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020 ▼a 9781085798297
035 ▼a (MiAaPQ)AAI13896654
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 371
1001 ▼a Erez, Yuval.
24510 ▼a Essays on Decision Making and the Role of Hunger in Risky Choice Behavior.
260 ▼a [S.l.]: ▼b Cornell University., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 143 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Includes supplementary digital materials.
500 ▼a Advisor: Blume, Lawrence E.
5021 ▼a Thesis (Ph.D.)--Cornell University, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a Decision making is an integral part of human life. It encompasses different domains (e.g., risky choice, intertemporal choice, etc.), and is affected by numerous factors (visceral factors, emotions, representations, etc.). Following a thorough review of the evolution of decision making as a field of study, this dissertation studies the effect of experimentally manipulated hunger - a typical drive state - on choices in the context of decision making under risk for both food and money. Using a risky-choice framing task, the effect of hunger was tested to assess its influence on: (a) choice consistency ("rational choice behavior") as reflected by the degree of framing bias exhibited by the participants, (b) risk preferences, and (c) sensitivity to midpoint probabilities. Furthermore, a number of theoretical hypotheses were driven from three distinct models - two traditional dual-system models and fuzzy-trace theory - and compared with participants' actual choice behavior. Results from the experiment show that being in a drive state of hunger increased risk aversion for food and money but did not generate a stronger framing bias, or significantly alter the sensitivity to midpoint probabilities. Particularly, this pattern of risk preferences was robust across both gain and loss-framed decisions. In addition, this work provides some evidence for oversensitivity to midpoint probabilities in the context of risky-choice framing task. These findings pose a challenge to the two traditional dual-system models, contradicting some of their formal predictions, while providing some support to fuzzy-trace theory. Future directions for theoretical research are discussed.
590 ▼a School code: 0058.
650 4 ▼a Economics.
650 4 ▼a Psychology.
650 4 ▼a Behavioral psychology.
690 ▼a 0501
690 ▼a 0621
690 ▼a 0384
71020 ▼a Cornell University. ▼b Economics.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0058
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15491738 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK