Save Money, Close Deals, Clip Coupons: the Science of Decision Making
Decisions are all around us, from what to wear in the morning, to purchasing the new model of your favorite phone, to making million dollar investment deals. It’s a massively important area in our lives, and so knowing how people make decisions can be an asset for business and consumers alike. This brief article will give you an understanding of an underlying theory to human decision making, discovered by psychology and applied to a multitude domains.
When finished, your eyes will be opened to a world of human bias: you’ll know why you clip coupons for burgers but not cars, care more about losing than winning, and how a simple rephrasing of text can increase actions upwards of 20% in some cases.
Rational vs Irrational
So let’s dig in. It’s probably no surprise to anyone that humans are irrational at times, far from raw calculating machines that we might like to be. When faced with a decision, we use prior choices, heuristics, and mental shortcuts to perform most of our decision making. Sometimes this is beneficial, in saving time or energy, and may even be the only option that we have, when all the information needed for a decision can’t be known or is too vast to understand. However — as we may know all too well — reaping benefits from unsound decisions may not always be the case.
There is a difference between between what may be best for us and what we actually do, rational vs irrational behavior. This difference plays a major role in modern decision theory and economics alike, and introduces a perfect opportunity for psychological and cognitive sciences to fill in the gaps of where we may fall short and even why we do. Most notably, is the contribution of the subjective, or how we perceive, a choice, value, opinion, ect., internally, biased by our own cognition. This allowed decision theory to move past the prior paradigm of looking only at how we should make decisions, but to also inquire about how humans actually make decisions.
This is where Prospect Theory comes into play. Put forward by two psychologists during the 1970’s, Amos Tversky and Daniel Kahneman, the later of which you may have heard of from his bestselling book, Thinking Fast and Slow, the theory sheds light on a structure in a vast sea of human irrationality. Currently one of the most studied and successful findings of its class, its pervasiveness in a multitude of domains ultimately earned it the 2002 Nobel Prize in economics. The theory also serves as a major early case of the impact that psychological science can have on industry, bringing academic theory to individual decisions, later revolutionizing business, economics, and psychology alike. Moreover, it’s relatively simple, packaged in two parts, each tackling separate components of our subjective decision making: value and likelihood.
Value
The value function concerns itself with just that, value. For example, when haggling a price for a new car at a dealership, people will tend to negotiate on the order of thousands of dollars, unconcerned with trying to save every cent possible. In contrast to this, people will go out of their way to clip coupons that will only save them a dollar on a cheeseburger at their restaurant of choice. This means that we tend to care less about lesser savings on larger purchases as opposed to larger savings on smaller purchases, even though the total amount that we could save would be exactly the same in each of the cases: a dollar is a dollar as some would say.
This is an example of the subjective decision making at work, particularly perceived value, which differs from the actual value, the total that is actually saved. In this case, a dollar for the burger and a dollar for the car would both be saved, the actual value, however, given the steep price of the car, the dollar does not seem like much, even though it does when it is compared to a $7 Cheeseburger.
The value function, the S shaped curve plotted on the graph, captures the value that people perceive. You’ll notice that this differs from the straight line of the actual value by curving away from the actual value line. The willingness of people to haggle for a dollar on smaller purchases rather than larger ones is captured in the top right quadrant of the graph by the perceived value curve deviating from the actual value for larger but not smaller purchases.
Losses; Gains
The perceived value function also captures the difference in people’s perceptions of losses and gains. Notice that the gain portion of the function (top right) is less steep than the loss portion (bottom left). This captures the finding that people subjectively overvalue losses but undervalue gains, otherwise known as loss aversion. In other words, the pain of a loss hurts more and the pleasure of a reward.
Prospect theory actually grants us the ability to put numbers behind the subjective value that people perceive. The subjective pain of losing $10,000 dollars feels worse than the subjective joy of gaining $10,000 feels good. Using the theory, we find that losing $10,000 would actually feel like losing $7,450.45 and gaining $10,000 to feel as if you only gained $3,311.31. This is a large distinction, where in this case, losing the money will feel more than twice as bad than if you gained it! Even though the actual value lost or gained is exactly the same, subjectively we feel there is more value to a loss than to a gain. Remember: good things satiate, bad things escalate.
Take a second to let that sink in. Loss aversion has widespread effects on people’s decisions, and is used extensively in business and marketing practices. For example, the principle underlies why trial periods are so effective, as the feeling of sending back a product will feel as if you are losing something that you already own. A 2004 study showed that consumers subscribing to insurance services are twice as likely to switch from a subscription with a price increase, rather than price decreases from other companies, as the increased loss of money hurts more than the apparent chance to save money (Dawes ‘04).
…and Frames
The most extreme example of loss aversion however, is the framing effect. Picture that you’re recently promoted as a top executive in a major corporation and have been tasked with a 600 employee plant that recently hit a rough patch with its net revenue. To help save the company, you need to make a decision over a new budgeting strategy with the main line item being employee layoffs at the plant. To stay in good standing with shareholders, you need to keep as many employees as possible. You’ve had a finance team work on it and they have presented you with two options:
Plan A: Ensures that 200 employees will be saved.
Plan B: A 1/3 chance that all of them will be saved, and 2/3 chance that none of them will be saved.
Which do you choose, A or B? Now remember your choice for a bit. You document your decision, sign it, and send it off for implementation. What you don’t know, is that the finance team had two other plans, C and D that they meant to send instead of the first two. Had they of sent these, which would you have chosen instead:
Plan C: After implementation, 400 employees will be terminated.
Plan D: 1/3 chance that no one will be terminated, and 2/3 chance that all 600 will be terminated.
Of these two new options, which would you choose? Remember this choice as well. Again, you document your decision, sign it, and send it off for implementation. What happens to the employees, however, might not depend on your decision at all. More importantly, it turns out, are which of the two sets of plans, A & B or C & D, were sent to you.
Not that the two sets are any different, if you run the numbers, (using probability theory), both plan A & C are exactly the same, being the more conservative option without any risk, as well as both B & D, a riskier option with the potential to save more employees than the conservative option, but with a chance of losing more as well. Despite each set of two questions being identical in outcome, you, and most people for that matter, will tend to choose different plans; that is, you’ll choose the conservative case A in the first set, and the riskier plan B in the second one. Thus, people are risk seeking when the decision is framed as a loss, but risk averse when it is framed as a gain.
The framing effect is everywhere, off skewing people’s decision making abilities, from political speech to marketing campaigns (Camerer ‘01). For example, viewing your stock reports between how much they profited vs how much they lost could bias your investment decisions. Advertisers can frame how much money you’ll save with a product vs how much you’ll lose. Politicians or news media may even take an opponent’s accomplishments, and frame them as a shortcoming. Even economists themselves sometimes unsuspectingly fall for it. When looking at the 2006 Economic Science Association registrations, 67% of graduate students registered early when it was framed as a discount, but 93% participants registered early when a penalty fee for late registration was emphasized (Gächter ‘09) (There is hope though, as this effect was not present in the more senior economists).
Conclusion
This essay has only grazed the surface of the breadth and depth of Prospect Theory and the psychological underpinnings of behavioral economics and business. In truth, the value function, loss aversion, and the framing effect far more reaching and all of them mix well with many other findings and predictions made from multiple fields; a hallmark of a Nobel winning theory. To me however, a more notable point of the theory is not its academic qualities, but its remarkable applicability to daily life. We will all have decisions to make, and when we have to make them, in business or otherwise, it pays dividends to know how the machinery behind the decision.
Knowing a bit of psychology can help you reread a document and help you check if it could be framed in a more positive or negative way, can help you save money where you might not think to save it, and prevent you from staying in your bad decision making habits. I challenge you to be on the lookout out for your own examples. And, if you’re applying for a job, make sure you convey what they’ll lose if they don’t hire you, rather than exclusively what they’ll gain. (But just don’t be cocky about it)
Future articles will explore the second part of prospect theory, the effect of likelihood on decisions, as well as introduce the neuroscience behind all of these findings. Be sure not to miss out!
Take home points
- Prospect theory describes people’s subjective decision making
- You’ll fight for saving a dollar on a small purchase, but not a large one
- Subjectively, the pain of a loss outweighs the joy of a gain
- Be careful with how decisions are framed
References
Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American psychologist, 39(4), 341.
Gächter, S., Orzen, H., Renner, E., & Starmer, C. (2009). Are experimental economists prone to framing effects? A natural field experiment. Journal of Economic Behavior & Organization, 70(3), 443–446.
Camerer, Colin F. (2001) Prospect Theory In The Wild: Evidence From The Field. In: Choices, Values, and Frames. Contemporary Psychology. №47. American Psychological Association , Washington, DC, pp. 288–300
Dawes, J. (2004). “Price Changes and Defection Levels in a Subscription-type Market: Can an Estimation Model Really Predict Defection Levels?”. Journal of Services Marketing. 18 (1): 35–44. doi:10.1108/08876040410520690.
Code: I’m currently compiling a library of code to explore the mathematics behind the theory. Check back for updates or email me if you’re interested!
