Bestiary of Behavioral Economics/Satisficing

From Wikibooks, open books for an open world
Jump to: navigation, search


In the 1950s, decision theorists were beginning to face difficulties in applying the ambiguous rationality postulate to more complicated decision problems. In response, Herbert Simon developed the notion of “bounded rationality.” Bounded rationality, as Simon describes, demonstrates the limit of rationality due to lack of information, intellectual ability, and definite amounts of time. He developed this notion from the fusion of substantive rationality (decisions made due to “total preference ordering” and the principal of individual rationality) and procedural rationality (decisions made by following a specific set of rules or procedures).[1]

With the background of bounded rationality, the term “satisficing” was developed as an alternative to optimization. Simon describes the need for satisficing:

“Because real-world optimization, with or without computers, is impossible, the real economic actor is in fact a satisficer, a person who accepts ‘good enough’ alternatives, not because less is preferred to more, but because there is no choice.” [2]

Simon believed that the goal of optimization (or maximizing) was virtually always unachievable in real life.[3] The term “satisficing” was created by Simon in 1956 to describe this theory of choice that determined the role of alternatives in decision making.[2] Simon ultimately believed that satisficing was a more accurate depiction of choice theory maximization.[3]


Investopedia describes satisficing as a “decision-making strategy that aims for a satisfactory or adequate result, rather than the optimal solution. This is because aiming for the optimal solution may necessitate needless expenditure of time, energy and resources.”[4]


In order to satisfice, people “need only to be able to place goods on some scale in terms of the degree of satisfaction they will afford, and to have a threshold of acceptability.”[3] A satisficer continually subjects his or her judgment on a variety of goods until one comes across that exceeds the “acceptability threshold,” and the good is then chosen. Because the satisficer is constantly evaluating new goods, he or she may find a second good that achieves a higher utility than the first; and in response, the satisficer replaces the latter for the former. Therefore, the satisficer always strives to achieve maximization without it ever being the explicit goal, nor ever being able to truly achieve maximization.[3]

Therefore, satisficing, in many instances, can be translated to mean “an approximation to being best,” or more commonly, “good enough.”[2] Because full optimization is virtually impossible in the real world, consumers are left to find choices that are good enough to fulfill their needs.


The satisficing theory pertains to many applications in a variety of fields aside from economics--including, but not being limited to, artificial intelligence and sociology.[4] Currently, a lot of research is being dedicated to the “design and implementation of artificial social systems.”[2] In the modern world--where computers are constantly evolving to become more efficient, precise, and effective--it is inevitable that artificial systems will increasingly function analogously to humans.[2] Computers will continually undertake the tasks that human workers execute as even complex computer labor becomes cheaper and more readily available.

One of the most common outlets of artificial intelligence (i.e. computers and other technology) for civilian consumers is security. Many corporations and organizations are increasingly deciding to use technology as a substitute for hiring people for quality security measures. Human workers may ultimately be more capable of accomplishing the task at hand, but humans must be continually paid and take breaks; whereas, computers are purchased once and can work twenty four hours a day. Therefore, the organization may choose to satisfice: when confronted with a variety of choices to fill a need, the organization decides to buy a computer system instead of hiring employees.[4] Although the computer may not be completely equipped to handle the most difficult situation, the consumer decides that the computer is “good enough” for the money that is required to purchase it. Although there is a trade-off in purchasing the full amount for the computer system at one time verses continually paying employees, the consumer may decide that the trade-off is worth it.

Example: The owner of a casino needs to achieve the task of obtaining adequate facial recognition software for surveillance to detect any unusual :behavior exhibited by gamblers. The owner has multiple options, of which include buying a computer system that constantly surveys the casino, or :hiring a team of people to survey the various cameras throughout the casino. Hiring a team of human workers for surveillance takes time and :resources, while buying a computer system to work in conjunction with an already established security technology is faster and cheaper. Instead :of taking the time, energy, and money to interview a variety of potential candidates, the owner decides to buy the computer software to expedite :the process. The owner may acknowledge that the technology has its limits in comparison to those employees that would be able to think for :themselves with ingenuity, but the owner decides to satisfice and choose the computer software to get the job done.


  1. Radner, Roy. "Satisficing." Journal of Mathematical Economics. 2. (1975): 253-262. Web. 6 May. 2012. <>. Max vs. Satisficing
  2. a b c d e Stirling, Wynn. Satisficing Games and Decision Making: With Applications to Engineering and Computer Science. 1. Cambridge: The Press Syndicate of the University of Cambridge, 2003. 1-28. Web. <>.
  3. a b c d Schwartz, Barry, Andrew Ward, et al. "Maximizing Versus Satisficing: Happiness Is a Matter of Choice." Journal of Personality and Social Psychology. 83.5 (2002): 1178-1197. Web. 6 May. 2012. <$FILE/schwartz et al. 2002 jpsp.pdf>.
  4. a b c "Satisficing Definition." Investopedia. N.p., 2012. Web. 6 May 2012. <