Editing Satisficing (section)

=== Heuristic Satisficing ===
Heuristic satisficing refers to the use of aspiration levels when choosing from different paths of action. By this account, decision-makers select the first option that meets a given need or select the option that seems to address most needs rather than the "optimal" solution. The basic model of aspiration-level adaptation is as follows: <ref>{{Cite book |last=Reb |first=Jochen |url=http://dx.doi.org/10.7551/mitpress/14939.001.0001 |title=Smart Management |last2=Luan |first2=Shenghua |last3=Gigerenzer |first3=Gerd |date=2024-05-14 |publisher=The MIT Press |isbn=978-0-262-37857-4}}</ref>

Step 1: Set an aspiration level α.

Step 2: Choose the first option that meets or exceeds α.

Step 3: If no option has satisfied α after time β, then change α by an amount γ and continue until a satisfying option is found.<blockquote>Example: Consider pricing commodities. An analysis of 628 used car dealers showed that 97% relied on a form of satisficing.<ref>{{Cite journal |last=Artinger |first=Florian M |last2=Gigerenzer |first2=Gerd |date=2024-07-23 |title=How heuristic pricing shapes the aggregate market: the “Cheap Twin Paradox” |url=https://academic.oup.com/icc/advance-article/doi/10.1093/icc/dtae025/7718687 |journal=Industrial and Corporate Change |language=en |doi=10.1093/icc/dtae025 |issn=0960-6491|doi-access=free }}</ref> Most set the initial price α in the middle of the price range of comparable cars and lowered the price if the car was not sold after 24 days (β) by about 3% (γ). A minority (19%), mostly smaller dealerships, set a low initial price and kept it unchanged (no Step 3). The car dealers adapted the parameters to their business environment. For instance, they decreased the waiting time β by about 3% for each additional competitor in the area.</blockquote>Note that aspiration-level adaptation is a process model of actual behavior rather than an as-if optimization model, and accordingly requires an analysis of how people actually make decisions. It allows for predicting surprising effects such as the "cheap twin paradox", where two similar cars have substantially different price tags in the same dealership.[4] The reason is that one car entered the dealership earlier and had at least one change in price at the time the second car arrived. 
:Example: A task is to sew a patch onto a pair of blue pants. The best needle to do the threading is a 4-cm-long needle with a 3-millimeter eye. This needle is hidden in a haystack along with 1,000 other needles varying in size from 1 cm to 6 cm. 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.

A crucial determinant of a satisficing decision strategy concerns the construction of the aspiration level. In many circumstances, the individual may be uncertain about the aspiration level.

: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.<ref>{{cite journal |last1=Castagnoli |first1=E. |first2=M. |last2=LiCalzi |year=1996 |title=Expected Utility without Utility |journal=Theory and Decision |volume=41 |issue=3 |pages=281–301 |doi=10.1007/BF00136129 |hdl=10278/4143 |s2cid=154464803 |url=https://iris.unive.it/bitstream/10278/4143/1/LiCalzi-96-ExpectedUtilityWithoutUtility.pdf |hdl-access=free }}</ref><ref>{{cite journal |last1=Bordley |first1=R. |first2=M. |last2=LiCalzi |year=2000 |title=Decision Analysis Using Targets Instead of Utility Functions |journal=Decisions in Economics & Finance |volume=23 |issue=1 |pages=53–74 |doi=10.1007/s102030050005 |hdl=10278/3610 |s2cid=11162758 |hdl-access=free }}</ref><ref>{{cite journal |last1=Bordley |first1=R. |first2=C. |last2=Kirkwood |year=2004 |title=Preference Analysis with Multiattribute Performance Targets |journal=Operations Research |volume=52 |issue=6 |pages=823–835 |doi=10.1287/opre.1030.0093 }}</ref>

Another key issue concerns an evaluation of satisficing strategies. Although often regarded as an inferior decision strategy, specific satisficing [[Heuristic|strategies]] for inference have been shown to be [[Ecological rationality|ecologically rational]], that is in particular decision environments, they can outperform alternative decision strategies.<ref>{{Cite journal|title = Reasoning the fast and frugal way: Models of bounded rationality.|journal = Psychological Review|pages = 650–669|volume = 103|issue = 4|doi = 10.1037/0033-295x.103.4.650|first1 = Gerd|last1 = Gigerenzer|first2 = Daniel G.|last2 = Goldstein|pmid=8888650|date=October 1996|citeseerx = 10.1.1.174.4404}}</ref>

Satisficing also 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 the group has already 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.