Behavioral Economics, Frameworks, Design Patterns
- 1. Behavioral Economics Biases, Design Patterns, Solutions 1 Thursday, August 26, 2010
- 2. Popularity Biases, Design Patterns, Solutions 2 Thursday, August 26, 2010
- 3. Outline What it is not! Talk Exhaustive survey of biases and heuristics How Behavioral Economics came to be? Quick survey of biases and cognitive Pedantic one-way ramblings heuristics Theoretically/Academically rigorous Stimulate ideas, thinking and discussions Develop Design Patterns & Solutions Framework based on BE Learn & Explore applications of these ideas The Good, the Bad and the Ugly Biases, Design Patterns, Solutions 3 Thursday, August 26, 2010
- 4. This is not the end! Design Patterns Survey of Behavioral Solutions Economics Frameworks Past, Present, Future Psych & Econ Thinking Models Choice Architecture Rationality Frameworks: Applications for non-gaming Heuristics Thaler: NUDGE online environments Biases Cialdini: RSS-CAL New Product Features Prospect Theory Loss/Gain Framework Drive User Engagement Intertemporal Choice Drive User Satisfaction Hyberbolic discounting Survey of Game User Behavior Mechanics Patterns Biases, Design Patterns, Solutions 4 Thursday, August 26, 2010
- 5. Chocolate cake or fruit salad Cognitive Load Biases, Design Patterns, Solutions 5 Thursday, August 26, 2010
- 6. Organ Donation - Saving Lives Biases, Design Patterns, Solutions 6 Thursday, August 26, 2010
- 7. Evolution of BE Classical Economics Adam Smith 1776: The Wealth of Nations Economics closely linked to psychology Ricardo John Mill Biases, Design Patterns, Solutions 7 Thursday, August 26, 2010
- 8. Evolution of BE Prospect Theory 1870s Bounded Rationality Modern Decision Theory Framing Effects Neo-classical Economics 1960s: Herb Simon 1940s: Von Neumann 1980: Kahneman & Tversky Keynesian Economics 1975: Hyperbolic Supply & Demand discounting Rational economic agents 1955: Kahneman & Tversky: cognitive psychology experiments Biases, Design Patterns, Solutions 8 Thursday, August 26, 2010
- 9. Evolution of BE 1980s: Richard Thaler Integration of Econ & Psych 2002: Kahneman gets begins: Humans v/s Econs Nobel price in Economics 2000 2008 1997: Special issue of Journal of Economics devoted to BE Biases, Design Patterns, Solutions 9 Thursday, August 26, 2010
- 10. Quiz Time! 10 Thursday, August 26, 2010
- 11. Linda Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations. Representativeness (Similarity) Rank the following in order of likelihood? Heuristic/Shortcut C: Linda is active in the feminist movement F: Linda is a bank teller H>F Conjunction G: Linda is an insurance salesperson Fallacy H: Linda is a bank teller and is active in the feminist movement Biases, Design Patterns, Solutions 11 Thursday, August 26, 2010
- 12. Thinking Emotional Effortless Slower Explicit Automatic Implicit Conscious Logical Fast Shortcuts Effortful Deliberate System I System II Biases, Design Patterns, Solutions 12 Thursday, August 26, 2010
- 13. Dating & happiness 0.11 Anchoring Heuristic 0.62 Biases, Design Patterns, Solutions 13 Thursday, August 26, 2010
- 14. Coin toss Which of the following series of coin tosses are more likely? Representativeness (Similarity) A: H-T-H-T-T-H Heuristic B: H-H-H-T-T-T C: H-H-H-H-H-T A>B>C Gambler’s Fallacy Biases, Design Patterns, Solutions 14 Thursday, August 26, 2010
- 15. Flight tomorrow Monday evening 10:00pm: Your boss calls to tell you that you must be at the South Beach office by 10:00 am tomorrow Representativeness Only 5 flights in the morning can get you their by (Similarity) 9:30 am. All are booked solid. Heuristic The (unbiased and independent) probability of getting on each of the flights are 30%, 25%, 15%, 20% and 25% Disjunctive Bias Do you expect to get on one of the flights? Biases, Design Patterns, Solutions 15 Thursday, August 26, 2010
- 16. Causes of Death Rank order of deaths in the US (1990 - 2000) Smoking 435K Availability Heuristic Poor diet and physical activity 400K Auto accidents 43K Gun violence Ease of Recall 29K Fallacy (Vividness, Recency) Drugs 17K Biases, Design Patterns, Solutions 16 Thursday, August 26, 2010
- 17. Herding Biases, Design Patterns, Solutions 17 Thursday, August 26, 2010
- 18. Rationality Everyday use Economists, Decision Theorists Reasonable - views are realistic Logic Actions guided by self-interest & values Internally consistent beliefs No requirement on reasonability Entitled to belief/want anything “80% chance that it will rain today” implies “20% chance it will not” Methodological function Simplifies theory construction Predict the behavior of markets Biases, Design Patterns, Solutions 18 Thursday, August 26, 2010
- 19. Rationality Dominance: If prospect A > prospect B (in at least one respect), then A should be preferred to B Invariance: Preference order is independent on the manner in which the prospects are described Biases, Design Patterns, Solutions 19 Thursday, August 26, 2010
- 20. Framing Participants were asked to imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume the exact scientific estimate of the consequences of the programs are as follows: Biases, Design Patterns, Solutions 20 Thursday, August 26, 2010
- 21. Framing The first group of participants were presented with a choice between two programs: 72% Program A: 200 people will be saved 28% Program B: there is a one-third probability that 600 people will be saved, and a two-thirds probability that no people will be saved Biases, Design Patterns, Solutions 21 Thursday, August 26, 2010
- 22. Framing The second group of participants were presented with the choice between: 22% Program C: 400 people will die 78% Program D: there is a one-third probability that nobody will die, and a two-third probability that 600 people will die Biases, Design Patterns, Solutions 22 Thursday, August 26, 2010
- 23. Choice Choose between: E: 25% chance to win $240 and 75% chance to lose $760 F: 25% chance to win $250 and 75% chance to lose $750 100% Biases, Design Patterns, Solutions 23 Thursday, August 26, 2010
- 24. Concurrent Choices Imagine that you face the following pair of concurrent decisions Decision I: Choose between: A: A sure gain of $240 84% B: 25% chance to gain $1000 and 75% chance to gain nothing 16% Decision II: Choose between: C: A sure loss of $750 13% D: 75% chance to lose $1000 and 25% chance to lose nothing 87% Biases, Design Patterns, Solutions 24 Thursday, August 26, 2010
- 25. Prospect Theory Framing: Value defined on gains and losses (relative to a reference point) rather than on total wealth Diminishing sensitivities in the domain of gains and losses Loss Aversion: considerably steeper for losses than for gains Biases, Design Patterns, Solutions 25 Thursday, August 26, 2010
- 26. Summary of Biases Biases, Design Patterns, Solutions 26 Thursday, August 26, 2010
- 27. Convergence of BE & Solutions How social, cognitive and emotional factors influence decision making, trade-offs, options Establish relationships between what is observed and the underlying emotions & biases Reconsider Anticipate Develop the solution problems informed space with with new hypotheses a new lens solutions Biases, Design Patterns, Solutions 27 Thursday, August 26, 2010
- 28. Gas Mileage & Car Shopping Biases, Design Patterns, Solutions 28 Thursday, August 26, 2010
- 29. MPG Illusion Focus on Car Overvalue large jumps efficiency between efficient cars MPG MPG Illusion Undervalue small mpg But obscures the improvements on value of improvements inefficient cars 1200 900 Gallons Per 10,000 Miles 600 300 0 5 10 15 20 25 30 35 40 45 50 55 Miles Per Gallon Biases, Design Patterns, Solutions 29 Thursday, August 26, 2010
- 30. Next Steps Increase Salience: Cost Meter Give Feedback: Prius battery/fuel consumption display Mappings: Virtual plant Biases, Design Patterns, Solutions 30 Thursday, August 26, 2010
- 31. Design Patterns 31 Thursday, August 26, 2010
- 32. Gains NOW, Losses later Intertemporal Hyberbolic Loss Aversion Choice Discounting Optimism Bias Gains NOW, Losses Later Increase present gains Delay losses Shift gains from the future Delay losses/cost or Frequent flyer into present payment to sometime in cards the future Break up future gains, so Credit cards Break up present losses, that pieces can be shifted min payments so that pieces can be to present shifted to the future Biases, Design Patterns, Solutions 32 Thursday, August 26, 2010
- 33. Break up Gains, Lump Losses Prospect Loss Aversion Theory Geico advertises discounts separately Break up Gains Lump Losses together Travel insurance on Which smaller losses can travelocity.com be combined into one? Separate large gains and incremental achievements Talk about larger gains in terms of smaller gains Phrase abstract gains into concrete gains Biases, Design Patterns, Solutions 33 Thursday, August 26, 2010
- 34. Smarter Defaults Status Quo Bias Opt-out for organ donation Smarter/Desirable Defaults Opt-out for 401K How can we capture the the desired behavior as a enrollment default option? Reduce effort involved for Eliminate unnecessary the desired behavior information Reveal bits of relevant information over time Biases, Design Patterns, Solutions 34 Thursday, August 26, 2010
- 35. Ownership Endowment Status Quo Loss Aversion Effect Bias Ownership Premium (cables) Emphasize the risk of channels losing an owned item? Can we create a perception of user ownership? Biases, Design Patterns, Solutions 35 Thursday, August 26, 2010
- 36. Shift Reference Point Loss Aversion Framing Shift the current reference point How are customers “Biggest loser” TV comparing losses & show gains? How can the reference point be shifted? Biases, Design Patterns, Solutions 36 Thursday, August 26, 2010
- 37. Reframe losses & gains Loss Aversion Framing Opt-out for organ donation Reframe Premium (cables) Reframe to emphasize the channels relevant gains and losses? Use “loss” language: “If you do not do X, you will lose Y” Biases, Design Patterns, Solutions 37 Thursday, August 26, 2010
- 38. Loss with the undesirable option Loss Aversion Framing Associate a loss with the undesirable option stickk.com How can the undesirable anti-charity behavior result in a loss? Use “loss” language: “If you do not do X, you will lose Y” Biases, Design Patterns, Solutions 38 Thursday, August 26, 2010
- 39. Vividness, Salience Anchoring Availability Vividness, Salience Narrate details as stories Use similar, vivid and Various charity Make stories more popular stories as advertisements emotional, personal examples Make the user recall pleasurable memories Biases, Design Patterns, Solutions 39 Thursday, August 26, 2010
- 40. Scarcity foodspotting.com How can we give users Battery meter to solicit nominations information about relative/comparative input depleting inventory? Limited character count TW character limits for feedback Throttle items that can be Seriosity uploaded Dribbble.com email currency image throttling Biases, Design Patterns, Solutions 40 Thursday, August 26, 2010
- 41. Next Steps Design Patterns Survey of Behavioral Solutions Economics Frameworks Past, Present, Future Psych & Econ Thinking Models Choice Architecture Rationality Frameworks: Applications for non-gaming Heuristics Thaler: NUDGE online environments Biases Cialdini: RSS-CAL New Product Features Prospect Theory Loss/Gain Framework Drive User Engagement Intertemporal Choice Drive User Satisfaction Hyberbolic discounting Survey of Game User Behavior Mechanics Patterns Biases, Design Patterns, Solutions 41 Thursday, August 26, 2010