Using Interactive Information Labels to Assist Decision Making Under Uncertainty: The Case for Long-term Saving

Product information labels can help users understand complex information leading them to make better decisions. One area where consumers are particularly prone to make costly decision-making errors is long-term saving, which requires understanding of complex concepts such as uncertainty and trade-offs. While most people are poorly equipped to deal with such concepts, interactive design can potentially help users make better decisions. We developed an interactive information label to assist consumers with retirement saving decision-making. To evaluate it, we exposed 382 users to one of three user interface conditions in a retirement saving simulator where they made 35 yearly decisions under changing circumstances. We found significantly better ability of users to reach their goals with the information label. Furthermore, users who interacted with the label made better decisions than those who were presented with a static information label. Lastly, we found the label particularly effective in helping novice savers.

[1]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[2]  Kent D. Daniel,et al.  Measuring mutual fund performance with characteristic-based benchmarks , 1997 .

[3]  Henry Been-Lirn Duh,et al.  To Risk or Not to Risk?: Improving Financial Risk Taking of Older Adults by Online Social Information , 2015, CSCW.

[4]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[5]  Ali Hortaçsu,et al.  Product Differentiation, Search Costs, and Competition in the Mutual Fund Industry: A Case Study of S&P 500 Index Funds , 2003 .

[6]  E. Haley,et al.  Adherence of Retirement Mutual Fund Providers to the Securities and Exchange Commission (SEC)’s Advertising Guidance: Provision and Readability of Advertising Disclosure , 2011 .

[7]  Lorrie Faith Cranor,et al.  Standardizing privacy notices: an online study of the nutrition label approach , 2010, CHI.

[8]  Melissa R. Wong,et al.  Impact of a letter-grade program on restaurant sanitary conditions and diner behavior in New York City. , 2015, American journal of public health.

[9]  Carol Byrd-Bredbenner,et al.  The inherent educational qualities of nutrition labels , 2001 .

[10]  Nick Feamster,et al.  Helping users shop for ISPs with internet nutrition labels , 2011, HomeNets '11.

[11]  R. Thaler,et al.  Save More Tomorrow™: Using Behavioral Economics to Increase Employee Saving , 2004, Journal of Political Economy.

[12]  David A. Shamma,et al.  Money talks: tracking personal finances , 2014, CHI.

[13]  Andrew F. Monk,et al.  Pay or delay: the role of technology when managing a low income , 2014, CHI.

[14]  John Riedl,et al.  Recommender systems: from algorithms to user experience , 2012, User Modeling and User-Adapted Interaction.

[15]  Jodi Forlizzi,et al.  Mining behavioral economics to design persuasive technology for healthy choices , 2011, CHI.

[16]  Andrew Howes,et al.  Informing decisions: how people use online rating information to make choices , 2011, CHI.

[17]  Jill E. Fisch,et al.  Why Do Retail Investors Make Costly Mistakes? An Experiment on Mutual Fund Choice , 2014 .

[18]  Francesco Lisi,et al.  On the Role of Risk in the Morningstar Rating for Mutual Funds , 2009 .

[19]  Oded Nov,et al.  Influencing Retirement Saving Behavior with Expert Advice and Social Comparison as Persuasive Techniques , 2015, PERSUASIVE.

[20]  Henrik Artman,et al.  Computer Support for Financial Advisors and Their Clients: Co-creating an Investment Plan , 2015, CSCW.

[21]  Li Chen,et al.  Evaluating recommender systems from the user’s perspective: survey of the state of the art , 2012, User Modeling and User-Adapted Interaction.

[22]  Zoltan Foley-Fisher,et al.  Health shelf: interactive nutritional labels , 2010, CHI EA '10.

[23]  Vera D. Khovanskaya,et al.  Reviewing reflection: on the use of reflection in interactive system design , 2014, Conference on Designing Interactive Systems.

[24]  Robert C. Merton,et al.  The crisis in retirement planning , 2014 .

[25]  Izak Benbasat,et al.  The Nature and Consequences of Trade-Off Transparency in the Context of Recommendation Agents , 2014, MIS Q..

[26]  Nikolaos C. Kourogenis,et al.  Selectivity, Market Timing and the Morningstar Star-Rating System , 2009 .

[27]  Lorrie Faith Cranor,et al.  A "nutrition label" for privacy , 2009, SOUPS.

[28]  S. James The contribution of behavioral economics to tax reform in the United Kingdom , 2012 .

[29]  S. Mullainathan,et al.  The Market for Financial Advice: An Audit Study , 2012 .

[30]  Eric C. Larson,et al.  The design and evaluation of prototype eco-feedback displays for fixture-level water usage data , 2012, CHI.

[31]  R. Thaler,et al.  The Behavioral Economics of Retirement Savings Behavior , 2007 .

[32]  Keith Jakob,et al.  Are Mutual Fund Managers Selecting the Right Benchmark Index , 2011 .

[33]  Madhu C. Reddy,et al.  Exploring the perceptions and use of electronic medical record systems by non-clinicians , 2014, Conference on Designing Interactive Systems.

[34]  Oded Nov,et al.  Informing and Improving Retirement Saving Performance using Behavioral Economics Theory-driven User Interfaces , 2015, CHI.