How Behavioral Economics Informs Website Design
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At the 2012 Face of Finance Conference, at Bentley University, in Waltham, MA, Eric Gold (Fidelity Investments) presented "How Behavioral Economics Informs Website Design".
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How Behavioral Economics Informs Website Design
- 1. How Behavioral Economics Informs Website Design Eric Gold, PhD Fidelity Investments October 24, 2012
- 2. How Behavioral Economics Informs Website Design Getting in the way of good decision making Seemingly inconsequential design decisions Taking advantage of the web Advice
- 3. Getting in the Way of Good Decision Making
- 4. Anchoring Getting in the way of good decision making
- 5. Anchoring Question: What percent of UN members are African countries? But, before answering, spin the wheel of fortune Mean Mean answer: answer: 25% 45% Tversky & Kahneman (1974)
- 6. Choice Paralysis Getting in the way of good decision making
- 7. Choice Paralysis 6 24 kinds of jams kinds of jams Shoppers who 40% 60% stopped Iyengar & Lepper (2000)
- 8. Choice Paralysis 6 24 kinds of jams kinds of jams Shoppers who 40% 60% stopped Shoppers who bought 30% 3% jam Iyengar & Lepper (2000)
- 9. Choice Paralysis 7000 Mutual Funds 5000 3000 1000 NYSE 1940 1960 1980 2000
- 10. Choice Paralysis 80% PARTICIPATION 70% 60% 50% 0 20 40 60 FUNDS OFFERED Iyengar et al. (2003)
- 11. Confirmation Bias Getting in the way of good decision making
- 12. Confirmation Bias If there is a vowel on one side, then there is an even number on the other. Which card(s) would you need to turn over to decide whether the statement is true or false? E K 4 7 Johnson-Laird (1983)
- 13. Irrelevant Information Getting in the way of good decision making
- 14. Irrelevant Information Use of irrelevant information increases with time, effort and cost of obtaining the information People are more likely to pursue irrelevant information for complex tasks People consider information relevant if they must wait for it Even mentioning information makes it seem more relevant People overweight recent information The internet is full of irrelevant advice Bastardi & Shafir (1998), Baron, et al. (1988), DeBondt & Thaler (1985)
- 15. Irrelevant Information You are considering registering for a course in your major that has very interesting subject matter and will not be offered again before you graduate. While the course is reputed to be taught by an excellent professor, you have discovered that he will be on leave, and that a less popular professor will be teaching the course. Immedia After Total Simple version te waiting (a) Decide to register for the course (82%) Simple Register 82 - 82 (b) Decide not to register for the course (18%) Not 18 - 18 register Uncertain version Uncertain Register 42 29 71 (a) Decide to register for the course (42%) Not 2 27 29 (b) Decide not to register for the course (2%) register (c) Wait until tomorrow (after finding out if the regular professor will be teaching) to decide about registering for the course (56%) If you chose c in the question above, please answer the following: It is the next day, and you find out that the less popular professor will be teaching the course. (a) Decide to register for the course (29%) (b) Decide not to register for the course (27%) Bastardi & Shafir (1998)
- 16. Recommendations Dont use default numbers unless meaningful. Make sure anchors represent a sensible estimation. Keep users away from irrelevant information Afford disconfirming evidence
- 17. Recommendations Organize choices Give strategies for making choices Avoid choices that are essentially the same Limit choices Use defaults
- 20. Framing Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Framing I: Which would you choose? A B 200 people will be saved 1/3 probability 600 people will be saved 2/3 probability no people will be saved Tversky and Kahneman (1981)
- 21. Framing Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Framing I: Which would you choose? A B 200 people will be saved 1/3 probability 600 people will be saved 2/3 probability no people will be saved Framing II: Which would you choose? A B 400 people will die 1/3 probability that nobody will die 2/3 probability that 600 people will die Tversky and Kahneman (1981)
- 22. Framing Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Framing I: Which would you choose? A B 200 people will be saved 1/3 probability 600 people will be saved 2/3 probability no people will be saved 72% 28% Framing II: Which would you choose? A B 400 people will die 1/3 probability that nobody will die 2/3 probability that 600 people will die 22% 78% Tversky and Kahneman (1981)
- 23. Framing Surcharge for Credit vs. Discount for Cash
- 26. Attraction Effect Seeming inconsequential design decisions
- 27. Attraction Effect Patient suffers from migraine headaches that: Last about 3 hours. Involve intense pain, nausea, dizziness, and hypersensitivity. Occur about 100 of those days/year (8.3 per month). You are considering 3 medications. All have same minor side effects, and are pills taken 1/day. Each differs in effectiveness and cost. The patient pays cost. Chapman & Malik (1995)
- 28. Attraction Effect Which would you choose? Drug A Reduces the number of headaches from 100 days with a headache per year to 30 days with a headache per year. It costs $350 per year. Drug B Reduces the number of headaches from 100 days with a headache per year to 50 days with a headache per year. It costs $100 per year. Chapman & Malik (1995)
- 29. Attraction Effect Drug A Reduces the number of headaches 36% from 100 days with a headache per year to 30 days with a headache per year. It costs $350 per year. Drug B Reduces the number of headaches 64% from 100 days with a headache per year to 50 days with a headache per year. It costs $100 per year. Chapman & Malik (1995)
- 30. Attraction Effect Drug A Reduces the number of headaches from 100 days with a headache per year to 30 days with a headache per year. It costs $350 per year. Drug B Reduces the number of headaches from 100 days with a headache per year to 50 days with a headache per year. It costs $100 per year. Drug C Reduces the number of headaches from 100 days with a headache per year to 60 days with a headache per year. It costs $100 per year. Chapman & Malik (1995)
- 31. Attraction Effect 2 choices 3 choices Drug A Reduces the number of headaches 36% 9% from 100 days with a headache per year to 30 days with a headache per year. It costs $350 per year. Drug B Reduces the number of headaches 64% 81% from 100 days with a headache per year to 50 days with a headache per year. It costs $100 per year. Drug C Reduces the number of headaches 10% from 100 days with a headache per year to 60 days with a headache per year. It costs $100 per year. Chapman & Malik (1995)
- 32. Joint vs. Separate Presentation Seeming inconsequential design decisions
- 33. Joint vs. Separate Presentation Dictionary A: 10,000 entries, like new Dictionary B: 20,000 entries, the cover is torn Jointly Dictionary A: 10,000 entries, like new - $19 Dictionary B: 20,000 entries, the cover is torn - $27 Separately Dictionary A: 10,000 entries, like new - $24 Dictionary B: 20,000 entries, the cover is torn - $20 Hsee(1996)
- 34. Diversification Bias Seeming inconsequential design decisions
- 35. Diversification Bias Read & Loewenstein (1995)
- 36. Diversification Bias Combined choice: 100% chose different candy bars Read & Loewenstein (1995)
- 37. Diversification Bias Combined choice: 100% chose different candy bars Separate choice: 48% chose different candy bars Read & Loewenstein (1995)
- 38. Diversification Bias 1/n strategy participants in 401(k) plans distribute their contributions more or less evenly over the funds offered. Implied Allocation Allocation Fund A Fund B for Fund A for Fund A Stocks Bonds 54% Stocks 遜 Stocks, 遜 Bonds 遜 Stocks, 遜 Bonds Bonds Benartzi & Thaler (1999)
- 39. Diversification Bias 1/n strategy participants in 401(k) plans distribute their contributions more or less evenly over the funds offered. Implied Allocation Allocation Fund A Fund B for Fund A for Fund A Stocks Bonds 54% Stocks 遜 Stocks, 遜 Bonds 46% 21% 遜 Stocks, 遜 Bonds Bonds Benartzi & Thaler (1999)
- 40. Diversification Bias 1/n strategy participants in 401(k) plans distribute their contributions more or less evenly over the funds offered. Implied Allocation Allocation Fund A Fund B for Fund A for Fund A Stocks Bonds 54% Stocks 遜 Stocks, 遜 Bonds 46% 21% 遜 Stocks, 遜 Bonds Bonds 69% 87% Benartzi & Thaler (1999)
- 41. Recommendations Run usability tests to determine best frame When appropriate, avoid negative frames that may paralyze the customer Encourage making decisions all at once, not piecemeal
- 42. Taking Advantage of the Web
- 43. Disambiguation Taking advantage of the web
- 44. Ambiguity Aversion An urn contains 30 red balls and 60 additional balls that are either yellow or black Gamble I: A: $100 if red is drawn B: $100 if black is drawn Gamble II: A: $100 if red or yellow is drawn B: $100 if black or yellow is drawn Ellsberg (1961)
- 45. Disambiguation Some subjects were tested with a variation of the Ellsberg Paradox, measuring ambiguity aversion. Other subjects were tested for risk aversion. Response to ambiguity Response to risk Hsu et al. (2006)
- 46. Discounting of Ambiguous Information Earlier this year you decided to exercise and opted for tennis. You purchased a one-year season ticket at a luxurious tennis club in your neighborhood. This means that during the year you can play on each Wednesday afternoon. The membership fee is 600 Euros for the entire year, and the costs have to be paid monthly (50 Euros per month). After a few weeks you injure your elbow, and the pain progresses. After two months it appears that you have developed tennis elbow. There are two options: either you continue to play and retain your season ticket for the year; or you quit, and return the season ticket to the club. The club has a standard arrangement: if you decide to return the season ticket, you are granted a refund so that you not have to play for the months to come. What would you do? Control Low Cost High Cost Ambiguous Continue 16% 38% 52% 22% Stop 84% 62% 48% 78% Van Dijk & Zeelenberg (2003)
- 47. Disjunction Effect Shafir & Tversky (1992)
- 48. Trade-offs Taking advantage of the web
- 50. Trade-offs Satisficing Elimination by aspects Most important attribute Majority of confirming dimensions Avoiding the decision Simon (1969), Fishburn (1974), Russo & Dosher (1983), Beattie & Barlas (2001)
- 51. Recommendations Run studies to determine what trade-off strategies customers use. Make sure that important possibilities are presented as trade-offs and understood that way. Make clear what attributes are important. Consider asking users to rate utilities and weights explicitly. When a trade-off is required, use similar attributes. Inform users that they can change their mind (when this is so).
- 52. Recommendations Identify and resolve ambiguities Build tools that dont needlessly resolve ambiguity
- 53. Advice
- 55. Advisors: This is not how it works We often expect that people will just do what we tell them Problem to solve Advisor Request for help The Judge (me) Advice Just do it! Swoll & Sniezek (2005), Gino & Moore (2006), Rantilla & Budescu (1999)
- 56. Advisors: This is not how it works We often expect that people will just do what we tell them sometimes without their even asking! Problem to solve ?! Advisor The Judge (me) Advice Just do it! Swoll & Sniezek (2005), Gino & Moore (2006), Rantilla & Budescu (1999)
- 57. Advisors: The Judge-Advisor System Judges (i.e., people) make decisions with or without one or more advisors. Advisors Problem to solve Advice The Judge (me) What gives the Judge confidence in the advice? Decision Swoll & Sniezek (2005), Gino & Moore (2006), Rantilla & Budescu (1999)
- 58. Changing Minds Information Acquisition Subjects were asked to choose a mountain bike Subjects were presented with either 5 (low complexity), 9 (medium complexity), or 13 (high complexity) possible bikes Each bike was rated on 6 attributes Schrah, Dalal & Sniezek (2006)
- 59. Changing Minds Information Acquisition Low Medium High complexity complexity complexity Pre-Advice Post- Pre- Post- Pre- Post- Advice Advice Advice Advice Advice Depth of search 2.41 1.28 2.16 0.69 1.45 0.49 Variability of search - 3.96 2.40 7.38 2.46 8.15 2.42 attributes Variability of search - 5.46 6.27 6.10 5.15 5.22 4.15 alternatives Search pattern -0.05 0.16 -0.17 0.43 -0.02 0.25 Latency of search 1.18 1.56 0.92 1.71 1.20 1.65 Proportion of 0.96 0.74 1.00 0.43 1.00 0.40 alternatives searched Proportion of 0.31 0.64 0.20 0.62 0.18 0.54 information search dedicated to selected/recommended alternative Schrah, Dalal & Sniezek (2006)
- 61. Egocentric Discounting Phase 1 In what year was the Suez Canal first opened for use? Your best estimate____ Phase 2 In what year was the Suez Canal first opened for use? Your previous estimate was 1905 The best estimate of advisor K was 1830 Your final best estimate ____ Judges Weight of knowledge advice High 0.20 Low 0.33 Yaniv (2004)
- 62. Others Advice Phase 1 In what year was the Suez Canal first opened for use? Your best estimate____ Phase 2 In what year was the Suez Canal first opened for use? Your previous estimate was 1905 The best estimate of advisor K was 1830 Your final best estimate ____ Distance Near Intermediate Far Decision Makers Knowledge High 0.31 0.28 0.23 Low 0.38 0.34 0.30 Yaniv (2004)
- 63. Recommendations Let the customers develop their own hypotheses Keep a clear and consistent position Base advice on multiple sources Keep advice relevant Encourage people to consider all available options
- 64. Conclusion
- 65. Topics Emotions Regret Anxiety Fear Overconfidence Financial literacy Numeracy Inertia Mental accounting Risk communication