Understanding User Preferences of Digital Privacy Nudges - A Best-Worst Scaling Approach

Digital nudging in privacy has become more important to protect users of information systems while working with privacy-related data. Nudging is about altering a user’s behavior without forbidding any options. Several approaches exist to “nudge” users to change their behavior. Regarding the usage of digital privacy nudges, research still has to understand the meaning and relevance of individual nudges better. Therefore, this paper compares the preferences of users for different digital nudges. To achieve this goal, it presents the results of a so-called best-worst scaling. This study contributes to theory by providing a better understanding of user preferences regarding design variations of digital nudges. We support practitioners by giving implications on how to design digital nudges in terms of user preferences.

[1]  T. Peters,et al.  Best--worst scaling: What it can do for health care research and how to do it. , 2007, Journal of health economics.

[2]  Jane Z. Sojka,et al.  Communicating through pictures and words: Understanding the role of affect and cognition in processing visual and verbal information , 2006 .

[3]  Sarah Spiekermann,et al.  Online social networks: why we disclose , 2010, J. Inf. Technol..

[4]  Ninghui Li,et al.  Using Context-Based Password Strength Meter to Nudge Users' Password Generating Behavior: A Randomized Experiment , 2017, HICSS.

[5]  Jan vom Brocke,et al.  Digital Nudging , 2016, Business & Information Systems Engineering.

[6]  Aad P. A. van Moorsel,et al.  Nudging towards security: developing an application for wireless network selection for android phones , 2015, BCS HCI.

[7]  Evangelos Karapanos,et al.  23 Ways to Nudge: A Review of Technology-Mediated Nudging in Human-Computer Interaction , 2019, CHI.

[8]  Alessandro Acquisti,et al.  Follow My Recommendations: A Personalized Privacy Assistant for Mobile App Permissions , 2016, SOUPS.

[9]  Steven H. Cohen Maximum Difference Scaling: Improved Measures of Importance and Preference for Segmentation , 2003 .

[10]  Chris Arney Nudge: Improving Decisions about Health, Wealth, and Happiness , 2015 .

[11]  Pamela J. Wisniewski,et al.  Making privacy personal: Profiling social network users to inform privacy education and nudging , 2017, Int. J. Hum. Comput. Stud..

[12]  Christiane Lehrer,et al.  Making Digital Nudging Applicable: The Digital Nudge Design Method , 2018, ICIS.

[13]  Cass R. Sunstein,et al.  Nudging: A Very Short Guide , 2014, How Change Happens.

[14]  J. Louviere,et al.  Some probabilistic models of best, worst, and best–worst choices , 2005 .

[15]  Moritz von Hoffen,et al.  A Method for Measuring User Preferences in Information Systems Design Choices , 2015, ECIS.

[16]  James Zijun Wang,et al.  An investigation into three visual characteristics of complex scenes that evoke human emotion , 2017, 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII).

[17]  Björn Niehaves,et al.  Standing on the Shoulders of Giants: Challenges and Recommendations of Literature Search in Information Systems Research , 2015, Commun. Assoc. Inf. Syst..

[18]  Serge Egelman,et al.  The Myth of the Average User: Improving Privacy and Security Systems through Individualization , 2015, NSPW.

[19]  Andreas Janson,et al.  Is it all about having Fun? - Developing a Taxonomy to gamify Information Systems , 2018, ECIS.

[20]  Daniel M. Oppenheimer,et al.  Instructional Manipulation Checks: Detecting Satisficing to Increase Statistical Power , 2009 .

[21]  Tobias Potthoff,et al.  The Dinu-Model - a Process Model for the Design of Nudges , 2017, ECIS.

[22]  Alexander Maedche,et al.  How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies , 2019, Journal of Behavioral and Experimental Economics.

[23]  Bryan Orme uracy of HB Estimation in MaxDiff Experiments , 2005 .

[24]  Alfred Benedikt Brendel,et al.  Towards a Unified Understanding of Digital Nudging by Addressing its Analog Roots , 2019, PACIS.

[25]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[26]  Alessandro Acquisti,et al.  Engineering Information Disclosure: Norm Shaping Designs , 2016, CHI.

[27]  Paul Jen-Hwa Hu,et al.  Examining the Mediating Roles of Cognitive Load and Performance Outcomes in User Satisfaction with a Website: A Field Quasi-Experiment , 2017, MIS Q..

[28]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[29]  J. Louviere,et al.  Determining the Appropriate Response to Evidence of Public Concern: The Case of Food Safety , 1992 .

[30]  Yang Wang,et al.  Nudges for Privacy and Security , 2017, ACM Comput. Surv..

[31]  Stefan Stieglitz,et al.  Enterprise Digital Nudging: Between adoption gain and unintended rejection , 2018, AMCIS.

[32]  R. Hertwig,et al.  Nudging and Boosting: Steering or Empowering Good Decisions , 2017, Perspectives on psychological science : a journal of the Association for Psychological Science.

[33]  John M. Blythe,et al.  Personality and Social Framing in Privacy Decision-Making: A Study on Cookie Acceptance , 2016, Front. Psychol..

[34]  Dennis Kaiser Individualized Choices and Digital Nudging: Multiple Studies in Digital Retail Channels , 2018 .

[35]  Kai Lung Hui,et al.  Disclosure : Motivators and Measurements , 2006 .

[36]  Ali Sunyaev,et al.  Cloud Service Certifications: Measuring Consumers' Preferences For Assurances , 2013, ECIS.

[37]  Jordan J. Louviere,et al.  Measuring values using best‐worst scaling: The LOV example , 2007 .

[38]  Rong Yan,et al.  Social influence in social advertising: evidence from field experiments , 2012, EC '12.

[39]  Stefan Stieglitz,et al.  Digital nudging and privacy: improving decisions about self-disclosure in social networks , 2019, Behav. Inf. Technol..

[40]  Christiane Lehrer,et al.  Digital Nudging: Altering User Behavior in Digital Environments , 2017, Wirtschaftsinformatik.

[41]  Nicholas Micallef,et al.  A Serious Game Design: Nudging Users' Memorability of Security Questions , 2017, ArXiv.

[42]  Matthew Smith,et al.  Using personal examples to improve risk communication for security & privacy decisions , 2014, CHI.

[43]  Bart P. Knijnenburg,et al.  AIS Electronic Library (AISeL) , 2022 .

[44]  Jordan J. Louviere,et al.  An introduction to the application of (case 1) best–worst scaling in marketing research , 2013 .

[45]  Jörg Schmidtke,et al.  Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments , 2013, European Journal of Human Genetics.