Herbert Simon coined the term satisficing behavior to describe human choice among alternative behaviors recognizing bounded rationality. The information-processing capacity of the human brain cannot examine all possible alternatives and their consequences for human satisfaction. Thus, Simon argued that satisficing was the dominant process, with maximizing playing a lesser role. Consumers, for example, might set an aspiration level and then begin to examine alternative purchases. When the aspiration level is reached, the person is satisfied, the search stops, and the purchase is made. Simon also applied his notion to games: "The players, instead of seeking for a ‘best’ move, need only to look for a ‘good’ move" (Simon 1955, p. 108). The aspiration level is conceived of as being learned in a series of choices. If the aspiration level is set too low, too many alternatives qualify, and perhaps the person is bored. If set too high, no alternatives may qualify, and the level is lowered. This makes preferences endogenous to ongoing experience and feedback rather than fixed as is often assumed in neoclassical economics. The new conception has not become standard among economists, but its use is growing.

Search among alternatives is necessarily selective and simplified by applying rules of thumb (heuristics) whether by a consumer or a business considering the mix of products to produce and methods of production. The interruption of routine is the occasion for examining behavior and goals. The learning involved in the examination of available means may cause goals (ends in view) to be modified. The problem agenda and problem representation are not given in advance but are worked out in the decision process affected by context and events affecting saliency of particular alternatives. This is consistent with a pragmatic view seeing means and ends as interdependent. "If there are goals, they do not so much guide the search as emerge from it" (Simon 1991, p. 367). Simon referred to this process as procedural rationality.

Humans are quite able to rationalize their current behavior. They can find a reason for what they are doing even if it was not in their consciousness before the behavior. The adjustment of aspiration level to the outcome of present behavior is both psychologically healthy and a possible source of disaster as habits can persist long after they are dysfunctional.

Some economists object to the concept of endogenous and evolving preferences because a moving target provides no deterministic standard for defining rationality. It is not easy to distinguish irrationality from learning. A business manager (or voter) may focus on one sub-problem rather than another over time. Saliency is affected by events, framing, context, and emotion. For example, environmental consciousness may result in management finding that former wastes can actually be recycled into profitable products. This would not happen if rationality were unbounded and all profitable alternatives were always being considered. Likewise, a consumer would not be influenced by product placement in the store or by advertising.

Consumers and producers do not have time to examine all possibilities. They collapse their experience into rules of thumb, and new observations cue behavior when the new data is put into a category to which a particular behavior is attached. The human brain can take in data and jump unconsciously to a conclusion and behavior. The fact that the reinforcement of behavior happens unconsciously does not mean that experience is irrelevant. The mind does not waste experience. The ability of the mind to fill in missing data is a strength and weakness. The brain takes in necessarily limited and uncertain data and fills in the rest by itself. This saves us from helpless indecision and at the same time exposes us to disaster when more observation would have led to a different behavior, perhaps affecting our very survival. In the face of very complex computational problems that challenge the capacity of the brain, this jumping to action may be better for profitability and survival than making a mistaken calculation. More data and more calculation are not necessarily better. When the payoff to one firm depends on the choices of other firms and the future is uncertain, the world may be much more predictable if most firms are using the same rules of thumb than if all are calculating their best guesses.

Satisficing is consistent with many observed behaviors, such as simple markup pricing by business (requires less data than profit maximization), lexicographic preferences and choice (requires less data and calculation than utility maximization), and modular budgets. There is experimental evidence that many choices are intransitive. A modular budget allocating one’s income initially to categories of expenditures produces what appears to an outsider as intransitive choices. Choices of goods then are made within these accounts without further reexamina-tion of all feasible alternatives.

Consumers and businesses have multiple objectives, and making them commensurable would take considerable mental energy and calculation. The same could be said for attaching subjective probabilities to all outcomes. It is simpler to regard outcomes simply as likely or unlikely (outcomes the consumer or manager would be surprised by).

Bounded rationality implies decision costs. There are necessary tradeoffs between decision costs and better decisions. It is tempting then to suggest a calculated optimal search rule and conclusion of what is good enough. But such a rule has the same problem as that of the brain’s limitations.

Satisficing, which focuses attention on how managers and consumers actually make decisions, has implications for research. Scholars must get out of their armchairs to conduct field surveys; such research will always be incomplete and messy, but Simon argued that it would still be better than making assumptions. After surveying the literature, John Conlisk concludes in his 1996 article "Why Bounded Rationality?" that "psychology and economics provide wide-ranging evidence that bounded rationality is important" (p. 692). He argues that "models of bounded rationality adhere to a fundamental tenet of economics, respect for scarcity. Human cognition, as a scarce resource, should be treated as such" (p. 692). Satisficing is consistent with both observations. The point is not that optimization be wholly replaced with satisficing, but that human behavior will, as Conlisk notes, "vary by context, depending on such conditions as deliberation cost, complexity, incentives, experience, and market discipline" (p. 692).

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