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Nudging users into digital service solutions

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Abstract

With the ubiquity and prevalence of advanced technologies in society, transactions have become increasingly digital, requiring new user identity verification mechanisms. Electronic identification (eID) enables user identity authorization in online environments. Although eID plays a central role in government initiatives worldwide to digitalize citizen transactions, eID adoption remains surprisingly low. Drawing on digital nudging theory and e-government literature, we examine how eID adoption can be increased by changing the decision environment in which users choose eID. In a controlled experiment with 161 participants, we investigate the effect of default options (eID vs. offline ID as default) and popularity signals (presence vs. absence of social proof) on users’ eID adoption behavior. Both nudges increase eID adoption, but default options are a double-edged sword as they simultaneously fuel privacy concerns towards the government, attenuating the effect of default option on eID adoption. These concerns can be mitigated by adding social proof cues.

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References

  • Adjerid, I., Peer, E., & Acquisti, A. (2018). Beyond the privacy paradox: Objective versus relative risk in privacy decision making. MIS Quarterly, 42(2), 465–488.

    Google Scholar 

  • Aguinis, H., & Bradley, K. J. (2014). Best practice recommendations for designing and implementing experimental vignette methodology studies. Organizational Research Methods, 17(4), 351–371.

    Google Scholar 

  • Al-Shafi, S. & Weerakkody, V. (2010). Factors affecting E-government adoption in the State of Qatar. Proceedings of the European and Mediterranean Conference on Information Systems.

  • Alawneh, A., Al-Refai, H., & Batiha, K. (2013). Measuring user satisfaction from e-government services: Lessons from Jordan. Government Information Quarterly, 30(3), 277–228.

    Google Scholar 

  • Alzahrani, L., Al-Karaghouli, W., & Weerakkody, V. (2016). Analysing the critical factors influencing trust in e-government adoption from citizens’ perspective: A systematic review and a conceptual framework. International Business Review, 26(1), 164–175.

    Google Scholar 

  • Amblee, N. C. & Bui, T. X. (2012). Value proposition and social proof in online deals: An exploratory study of Groupon. Com. Proceedings of the 14th Annual International Conference on Electronic Commerce, 294-300.

  • Amblee, N. C., & Bui, T. X. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International Journal of Electronic Commerce, 16(2), 91–114.

    Google Scholar 

  • Amirpur, M. & Benlian, A. (2015). Buying under pressure: purchase pressure cues and their effects on online buying decisions. Proceedings of the 36th International Conference on Information Systems (ICIS).

  • Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402.

    Google Scholar 

  • Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 4(3), 291–295.

    Google Scholar 

  • Barry, C., Hogan, M., & Torres, A. (2013). Perceptions of low-cost carriers’ compliance with EU legislation on optional extras. Information Systems Development (pp. 669-680). New York, NY: Springer.

  • Behrend, T., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43(3), 800–813.

    Google Scholar 

  • Belanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. Management Information Systems Quarterly, 35(4), 1017–1041.

    Google Scholar 

  • Belanger, F., & Hiller, J. S. (2006). A framework for e-government: Privacy implications. Business Process Management Journal, 12(1), 48–60.

    Google Scholar 

  • Benlian, A. (2015). Web personalization cues and their differential effects on user assessments of website value. Journal of Management Information Systems, 32(1), 225–260.

    Google Scholar 

  • Benlian, A., Titah, R., & Hess, T. (2012). Differential effects of provider recommendations and consumer reviews in E-commerce transactions: An experimental study. Journal of Management Information Systems, 29(1), 237–272.

    Google Scholar 

  • Benlian, A., Klumpe, J., & Hinz, O. (2019). Mitigating the intrusive effects of smart home assistants by using anthropomorphic design features: A multimethod investigation, Information Systems Journal, forthcoming.

  • Brown, L. C., & Krishna, A. (2004). The skeptical shopper: A metacognitive account for the effects of default options on choice. Journal of Consumer Research, 31, 529–539.

    Google Scholar 

  • Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon's mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6(1), 3–5.

    Google Scholar 

  • Burnkrant, R. E., & Cousineau, A. (1975). Informational and normative social influence in buyer behavior. Journal of Consumer Research, 2(3), 206–215.

    Google Scholar 

  • Cao, Z., Hui, K. L., & Xu, H. (2018). An economic analysis of Peer disclosure in online social communities. Information Systems Research, 29(3), 546–566.

    Google Scholar 

  • Capgemini (2017). E-government benchmark 2017. Retrieved from https://www.capgemini.com/wp-content/uploads/2017/11/2017-egovernment-benchmark_background_v7.pdf.

  • Carr, A. (2013) How square register’s UI guilts you into leaving tips. Retrieved from https://www.fastcompany.com/3022182/how-square-registers-ui-guilts-you-into-leaving-tips.

  • Carroll, D. G., Choi, J. J., Laibson, D., Madrian, B., & Metrick, A. (2009). Optimal defaults and active decisions. The Quarterly Journal of Economics, 124(4), 1639–1674.

    Google Scholar 

  • Cavusoglu, H., Phan, T. Q., Cavusoglu, H., & Airoldi, E. M. (2016). Assessing the impact of granular privacy controls on content sharing and disclosure on Facebook. Journal Information Systems Research, 27(4), 848–879.

    Google Scholar 

  • Center for Health and Safety Culture (2015). Retrieved from http://chsculture.org/mou_projects/most-of-us-wear-seatbelts-campaign-2002-2003/.

  • Chapman, G. B. (2004). The psychology of medical decision making. In D. J. Koehler & N. Harvey (Eds.), Handbook of judgment and decision making (pp. 585–603). Oxford, UK: Blackwell Publishing.

    Google Scholar 

  • Choi, J. J., Laibson, D., Madrian, B. C., & Metrick, A. (2003). Optimal defaults. The American Economic Review, 93(2), 180–185.

    Google Scholar 

  • Cialdini, R. B. (1993). Influence: Science and practice. New York, NY: Harper Collins.

    Google Scholar 

  • Cialdini, R. B., & Trost, M. R. (1998). Social influence: Social norms, conformity, and compliance. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 151–192). New York, US: McGraw-Hill.

    Google Scholar 

  • Cnet (2017). China is testing an electronic identification system on WeChat. Retrieved from https://www.cnet.com/news/china-is-testing-an-electronic-identification-system-on-wechat/.

  • Cronqvist, H., & Thaler, R. H. (2004). Design choices in privatized social-security systems: Learning from the Swedish experience. American Economic Review, 94(2), 424–428.

    Google Scholar 

  • Dinev, T., & Hart, P. (2006). An extended privacy Calculus model for E-commerce transactions. Information Systems Research, 17(1), 61–80.

    Google Scholar 

  • Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011). Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology, 17(4), 332–341.

    Google Scholar 

  • Dolan, P., Hallsworth, M., Halpern, D., King, D., Metcalfe, R., & Vlaev, I. (2012). Influencing behaviour: The mindspace way. Journal of Economic Psychology, 33(1), 264–277.

    Google Scholar 

  • Dogruel, L. (2017). Cross-cultural differences in movie selection. Decision-making of German, U.S., and Singaporean media users for video-on-demand movies. Journal of International Consumer Marketing, 2001(6), 1–13.

    Google Scholar 

  • Downs, S. J., Loewenstein, G., & Wisdom, J. (2009). Strategies for promoting healthier food choices. The American Economic Review, 99(2), 159–164.

    Google Scholar 

  • Duhan, D. F., Johnsen, S. D., Wilcox, J. B., & Harrell, G. D. (1997). Influences on consumer use of word-of-mouth recommendation sources. Journal of the Academy of Marketing Science, 25(4), 283–295.

    Google Scholar 

  • Edelman (2018). 2018 Edelman Trust Barometer Global Report. Retrieved from https://cms.edelman.com/sites/default/files/2018-01/2018%20Edelman%20Trust%20Barometer%20Global%20Report.pdf.

  • European Commission (2018a). Trust Services and Electronic identification (eID). Retrieved from https://ec.europa.eu/digital-single-market/en/policies/trust-services-and-eidentification.

  • European Commission (2018b). Retrieved from https://ec.europa.eu/digital-single-market/en/news/cross-border-digital-identification-eu-countries-major-step-trusted-digital-single-market.

  • European Commission (2018c). Retrieved from https://ec.europa.eu/cefdigital/wiki/display/CEFDIGITAL2018/Country+Overview+-+eID.

  • European Parliament (2014). Regulation (EU) No 910/2014 of the European Parliament and of the Council on electronic identification and trust services for electronic transactions in the internal market and repealing Directive 1999/93/EC. Retrieved from https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=uriserv:OJ.L_.2014.257.01.0073.01.ENG.

  • Eurostat (2018). Individuals using the Internet for interacting with public authorities. Retrieved from http://appsso.eurostat.ec.europa.eu/nui/show.do?query=BOOKMARK_DS-125123_QID_-432FBBA7_UID_-3F171EB0andlayout=TIME,C,X,0;GEO,L,Y,0;INDIC_IS,L,Z,0;IND_TYPE,L,Z,1;UNIT,L,Z,2;INDICATORS,C,Z,3;andzSelection=DS-125123INDICATORS,OBS_FLAG;DS-125123UNIT,PC_IND;DS-125123IND_TYPE,IND_TOTAL;DS-125123INDIC_IS,I_IUGOV12;andrankName1=TIME_1_0_0_0andrankName2=UNIT_1_2_-1_2andrankName3=GEO_1_2_0_1andrankName4=INDICATORS_1_2_-1_2andrankName5=INDIC-IS_1_2_-1_2andrankName6=IND-TYPE_1_2_-1_2andsortC=ASC_-1_FIRSTandrStp=andcStp=andrDCh=andcDCh=andrDM=trueandcDM=trueandfootnes=falseandempty=falseandwai=falseandtime_mode=NONEandtime_most_recent=falseandlang=ENandcfo=%23%23%23%2C%23%23%23.%23%23%23.

  • Fan, J., Zhang, P., & Yen, D. C. (2014). G2G information sharing among government agencies. Information and Management, 51(1), 120–128.

    Google Scholar 

  • Felsen, G., Castelo, N., & Reiner, P. B. (2013). Decisional enhancement and autonomy: Public attitudes towards overt and covert nudges. Judgment and Decision making, 8(3), 202–213.

    Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Fitzsimons, G. J., & Lehmann, D. R. (2004). Reactance to recommendations: When unsolicited advice yields contrary responses. Marketing Science, 23(1), 82–94.

    Google Scholar 

  • Gemalto (2018). Digital driver’s license - your ID in your smartphone. Retrieved from https://www.gemalto.com/govt/traffic/digital-driver-license.

  • Goffart, K., Schermann, M., Kohl, C., Preißinger, J., & Krcmar, H. (2016). Using the default option Bias to influence decision making while driving. International Journal of Human-Computer Interaction, 32(1), 39–50.

    Google Scholar 

  • Goldstein, D. G., & Johnson, E. J. (2008). Nudge your customers toward better choices. Harvard Business Review, 86(12), 99–105.

    Google Scholar 

  • Goodman, J. K., & Paolacci, G. (2017). Crowdsourcing consumer research. Journal of Consumer Research, 44(1), 196–210.

    Google Scholar 

  • Gu, J., Xu, Y., Xu, H., Zhang, C., & Ling, H. (2017). Privacy concerns for mobile app download: An elaboration likelihood model perspective. Decision Support Systems, 94, 19–28.

    Google Scholar 

  • Gunaratne, J., & Nov, O. (2015). Informing and improving retirement saving performance using behavioral economics theory-driven user interfaces. Proceedings of the 33rd annual ACM conference on human factors in computing systems (pp. 917–920). New York: ACM.

    Google Scholar 

  • Haan, T., & Linde, J. (2018). Good nudge lullaby’: Choice architecture and default Bias reinforcement. The Economic Journal, 128(610), 1180–1206.

    Google Scholar 

  • Hansen, P. G., & Jespersen, A. M. (2013). Nudge and the manipulation of choice: A framework for the responsible use of the nudge approach to behaviour change in public policy. European Journal of Risk Regulation, 4(1), 3–28.

    Google Scholar 

  • Hayes, A. F. (2018). Mediation, moderation, and conditional process analysis (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • Heeks, R. (2003). Most eGovernment for development projects fail: How can risks be reduced. Institute for Development Policy and Management.

  • Hoff, J. V., & Hoff, F. V. (2010). The Danish eID case: Twenty years of delay. Identity in the Information Society, 3(1), 155–174.

    Google Scholar 

  • Hogan, M., Barry, C., & Torres, A. M. (2015). Keeping an Eye on how Users Perceive Optionality in Purchasing Decisions: A Pilot Study. Proceedings of the 14th International WWW/Internet Conference, 13(2).

  • Huh, Y. E., Vosgerau, J., & Morewedge, C. K. (2016). Selective sensitization: Consuming a food activates a goal to consume its complements. Journal of Marketing Research, 53(6), 1034–1049.

    Google Scholar 

  • Janssen, M., Rana, N. P., Slade, E. L., & Dwivedi, Y. K. (2018). Trustworthiness of digital government services: Deriving a comprehensive theory through interpretive structural modelling. Public Management Review, 20(5), 647–671.

    Google Scholar 

  • Jin, L., He, Y., & Song, H. (2012). Service customization: To upgrade or to downgrade? An investigation of how option framing affects tourists’ choice of package-tour services. Tourism Management, 33, 266–275.

    Google Scholar 

  • Johnson, E. J., Bellman, S., & Lohse, G. L. (2002). Defaults, framing and privacy: Why opting in-opting out? Marketing Letters, 13(1), 5–15.

    Google Scholar 

  • Johnson, E. J., & Goldstein, D. G. (2003). Do defaults save lives? Science, 302, 1338–1339.

    Google Scholar 

  • Johnson, E. J., & Goldstein, D. G. (2004). Defaults and donation decisions. Transplantation, 78(12), 1713–1716.

    Google Scholar 

  • Johnson, E. J., Hershey, J., Meszaros, J., & Kunreuther, H. (1993). Framing, probability distortions, and insurance decisions. Journal of Risk and Uncertainty, 7(1), 35–51.

    Google Scholar 

  • Johnson, E. J., & Russo, J. E. (1984). Product familiarity and learning new information. Journal of Consumer Research, 11(1), 542–550.

    Google Scholar 

  • Johnson, E. J., Shu, S. B., Dellaert, B. G. C., Fox, C., Goldstein, D. G., Haubl, G., Larrick, R. P., Payne, J. W., Peters, E., Schkade, D., Wansink, B., & Weber, E. U. (2012). Beyond nudges: Tools of a choice architecture. Marketing Letters, 2(23), 487–504.

    Google Scholar 

  • Karahanna, E., Straub, D., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.

    Google Scholar 

  • Karahanna, E., Benbasat, I., Bapna, R., & Rai, A. (2018). S comments: Opportunities and challenges for different types of online experiments. MIS Quarterly, 42(4), 3–10.

    Google Scholar 

  • Katz, J. and Hilbert, M. (2003) Building an information society: A Latin American and Caribbean perspective, 1st edn. ECLAC.

  • Keller, P. A., Harlam, B., Loewenstein, G., & Volpp, K. G. (2011). Enhanced active choice: A new method to motivate behavior change. Journal of Consumer Psychology, 21(4), 376–383.

    Google Scholar 

  • Kelley, H. H. (1967). Attribution theory in social psychology. In L. David (Ed.), Nebraska symposium on motivation. Lincoln, US: University of Nebraska Press.

    Google Scholar 

  • Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision making model in electronic commerce: The role of trust, perceived risk. and their antecedents. Decision Support Systems, 44(2), 544–564.

    Google Scholar 

  • Klumpe, J., Koch, O. F. & Benlian, A. (2019). How pull vs. push information delivery and social proof affect information disclosure in location based services. Electronic Markets (forthcoming).

  • Koch, O. F., & Benlian, A. (2015). Promotional tactics for online viral marketing campaigns: How scarcity and personalization affect seed stage referrals. Journal of Interactive Marketing, 32, 37–52.

    Google Scholar 

  • Kumar, R., Sachan, A., & Mukherjee, A. (2017). Qualitative approach to determine user experience of e-government services. Computers in Human Behavior, 71, 299–306.

    Google Scholar 

  • Kroll T, & Stieglitz, S. (2019). Digital nudging and privacy: Improving decisions about self-disclosure in social networks. Behaviour & Information Technology.

  • Lallmahomed, M. Z. I., Lallmahomed, N., & Lallmahomed, G. M. (2017). Factors influencing the adoption of e-government services in Mauritius. Telematics and Informatics, 34(4), 57–72.

    Google Scholar 

  • Li, Y. (2011). Empirical studies on online information privacy concerns: Literature review and an integrative framework. Communications of the Association for Information Systems, 28, Article 28.

  • Lips, A. M., O’Neill, R., & Eppel, E. A. (2011). Cross-agency collaboration in New Zealand: An empirical study of information sharing practices, enablers and barriers in managing for shared social outcomes. International Journal of Public Administration, 34(4), 255–266.

    Google Scholar 

  • Looney, C. A., & Hardin, A. M. (2009). Decision support for retirement portfolio management: Overcoming myopic loss aversion via technology design. Management Science, 55(10), 1688–1703.

    Google Scholar 

  • Lowry, P. B., Moody, G. D., & Chatterjee, S. (2017). Using IT design to prevent cyberbullying. Journal of Management Information Systems, 34(3), 863–901.

    Google Scholar 

  • Madrian, B. C., & Shea, D. (2001). The power of suggestion: Inertia 401(k) participation and savings behavior. Quarterly Journal of Economics, 116(4), 1149–1187.

    Google Scholar 

  • Makene, B. (2009) The role of e-government in effective service delivery: a case study of Tanzania electric supply company limited (TANESCO).

  • Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355.

    Google Scholar 

  • McClure, D. L. (2000). Statement of David L. McClure, U.S. General Accounting Office, before the Subcommittee on Government Management, Information and Technology, Committee on Government Reform, House of Representatives. Available at: http://www.gao.gov.

  • McKenzie, C. R. M., Liersch, M. J., & Finkelstein, S. R. (2006). Recommendations implicit in policy defaults. Psychological Science, 17(5), 414–420.

    Google Scholar 

  • McKinsey (2019a). Infographic: What is good digital ID? Retrieved from https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/infographic-what-is-good-digital-id.

  • McKinsey (2019b). Digital identification: A key to inclusive growth. Retrieved from https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/digital-identification-a-key-to-inclusive-growth.

  • Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46(1), 81–95.

    Google Scholar 

  • Mirsch, T., Lehrer, C. and Jung, R. (2017). Digital nudging: Altering user behavior in digital environments. Proceedings of the 13th International Conference on Wirtschaftsinformatik, 634-648.

  • Naylor, R. W., Lamberton, C. P., & Norton, D. A. (2011). Seeing ourselves in others: Reviewer ambiguity, egocentric anchoring, and persuasion. Journal of Marketing Research, 48(3), 617–631.

    Google Scholar 

  • Nederhof, A. J. (1985). Methods of coping with social desirability Bias: A review. European Journal of Social Psychology, 15(3), 263–280.

    Google Scholar 

  • Olshavsky, R. W., & Granbois, D. H. (1979). Consumer decision-making fact or fiction. Journal of Consumer Research, 6(2), 93–100.

    Google Scholar 

  • Oxford English Dictionary (2018). Retrieved from https://en.oxforddictionaries.com/definition/nudge.

  • Palanisamy, R. and Mukerji, B. (2011). Security and privacy issues in E-government. In Shareef, M. a., archer, N. and Dutta, S. (Eds.), E-Government Service Maturity and Development: Cultural, Organizational and Technological Perspectives, 236–248..

  • Palmer, K. (2014). Psychology and 'nudges': Five tricks the taxman uses to make you pay £210m extra. Retrieved from https://www.telegraph.co.uk/finance/personalfinance/tax/11147321/Five-tricks-or-nudges-HMRC-uses-to-make-you-pay-210m-extra.html.

  • Parker, J. R., & Lehmann, D. R. (2011). When shelf-based scarcity impacts consumer preferences. Journal of Retailing, 87(2), 142–155.

    Google Scholar 

  • Pew Research Center (2019). Public Trust in Government: 1958-2019. Retrieved from https://www.people-press.org/2019/04/11/public-trust-in-government-1958-2019/.

  • Průša, J. (2015). E-identity: Basic building block of e-government. Proceedings of the IST-Africa Conference.

  • Rao, H., Greve, H. R., & Davis, G. F. (2001). Fool's gold: Social proof in the initiation and abandonment of coverage by wall street analysts. Administrative Science Quarterly, 46(3), 502–526.

    Google Scholar 

  • Rubel, A. P. and Jones, K. (2016). Data Analytics in Higher Education: Key Concerns and Open Questions. University of St. Thomas Journal of Law and Public Policy, 2017.

  • Sánchez-Torres, J. M., & Miles, I. (2017). The role of future-oriented technology analysis in e-government: A systematic review. European Journal of Futures Research, 5(15), 1–18.

    Google Scholar 

  • Sarrayrih, M. A., & Sriram, B. (2015). Major challenges in developing a successful e-government: A review on the Sultanate of Oman. Journal of King Saud University - Computer and Information Sciences, 27(2), 230–235.

    Google Scholar 

  • Schneider, D., Lins, S., Grupp, T., Benlian, A. and Sunyaev, A. (2017). Nudging Users into Online Verification: The Case of Carsharing Platforms. Proceedings of the 38th International Conference on Information Systems (ICIS).

  • Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118.

    Google Scholar 

  • Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: An interdisciplinary review. MIS Quarterly, 35(4), 989–1016.

    Google Scholar 

  • Smith, H. J., Milberg, J. S., & Burke, J. S. (1996). Information privacy: Measuring Individuals' concerns about organizational practices. Management Information Systems Quarterly, 20(2), 167–196.

    Google Scholar 

  • Steelman, Z. R., Hammer, B., & Limayem, M. (2014). Data collection in the digital age: Innovative alternatives to student samples. Management Information Systems Quarterly, 38(2), 355–378.

    Google Scholar 

  • Steffel, M., Williams, E. F., & Pogacar, R. (2016). Ethically deployed defaults: Transparency and consumer protection through disclosure and preference articulation. Journal of Marketing Research, 53(5), 865–880.

    Google Scholar 

  • Sunstein, C. R. (2015). Choosing not to choose: Understanding the value of choice. Oxford: Oxford University Press.

    Google Scholar 

  • Sunstein, C. R. (2014). Nudging: A very short guide. Journal of Consumer Policy, 37(4), 583–588.

    Google Scholar 

  • Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness (p. 293). New Haven, CT: Yale University Press.

    Google Scholar 

  • Thaler, R. H., & Sunstein, C. R. (2003). Libertarian Paternalism. The American Economic Review, 93(2), 175–179.

    Google Scholar 

  • The Economist (2017). Policymakers around the world are embracing behavioural science. Retrieved from https://www.economist.com/international/2017/05/18/policymakers-around-the-world-are-embracing-behavioural-science.

  • The Guardian (2019). The Cambdrige Analytica scandal changed the world – But it didn’t change Facebook. Retrieved from https://www.theguardian.com/technology/2019/mar/17/the-cambridge-analytica-scandal-changed-the-world-but-it-didnt-change-facebook.

  • Theotokis, A., & Manganari, E. (2015). The impact of choice architecture on sustainable consumer behavior: The role of guilt. Journal of Business Ethics, 131(2), 423–437.

    Google Scholar 

  • Thies, F., Wessel, M., & Benlian, A. (2016). Effects of social interaction dynamics on platforms. Journal of Management Information Systems, 33(3), 843–873.

    Google Scholar 

  • Toulmin, S. E. (1958). The use of argument. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

    Google Scholar 

  • United Nations (2018). E-Government Survey 2018: Gearing E-Government to Support Transformation Towards Sustainable and Resilient Societies. Retrieved from https://publicadministration.un.org/egovkb/Portals/egovkb/Documents/un/2018-Survey/E-Government%20Survey%202018_FINAL%20for%20web.pdf.

  • Van Herpen, E., Pieters, R., & Zeelenberg, M. (2009). When demand accelerates demand: Trailing the bandwagon. Journal of Consumer Psychology, 19(3), 302–312.

    Google Scholar 

  • Wang, C., Zhang, X., & Hann, I.-H. (2018). Socially nudged: A quasi-experimental study of friends’ social influence in online product ratings. Information Systems Research, 29(3), 3–6.

    Google Scholar 

  • Warkentin, M., Gefen, D., Pavlou, P. A., & Rose, G. M. (2002). Encouraging citizen adoption of e-government by building trust. Electronic Markets, 12(3), 157–162.

    Google Scholar 

  • Weimann, M., Schneider, C., & vom Brocke, J. (2016). Digital nudging. Business & Information Systems Engineering, 56(6), 433–436.

    Google Scholar 

  • Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 798–824.

    Google Scholar 

  • Xu, H., & Gupta, S. (2009). The effects of privacy concerns and personal innovativeness on potential and experienced customers' adoption of location-based services. Electronic Markets, 19(2-3), 137–149.

    Google Scholar 

  • Xu, H., Dinev, T., Smith, H. J. & Hart, P. (2008). Examining the Formation of Individual's Privacy Concerns: Toward an Integrative View. Proceedings of the International Conference of Information Systems (ICIS).

  • Yang, T. M., & Maxwell, T. A. (2011). Information-sharing in public organizations: A literature review of interpersonal, intra-organizational and inter-organizational success factors. Government Information Quarterly, 28(2), 164–175.

    Google Scholar 

  • Zhang, J. (2010). The sound of silence: Observational learning in the US kidney market. Marketing Science, 29(2), 315–335.

    Google Scholar 

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Appendix

Appendix

Table 4 Measurement items
Table 5 Frequency distribution of occupation scale
Table 6 Frequency distribution of education scale
Table 7 Systematic literature overview of digital nudging in privacy contexts

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Schneider, D., Klumpe, J., Adam, M. et al. Nudging users into digital service solutions. Electron Markets 30, 863–881 (2020). https://doi.org/10.1007/s12525-019-00373-8

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