Using ELECTRE to analyse the behaviour of economic agents
According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing...
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Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2020-09, Vol.24 (18), p.13629-13637 |
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creator | Fattoruso, Gerarda Marcarelli, Gabriella Olivieri, Maria Grazia Squillante, Massimo |
description | According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275,
2009
) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l,
1979
). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents. |
doi_str_mv | 10.1007/s00500-019-04397-2 |
format | Article |
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2009
) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l,
1979
). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents.</description><identifier>ISSN: 1432-7643</identifier><identifier>EISSN: 1433-7479</identifier><identifier>DOI: 10.1007/s00500-019-04397-2</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Alternatives ; Artificial Intelligence ; Axioms ; Computational Intelligence ; Control ; Decision making ; Decision theory ; Economic analysis ; Editing ; Emotional factors ; Engineering ; Expected utility ; Focus ; Mathematical analysis ; Mathematical Logic and Foundations ; Mechatronics ; Multiple criterion ; Optimization ; Preferences ; Probability ; Psychology ; Rationality ; Robotics</subject><ispartof>Soft computing (Berlin, Germany), 2020-09, Vol.24 (18), p.13629-13637</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-c626cfdcadba3c06aa9016756ded8c4458a13fcf57c81a1bd937993853ac57e33</citedby><cites>FETCH-LOGICAL-c362t-c626cfdcadba3c06aa9016756ded8c4458a13fcf57c81a1bd937993853ac57e33</cites><orcidid>0000-0003-4085-4484</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00500-019-04397-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2917979484?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21387,27923,27924,33743,41487,42556,43804,51318,64384,64388,72340</link.rule.ids></links><search><creatorcontrib>Fattoruso, Gerarda</creatorcontrib><creatorcontrib>Marcarelli, Gabriella</creatorcontrib><creatorcontrib>Olivieri, Maria Grazia</creatorcontrib><creatorcontrib>Squillante, Massimo</creatorcontrib><title>Using ELECTRE to analyse the behaviour of economic agents</title><title>Soft computing (Berlin, Germany)</title><addtitle>Soft Comput</addtitle><description>According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275,
2009
) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l,
1979
). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. 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Marcarelli, Gabriella ; Olivieri, Maria Grazia ; Squillante, Massimo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-c626cfdcadba3c06aa9016756ded8c4458a13fcf57c81a1bd937993853ac57e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Alternatives</topic><topic>Artificial Intelligence</topic><topic>Axioms</topic><topic>Computational Intelligence</topic><topic>Control</topic><topic>Decision making</topic><topic>Decision theory</topic><topic>Economic analysis</topic><topic>Editing</topic><topic>Emotional factors</topic><topic>Engineering</topic><topic>Expected utility</topic><topic>Focus</topic><topic>Mathematical analysis</topic><topic>Mathematical Logic and Foundations</topic><topic>Mechatronics</topic><topic>Multiple criterion</topic><topic>Optimization</topic><topic>Preferences</topic><topic>Probability</topic><topic>Psychology</topic><topic>Rationality</topic><topic>Robotics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fattoruso, Gerarda</creatorcontrib><creatorcontrib>Marcarelli, Gabriella</creatorcontrib><creatorcontrib>Olivieri, Maria Grazia</creatorcontrib><creatorcontrib>Squillante, Massimo</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Soft computing (Berlin, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fattoruso, Gerarda</au><au>Marcarelli, Gabriella</au><au>Olivieri, Maria Grazia</au><au>Squillante, Massimo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using ELECTRE to analyse the behaviour of economic agents</atitle><jtitle>Soft computing (Berlin, Germany)</jtitle><stitle>Soft Comput</stitle><date>2020-09-01</date><risdate>2020</risdate><volume>24</volume><issue>18</issue><spage>13629</spage><epage>13637</epage><pages>13629-13637</pages><issn>1432-7643</issn><eissn>1433-7479</eissn><abstract>According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275,
2009
) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l,
1979
). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00500-019-04397-2</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-4085-4484</orcidid></addata></record> |
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subjects | Alternatives Artificial Intelligence Axioms Computational Intelligence Control Decision making Decision theory Economic analysis Editing Emotional factors Engineering Expected utility Focus Mathematical analysis Mathematical Logic and Foundations Mechatronics Multiple criterion Optimization Preferences Probability Psychology Rationality Robotics |
title | Using ELECTRE to analyse the behaviour of economic agents |
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