; Stevens, M.; Henry H.; White, J. S. (2009): Generalized linear mixed models: a practical guide for ecology and evolution. In Trends in ecology & evolution 24 (3), pp. 127–135.
Bollen, K. A. (1989): Structural Equations with Latent Variables. Hoboken, NJ, USA: John Wiley & Sons, Inc.
Borgatti, S. P.; Foster, P. C. (2003): The Network Paradigm in Organizational Research: A Review and Typology. In Journal of Management 29 (6), pp. 991–1013.
Bortz, J.; Döring, N. (2015): Forschungsmethoden und Evaluation. Für Human- und Sozialwissenschaftler. 5. Aufl. Berlin: Springer (Springer-Lehrbuch).
Bovens, L. (2008): The Ethics of Nudge. In Till Grüne-Yanoff, Sven O. Hansson (Eds.): Preference Change. Approaches from Philosophy, Economics and Psychology. Berlin, New York: Springer, Theory and Decision Library A.
Brown, M. B.; Forsythe, A. B. (1974): Robust Tests for the Equality of Variances. In Journal of the American Statistical Association 69 (346).
Browne, M. W. (2001): An Overview of Analytic Rotation in Exploratory Factor Analysis. In Multivariate Behavioral Research 36 (1), pp. 111–150.
Bruns, H.; Kantorowicz-Reznichenko, E.; Klement, K.; Luistro J. M.; Rahali, B. (2018): Can nudges be transparent and yet effective? In Journal of Economic Psychology 65, pp. 41–59.
Bundesministerium für Gesundheit (2018): Gesetzliche Krankenversicherung. Mitglieder, mitversicherte Angehörige und Krankenstand Monatswerte Januar-August 2018.
Carmean, C.; Mizzi, P. (2010): The Case for Nudge Analytics. In Educause Quarterly 33 (4).
Charness, G.; Gneezy, U.; Kuhn, M. A. (2012): Experimental methods: Between-subject and within-subject design. In Journal of Economic Behavior & Organization 81 (1), pp. 1–8.
Chellappa, R. K.; Sin, R. G. (2005): Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma. In Information Technology and Management 6 (2), pp. 181–202.
Child, Dennis (2006): Essentials of factor analysis: A&C Black.
Cole, J. I.; Sunman, M.; Schramm, P.; Zhou, L. (2017): Surveying the Digital Future. The 15th annual study on the impact of digital technology on Americans. Available online at http://www.digitalcenter.org/wp-content/uploads/2013/10/2017-Digital-Future-Report.pdf, checked on 10/3/2019.
Cook, T. D.; Campbell, D. T. (1979): Quasi-experimentation. Design and analysis issues for field settings. Boston: Houghton-Mifflin.
Couper, M. P.; Tourangeau, R.; Conrad, F. G.; Crawford, S. D. (2004): What They See Is What We Get. In Social Science Computer Review 22 (1), pp. 111–127.
Deloitte (2018): European Health & Fitness Market. Report 2018. In EuropeActive (4).
Department for Work and Pensions (2017): Automatic Enrolment Review. Maintaining the Momentum /UK Parliament Department for Work and Pensions. London: Dandy Booksellers Ltd (UK Parliament Command Paper, session 2017/19, CM 9546). Available online at http://www.publicinformationonline.com/download/157782.
Department of Health (2010): Healthy lives, healthy people. Our strategy for public health in England.
Edelman Inc. (2019): Edelman Trust Barometer: Executive Summary. Available online at https://www.edelman.com/sites/g/files/aatuss191/files/2019-02/2019_Edelman_Trust_Barometer_Executive_Summary.pdf.
Evans, J. (2003): In two minds: dual-process accounts of reasoning. In Trends in Cognitive Sciences 7 (10), pp. 454–459.
Ferketich, S. (1991): Focus on psychometrics. Aspects of item analysis. In Res. Nurs. Health 14 (2), pp. 165–168.
Field, A. P. (2009): Discovering statistics using SPSS. (and sex and drugs and rock 'n' roll) / Andy Field. 3rd ed. Los Angeles i.e. Thousand Oaks, Calif., London: SAGE Publications (Introducing statistical methods).
Fornell, C.; Larcker, D. F. (1981): Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. In Journal of Marketing Research 18 (1), p. 39.
Franke, G. R. (2011): Multicollinearity. In Jagdish N. Sheth, Naresh K. Malhotra (Eds.): Wiley international encyclopedia of marketing, vol. 34. Chichester: Wiley, p. 227.
Freud, Sigmund (1915): Das Unbewusste. In Internationale Zeitschrift für Psychoanalyse 3 (4), pp. 189–203.
Friedman, M.; Friedman, R. D. (1980): Free to choose / M. A personal statement. 1st ed. New York: Harcourt Brace Jovanovich.
Girden, E. R. (2006): Evaluating research articles. From start to finish. 2. ed., 5. print. Lonon: Sage.
Goldstein, D. G.; Johnson, E. J.; Herrmann, A.; Heitmann, M. (2008): Nudge Your Customers Toward Better Choices. In Harvard Business Review (December Issue).
Gosnell, G.; List, J.; Metcalfe, R. (2016): A New Approach to an Age-Old Problem: Solving Externalities by Incenting Workers Directly. Cambridge, MA.
Granovetter, M. S. (1973): The Strength of Weak Ties. In American Journal of Sociology 78 (6), pp. 1360–1380.
Gravetter, F.; Wallnau, L. (2014): Essentials of Statistics for the Behavioral Sciences. 8th ed. Belmont, CA: Wadsworth.
Ha, S. H. (2002): Helping online customers decide trho. In IEEE Intelligent Systems 17 (6), pp. 34–43.
Hair, J. F. (2010): Multivariate data analysis. 7th ed. Upper Saddle River NJ: Prentice Hall.
Hansen, P. G. (2016): The Definition of Nudge and Libertarian Paternalism: Does the Hand Fit the Glove? In Eur. j. risk regul. 7 (01), pp. 155–174.
Hansen, P. G.; Jespersen, A. M. (2013): Nudge and the Manipulation of Choice. In Eur. j. risk regul. 4 (01), pp. 3–28.
Häubl, G.; Trifts, V. (2000): Consumer Decision Making in Online Shopping Environments. The Effects of Interactive Decision Aids. In Marketing Science 19 (1), pp. 4–21.
Hayes, A. F. (2013): Introduction to mediation, moderation, and conditional process analysis. A regression-based approach. New York, NY: Guilford Press.
Ho, S. Y.; Bodoff, D. (2014): The Effects of Web Personalization on User Attitude and Behavior. An Integration of the Elaboration Likelihood Model and Consumer Search Theory. In MIS Quarterly 38 (2), pp. 497–520.
Huang, N.; Chen, P.; Hong, Y..; Wu, S. (Eds.) (2018): Digital Nudging for Online Social Sharing. Evidence from A Randomized Field Experiment. 51st Hawaii International Conference on System Sciences. Hawaii.
James, L. R. (1980): The unmeasured variables problem in path analysis. In Journal of Applied Psychology 65, pp. 415–421.
Johnson, E. J.; Goldstein, D. (2003): Medicine. Do defaults save lives? In Science (New York, N.Y.) 302 (5649), pp. 1338–1339.
Johnson, E. J.; Hassin, R.; Baker, T.; Bajger, A. T.; Treuer, G. (2013): Can consumers make affordable care affordable? The value of choice architecture. In PloS one 8 (12), e81521
Johnson, E. J.; Shu, S. B.; Dellaert, B. G. C.; Fox, C.; Goldstein, D. G.; Häubl, G. et al. (2012): Beyond nudges: Tools of a choice architecture. In Mark Lett 23 (2), pp. 487–504
Kaiser, H. F. (1960): The Application of Electronic Computers to Factor Analysis. In Educational and Psychological Measurement 20 (1), pp. 141–151.
Kapsner, A.; Sandfuchs, B. (2015): Nudging as a Threat to Privacy. In Rev.Phil.Psych. 6 (3), pp. 455–468.
Kretzer, M.; Maedche, A. (2018): Designing Social Nudges for Enterprise Recommendation Agents: An Investigation in the Business Intelligence Systems Context. In JAIS, pp. 1145–1186.
Lamnek, S. (2010): Qualitative Sozialforschung. Lehrbuch. Weinheim, Basel: Beltz.
Lance, C. E.; Butts, M. M.; Michels, L. C. (2006): The Sources of Four Commonly Reported Cutoff Criteria. In Organizational Research Methods 9 (2), pp. 202–220.
Laudon, K. C. (1996): Markets and privacy. In Commun. ACM 39 (9), pp. 92–104.
Levav, J.; Heitmann, M.; Herrmann, A.; Iyengar, S. S. (2010): Order in Product Customization Decisions: Evidence from Field Experiments. In Journal of Political Economy 118 (2), pp. 274–299.
Logan, G. D.; Cowan, W. D. (1984): On the Ability to Inhibit Thought and Action. A Theory of an Act of Control. In Psychological Review 91 (3), pp. 295–327.
Loock, C.; Staake, T.; Thiesse, F. (2013): Motivating Energy-Efficient Behavior with Green IS. An Investigation of Goal Setting and the Role of Defaults. In MIS Quarterly 37 (4), pp. 1313–1332.
Madrian, B. C.; Shea, D. F. (2001): The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior. In The Quarterly journal of economics 116 (4), pp. 1149–1187.
Malhotra, N. K.; Birks, D. F.; Wills, P. (2012): Marketing research. An applied approach. Fourth edition. Harlow, England: Pearson.
Malhotra, N. K.; Peterson, M. (2006): Basic marketing research. A decision-making approach. 2nd ed. Upper Saddle River N.J.: Pearson/Prentice Hall.
Marsden, P. V., and Friedkin N. E. (1993): "Network studies of social influence." Sociological Methods & Research 22 (1), pp. 127-151.
Marsh, H. W.; Hau, K.-T. (1999): Confirmatory factor analysis: Strategies for small sample size. In R. H. Hoyle (Ed.): Statistical strategies for small sample research. Thousand Oaks, CA: Sage.
Milligan, G. W.; Cooper, M. C. (1988): A Study of Standardization of Variables in Cluster Analysis. In Journal of Classification 5 (2), pp. 181–204.
Mirsch, T.; Lehrer, C.; Jung, R. (2017): Digital Nudging. Altering User Behavior in Digital Environments. In Leinmeister, J., M., W. Brenner (Eds.): Digital Nudging. Altering User Behavior in Digital Environments. 13th International Conference on Wirtschaftsinformatik. St. Gallen, Switzerland, Febuary 12-15, pp. 634–648.
Molich, R.; Nielsen, J. (1990): Improving a human-computer dialogue. In Commun. ACM 33 (3), pp. 338–348.
Mowrer, O. H. (1960): Learning theory and behavior. Hoboken: John Wiley & Sons Inc.
Nielsen, J. (1995): 10 usability heuristics for user interface design. In Nielsen Norman Group 1 (1).
Norberg, P. A.; Horne, D. R.; Horne, D. A. (2007): The Privacy Paradox: Personal Information Disclosure Intentions versus Behaviors. In Journal of Consumer Affairs 41 (1), pp. 100–126.
Norman, D.; Nielsen, J. (2019): The Definition of User Experience (UX). Available online at https://www.nngroup.com/articles/definition-user-experience/.
Norris, M.; Lecavalier, L. (2010): Evaluating the use of exploratory factor analysis in developmental disability psychological research. In Journal of autism and developmental disorders 40 (1), pp. 8–20.
Nunnaly, J. C.; Bernstein, I. H. (1994): Psychometric Theory. Sydney: McGraw-Hill.
Oliver, A.; Ubel, P. (2014): Nudging the obese: a UK-US consideration. In Health economics, policy, and law 9 (3), pp. 329–342.
Peters, E.; Hibbard, J.; Slovic, P.; Dieckmann, N. (2007): Numeracy skill and the communication, comprehension, and use of risk-benefit information. In Health affairs (Project Hope) 26 (3), pp. 741–748.
Raubenheimer, J. (2004): An item selection procedure to maximise scale reliability and validity. In SA Journal of Industrial Psychology 30 (4), pp. 59–64.
Reisch, L. A.; Sunstein, C. R. (2016): Do Europeans like nudges? In Judgement and Decision Making 11 (4), pp. 310–325.
Ruderman, A. J. (1985): Dysphoric mood and overeating: A test of restraint theory's disinhibition hypothesis. In Journal of Abnormal Psychology 94 (1), pp. 78–85.
Schmider, E.; Ziegler, M.; Danay, E.; Beyer, L.; Bühner, M. (2010): Is It Really Robust? In Methodology 6 (4), pp. 147–151.
Schneider, C.; Weinmann, M.; Vom Brocke, J. (2018): Digital nudging. In Commun. ACM 61 (7), pp. 67–73.
Spiekermann, S., Grossklags, J., and Berendt, B. (2001): E-privacy in 2nd Generation E-Commerce: Privacy Preferences versus actual Behavior, Proceedings of the 3rd ACM conference on Electronic Commerce, pp. 28–47.
Schwartz, B. (2007): The paradox of choice. Why more is less. Pymble, NSW, New York: HarperCollins e-books.
Shankar, V.; Smith, A. K.; Rangaswamy, A. (2003): Customer satisfaction and loyalty in online and offline environments. In International journal of research in marketing 20 (2), pp. 153–175.
Simon, H. A. (1955): A Behavioral Model of Rational Choice. In Quarterly Journal of Economics 69 (1), pp. 99–118.
Statista (2010): Zufriedenheit mit der Krankenversicherung (in Prozent). Available online at https://de.statista.com/statistik/daten/studie/76752/umfrage/krankenversicherung-zufriedenheit/, checked on 5/11/2019.
Statista (2017): Wenn es um Ihre Krankenkasse/Krankenversicherung geht, wie sehr vertrauen Sie dann einer klassischen Versicherung? Available online at https://de.statista.com/statistik/daten/studie/674061/umfrage/umfrage-zum-vertrauen-in- klassische-krankenkassen-krankenversicherungen-in-deutschland/, checked on 5/11/2019.
Statista (2019a): Number of Amazon Prime members in the United States as of December 2018 (in millions). Available online at https://www.statista.com/statistics/546894/number-of-amazon-prime-paying-members/, checked on 5/25/2019.
Statista (2019b): Internet Usage Worldwide. Available online at https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/, checked on 5/25/2019
Statista (2019c): Entwicklung der Studienanfängerquote* in Deutschland von 2001 bis 2018. Available online at https://de.statista.com/statistik/daten/studie/72005/umfrage/entwicklung-der-studienanfaengerquote/, checked on 5/01/2019.
Sunstein, C. R. (2012a): The Office of Information and Regulatory Affairs: Myths and Realities. In Harvard Law Review, Forthcoming; Harvard Public Law Working Paper 13 (7).
Sunstein, C. R. (2012b): The Storrs lectures. Behavioral economics and paternalism. In Yale Law Journal, 1826-1899.
Sunstein, C. R. (2014): Why nudge? The politics of libertarian paternalism: Yale University Press.
Tam, K. Y.; Ho, S. Y. (2006): Understanding the Impact of Web Personalization on User Information Processing and Decision Outcomes. In MIS Quarterly 30 (4), pp. 865–890.
Tavakol, M.; Dennick, R. (2011): Making sense of Cronbach's alpha. In International journal of medical education 2, pp. 53–55.
Taylor, D. G.; Davis, D. F.; Jillapalli, R. (2009): Privacy concern and online personalization: The moderating effects of information control and compensation. In Electron Commer Res 9 (3), pp. 203–223.
Thaler, R. H. (2000): From Homo Economicus to Homo Sapiens. In Journal of Economic Perspectives 14 (1), pp. 133–141.
Thaler, R. H. (2015): The power of nudges, for good and bad. In New York Times, 10/31/2015.
Thaler, R. H.; Sunstein, C. R. (2008): Nudge. Improving decisions using the architecture of choice. New Haven, Conn., London: Yale University Press.
Treumann, K. P. (1986): Zum Verhältnis qualitativer und quantitativer Forschung. Mit einem methodischen Ausblick auf neuere Jugendstudien. In Interdisziplinäre Jugendforschung. Fragestellungen, Problemlagen, Neuorientierungen.
Trochim, W. M.; Donnelly, J. P. (2006): The research methods knowledge base. 3rd ed. Cincinnati, OH: Atomic Dog.
Tseng, W.; Dörnyei, Z.; Schmitt, N. (2006): A New Approach to Assessing Strategic Learning: The Case of Self-Regulation in Vocabulary Acquisition. In Applied Linguistics 27 (1), pp. 78–102.
Tversky, A.; Kahneman, D. (1981): The framing of decisions and the psychology of choice. In Science 211 (4481), pp. 453–458.
Van Kleef, E.; Otten, K.; Van Trijp, H. C. M. (2012): Healthy snacks at the checkout counter: a lab and field study on the impact of shelf arrangement and assortment structure on consumer choices. In BMC public health 12, p. 1072.
Wang, Y.; Leon, P. G.; Acquisti, A.; Cranor, L. F.; Forget, A.; Sadeh, N. (2014): A field trial of privacy nudges for facebook. In Matt Jones, Philippe Palanque, Albrecht Schmidt, Tovi Grossman (Eds.): Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14. the 32nd annual ACM conference. Toronto, Ontario, Canada, 4/26/2014 - 5/1/2014. New York, New York, USA: ACM Press, pp. 2367–2376.
Wansink, B.; Sobal, J. (2007): Mindless Eating. In Environment and Behavior 39 (1), pp. 106–123.
Weinmann, M.; Schneider, C.; Vom Brocke, J. (2016): Digital Nudging. In Bus Inf Syst Eng 58 (6), pp. 433–436.
Willis, L. E. (2013): When nudges fail. Slippery defaults. In The University of Chicago Law Review, pp. 1155–1229.
World Obesity Federation (2018): Changes in % Overweight in Children. Changes in % Overweight between 2001 & 2013/4. Available online at https://www.worldobesitydata.org/presentation-graphics/resources/charts/83/, checked on 4/13/2019.