Satisficing choice procedures

Papi, Mauro

doi:10.1016/j.jebo.2012.04.017

Cited by 30 publications

(16 citation statements)

References 15 publications

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“…Another approach to form a consideration set can be seen in a satisficing procedure (Simon (1959) and more related Tyson (2008Tyson ( , 2013, Papi (2012), Manzini et al (2013a)). …”

Section: The Impact Of Data and Experience On The Formation Of A Probmentioning

confidence: 99%

Limited Attention in Case-Based Belief Formations

Bleile

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract An agent wants to derive her belief over outcomes based on past observations collected in her database (memory). There is well establish evidence in the psychology and marketing literature that agents consistently fail (or choose not) to process all available information. An agent might be constraint to pay attention (recall) and consider only parts of her potentially available information due to unawareness, cognitive or psychological limitations or intentionally for effort-efficiency. Based on this insight, we axiomatize a two-stage belief formation process in which in a first step agents filter ((un)intentionally) the available information. In a second step individuals employ the remaining observations to express a belief. We impose cognitively and normatively desirable properties on the filtering process. The axioms on the belief formation stage describe the relationship between databases and their induced beliefs. The axiomatized belief induced by a filtered databases is representable by a similarity weighted average of the estimations induced by each past attentiongrabbing observation. An appealing application is a satisficing filter that induces a filtered belief that relies only on past experiences that are sufficiently relevant for a current problem. For the specific situation that agents (are able to) always pay attention to all available information, our axiomatization coincides with the axiomatization of a belief formation in Billot et al. (Econometrica (2005)). Terms of use: Documents in

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“…Another approach to form a consideration set can be seen in a satisficing procedure (Simon (1959) and more related Tyson (2008Tyson ( , 2013, Papi (2012), Manzini et al (2013a)). …”

Section: The Impact Of Data and Experience On The Formation Of A Probmentioning

confidence: 99%

Limited Attention in Case-Based Belief Formations

Bleile

2014

SSRN Journal

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“…It is worth noting at this point that satisficing behavior is not necessarily sub-optimal, and in fact utility maximization (optimization) is a special case of satisficing (Tyson, 2008;Papi, 2012). Let us consider an individual facing a choice between different products in a store.…”

Section: Introductionmentioning

confidence: 99%

“…Another stream of research has focused on deriving axioms and provide axiomatic perspectives of the satisficing heuristic (Tyson, 2008;Papi, 2012). These researchers attempt to derive "optimal" stopping rules under incomplete information search when the search order is fully or partially observed.…”

Section: Introductionmentioning

confidence: 99%

Accommodating satisficing behaviour in stated choice experiments

Sandorf

Campbell

2018

European Review of Agricultural Economics

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Accumulating evidence suggests that respondents in stated choice experiments use simplifying strategies. Such behavior is a deviation from random utility theory and can lead to wrong inferences regarding preferences. This is a first attempt to systematically explore satisficing in stated choice experiments. We consider 944 satisficing rules and allow respondents to revise the rules adopted throughout the choice sequence. Only a minority of respondents used the same satisficing rule across the entire sequence. Allowing for updating reveals that the use of the heuristic changes over the choice sequence. Considering satisficing behavior leads to improved model fits and different marginal willingness-to-pay estimates.

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“…Prominent amongst these latter weaker theories are theories of incomplete preferences (Ok et al 2012;Nau 2006;Mandler 2005;Dubra et al 2004); theories of behaviour under ambiguity (Etner et al 2012;Gajdos et al 2008;Ghirardato et al 2004;Hayashi and Wada 2010;Klibanoff et al 2005;Schmeidler 1989;Siniscalchi 2009); theories of rational inattention (Sims 2003;Manzini and Mariotti 2014;Matejka and McKay 2015;Caplin and Dean 2015); and search theories (Masatlioglu and Nakajima 2013;McCall 1970;Morgan and Manning 1985;Stigler 1961). A useful survey of satisficing choice procedures can be found in Papi (2012).…”

Section: Introductionmentioning

confidence: 99%

When and how to satisfice: an experimental investigation

2017

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This paper is about satisficing behaviour. Rather tautologically, this is when decision-makers are satisfied with achieving some objective, rather than in obtaining the best outcome. The term was coined by Simon (Q J Econ 69: [99][100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116][117][118] 1955), and has stimulated many discussions and theories. Prominent amongst these theories are models of incomplete preferences, models of behaviour under ambiguity, theories of rational inattention, and search theories. Most of these, however, seem to lack an answer to at least one of two key questions: when should the decision-maker (DM) satisfice; and how should the DM satisfice. In a sense, search models answer the latter question (in that the theory tells the DM when to stop searching), but not the former; moreover, usually the question as to whether any search at all is justified is left to a footnote. A recent paper by Manski (Theory Decis. doi:10.1007/s11238-017-9592-1, 2017) fills the gaps in the literature and answers the questions: when and how to satisfice? He achieves this by setting the decision problem in an ambiguous situation (so that probabilities do not exist, and many preference functionals can therefore not We would like to thank an anonymous referee for very helpful comments on an earlier version of this paper. Electronic supplementary materialThe online version of this article (doi:10.1007/s11238-017-9600-5) contains supplementary material, which is available to authorized users. be applied) and by using the Minimax Regret criterion as the preference functional. The results are simple and intuitive. This paper reports on an experimental test of his theory. The results show that some of his propositions (those relating to the 'how') appear to be empirically valid while others (those relating to the 'when') are less so.

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Satisficing choice procedures

Cited by 30 publications

References 15 publications

Limited Attention in Case-Based Belief Formations

Limited Attention in Case-Based Belief Formations

Accommodating satisficing behaviour in stated choice experiments

When and how to satisfice: an experimental investigation

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