The Complex Art of Decision-Making
The decision-making process explained by behavioral economics
This blog attempts to synthesize many previous posts (links provided in text) on ground-breaking theories of behavioral economics. It will synthesize those into a single view of the decision-making process influenced by various cognitive forces.
This view may be incomplete or scientifically incorrect. Still, it is intended to give you a sense of the ultimate complexity of what we think happens simply because we're smart.
The formula of decision-making
Decision-making is identifying alternative courses of action, selecting the appropriate one for the particular situation, and considering value-relevant consequences.
This definition provides a simple formula: decision-making = judgment + choice.
The first helps us identify available options, and the second takes on the selection task.
The theory of bounded rationality
Herbert Simon, the father of bounded rationality, said, "Human behavior is intendedly rational but only limitedly so."
We believe in making rational judgments while we're uneven in our cognitive abilities, operate with imperfect information, and are limited in time and resources.
All of that leads us to "satisficing"—selecting not the option with the highest utility (wealth, satisfaction, happiness) but the easiest one to achieve within the task's limitations.
Satisficing and multitasking
So, "satisfice" is a slang word composed of "satisfy" and "suffice."Visualizing it is equally simple—you may strive for maximum utility in the infinity area of a linear graph between an effort and a value.
Usually, we don't reach the horizon and stop somewhere midway, which is that "good enough" spot representing the sufficient value paid off by decent effort.
Here, we almost forgot to account for the mandatory element of today's work—multitasking. We can barely concentrate on a single task and develop to the extremum.
Instead, we conduct multiple jobs simultaneously, linearly dependent on effort.
Here, we almost forgot to account for the mandatory element of today's work—multitasking. We can barely concentrate on a single task and develop to the extremum.
Instead, we conduct multiple jobs simultaneously, linearly dependent on effort.
Furthermore, each individual has a productivity threshold, after which the output deteriorates even further. So, the number of tasks develops linearly, while the time to accomplish those tasks suddenly increases.
That breaking point of no. of tasks vs. time to accomplish could be the "satisficing" point, after which an individual becomes nearly unproductive.
That breaking point of no. of tasks vs. time to accomplish could be the "satisficing" point, after which an individual becomes nearly unproductive.
The graphical representation of the bounded rationality theory may be as simple as the following one.
Indeed, rational decisions providing maximum utility are the actual works of art.
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Allais Paradox
As early as 1952, Maurice Allais objected to the rational choice theory, assuming that we shouldn't consider the rationality of choice but the rationality of the decision-maker.
His experiments proved that people look for the reliability of decisions instead of the maximum utility.
E.g. most of us would choose A and C options in the following scenarios:
Option А: 100% win of 1 mln francs
vs.
Option В: 89% chance to win 1 mln francs, 10% chance to win 5 mln francs, 1% chance of no-win.
Option C: 10% chance to win 5 mln francs, 90% chance of no-win
vs.
Option D: 11% chance to win 1 mln francs, 89% chance of no-win.
In fact, a rational economic actor would've opted for scenarios B and D, where 1% of additional risk would provide an opportunity to win 390,000 francs more.
Prospect theory: our judgments depend on a subjective anchor
Prospect theory went further on Allais' findings and explained specific patterns of our behavior when operating under bounded rationality conditions.
Most importantly, our judgments depend not on the maximum utility but on the marginal one compared to our subjective reference point - an anchor.
The theory of regret
Regret theory assumes that an option's expected utility depends on one's regret when comparing its outcomes to the results of rejected options.
We regret when the outcome of the rejected option would have been better and rejoice when the rejected option would have been worse.
Interestingly, our judgments are influenced by both anticipated regret (the anticipation of regret caused by manipulating expected feedback on future options) and post-decision one (disappointment from comparing the utility of the selected option with unchosen ones).
Post-decision regret influences our decisions by creating experiences that affect our future anticipated regret.
We fear the choice consequences in advance and try to minimize our post-decision regret by making regret-averse choices.
Cognitive dissonance
Cognitive dissonance is related to
- the net desirability of the chosen and unchosen options, and
- the importance of the decision.
Making a decision can cause dissonance, especially if the chosen and unchosen alternates have similar net benefits and if the decision is essential. That can send us into a cycle of rumination, causing regret and anxiety.
Accountability
When we make important decisions, we may experience regret and even anxiety afterward because we are accountable for their outcomes.
Therefore, we prefer readily justifiable decisions in the face of accountability to those with the highest benefits.
Decision-making in the face of conflicting cognitive forces
The following scheme tries to visualize the extreme complexity of decision-making in the face of many conflicting forces.
Assuming how many decisions we make regularly, there must be times when we stand back and reflect on the quality and driving forces of our decisions. Arguably, many of those won't be sufficiently rational.
There's not much glory in being a decision-maker. Instead, it's a challenging and primarily unpleasant job of fighting many demons and planting the course among cognitive traps to the nearest safe haven.
P.S. To increase the complexity even further, you may read about the Nudge Theory.
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