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西蒙满意度模型

  	      	      	    	    	      	    

西蒙满意度模型(Satisficing Model)也称满意度法则(Satisficing Principle)

目录

西蒙满意度模型简介

  满意度模型(Satisficing Model)是指人们做实际决策时,是以满意度最高的方案为准。

  满意度模型是赫伯特·西蒙的思想。在考察了理性决策、追求最大化和最优化的决策模式后,西蒙提出,由于人的观念、智慧、认知力、知识、技能、精力、时间等等是有限的,所以人们不可能总是把所有的问题都考虑到,找到最佳的目标和最佳的方法,追求极大化;甚至,连最优化的可能都没有。有人认为可以是在特定条件下的最优,实际上,由于信息、认知、机遇、思考能力、未知的变化、甚至一念之差,他并不知道是不是当时的最优,其选择也不可能是已有条件下的最优。他可能对自己的偏好曲线都不知道,决策的依据是他当时的满意度。只要对决策的目标和执行的手段基本满意,他们就会做出决定,开始行动。后来的学者科亨和赛亚特,研究了许多公司的决策过程, 用经验性的数据证实了这个模式的存在。[1]从这一模式中引申出来的结论是,除了能力之外,决策者的见识、期望值在决策的过程中能起到十分重要的作用。

Satisficing (a portmanteau of "satisfy" and "suffice") is a decision-making strategy which attempts to meet criteria for adequacy, rather than to identify an optimal solution. A satisficing strategy may often be (near) optimal if the costs of the decision-making process itself, such as the cost of obtaining complete information, are considered in the outcome calculus.

The word satisfice was coined by Herbert Simon. He pointed out that human beings lack the cognitive resources to maximize: we usually do not know the relevant probabilities of outcomes, we can rarely evaluate all outcomes with sufficient precision, and our memories are weak and unreliable. A more realistic approach to rationality takes into account these limitations: This is called bounded rationality.

Some consequentialist theories in moral philosophy use the concept of satisficing in the same sense, though most call for optimization instead.

Cybernetics and artificial intelligence

In cybernetics, satisficing is optimization where all costs, including the cost of the optimization calculations themselves and the cost of getting information for use in those calculations, are considered.

As a result, the eventual choice is usually sub-optimal as regards the main goal of the optimization, i.e. different from the optimum in the case that the costs of choosing are not taken into account.

During a 1997 game against Deep Blue, Garry Kasparov, after being defeated in a game where his computer opponent adopted a satisficing position,Template:Fact remarked that the computer was "playing like a human." Kasparov later explained that, when playing computers, chess masters could often defeat them by predicting the most "rational" move; however, satisficing made such prediction unreliable.

Reference: Klaus Krippendorff's "A Dictionary of Cybernetics".

Decision making

In decision making, satisficing explains the tendency to select the first option that meets a given need or select the option that seems to address most needs rather than the “optimal” solution.

Example: A task is to sew a patch onto a pair of jeans. The best needle to do the threading is a 4 inch long needle with a 3 millimeter eye. This needle is hidden in a haystack along with 1000 other needles varying in size from 1 inch to 6 inches. Satisficing claims that the first needle that can sew on the patch is the one that should be used. Spending time searching for that one specific needle in the haystack is a waste of energy and resources.

Simon, as a further example, once explained satisficing to his students by describing a mouse searching for cheese in a maze. The mouse might begin searching for a piece of Gouda, but unable to find any would eventually be "satisfied" and could "suffice" with any piece of cheese, such as cheddar.

Satisficing occurs in consensus building when the group looks towards a solution everyone can agree on even if it may not be the best.

Example: A group spends hours projecting the next fiscal year's budget. After hours of debating they eventually reach a consensus only to have one person speak up and ask if the projections are correct. When the group becomes upset at the question, it is not because this person is wrong to ask, but rather because they have come up with a solution that works. The projection may not be what will actually come, but the majority agrees on one number and thus the projection is good enough to close the book on the budget.

In many circumstances, the individual may be uncertain about what constitutes a satisfactory outcome. For example, an individual who only seeks a satisfactory retirement income may not know what level of wealth is required—given uncertainty about future prices—to ensure a satisfactory income. In this case, the individual can only evaluate outcomes on the basis of their probability of being satisfactory.

If the individual chooses that outcome which has the maximum chance of being satisfactory, then this individual's behavior is theoretically indistinguishable from that of an optimizing individual under certain conditions (Castagnoli and LiCalzi, 1996; Bordley and LiCalzi, 2000; Bordley and Kirkwood, 2004).

Economics

In economics, satisficing is a behavior which attempts to achieve at least some minimum level of a particular variable, but which does not necessarily maximize its value. The most common application of the concept in economics is in the behavioural theory of the firm, which, unlike traditional accounts, postulates that producers treat profit not as a goal to be maximized, but as a constraint. Under these theories, a critical level of profit must be achieved by firms; thereafter, priority is attached to the attainment of other goals.

Survey Taking

As an example of satisficing, in the field of social cognition, Jon Krosnick proposed a theory of statistical survey satisficing which says that optimal question answering by a survey respondent involves a great deal of cognitive work and that some people would use satisficing to reduce that burden. Some people may shortcut their cognitive processes in two ways:

  • Weak satisficing: Respondent executes all cognitive steps involved in optimizing, but less completely and with bias.
  • Strong satisficing: Respondent offers responses that will seem reasonable to the interviewer without any memory search or information integration.

Likelihood to satisfice is linked to respondent ability, respondent motivation and task difficulty

Regarding survey answers, satisficing manifests in:

  • choosing explicitly offered no-opinion response option
  • choosing socially desirable responses
  • non-differentiation when a battery of questions asks for ratings of multiple objects on the same response scale
  • acquiescence response bias, which is the tendency to agree with any assertion, regardless of its content

References

  • Bordley, R. and M. LiCalzi (2000). "Target-Oriented Utility." Decisions in Economics & Finance.
  • Bordley, R. and C. Kirkwood (2004). "Preference Analysis with Multiattribute Performance Targets." Operations Research.
  • Byron, M. (ed.). Satisficing and Maximizing: Moral Theorists on Practical Reason. Cambridge University Press, 2004.
  • Castagnoli, E. and M. LiCalzi, 1996. "Expected Utility without Utility." Theory and Decision
  • Holbrook, A.; Green, M.; Krosnick, J. 2003. "Telephone versus face-to-face interviewing of national probability samples with long questionnaires - comparison of respondent satisficing and social desirability response bias." Public Opinion Quarterly, Vol 67, 79-125.
  • Krippendorff, Klaus. "A Dictionary of Cybernetics."
  • Krosnick, J. (1991). "Response strategies for coping with the cognitive demands of attitude measures in surveys." Applied Cognitive Psychology. Vol 5, 213-36.
  • Simon, H. A. (1957). Models of man: Social and rational. New York: Wiley
  • Simon, H. A. (1978). Rationality as a process and product of thought. American Economic Review, 68, 1-16
  • Simon, H. A. (1983). Reason in human affairs. Stanford: Stanford University Press

See also

External links

参考文献

  1. Cohen, K. J., & Cyert, R. M.. Theory of the firm : Resource allocation in a market economy[M] (2d ed.). Englewood Cliffs, N.J.: Prentice- Hall. 1975.