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On decision making without likelihood judgment [An article from: Organizational Behavior and Human Decision Processes]
Book Details
Author(s)Y. Rottenstreich, R. Kivetz
PublisherElsevier
ISBN / ASINB000PAUDHU
ISBN-13978B000PAUDH2
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Organizational Behavior and Human Decision Processes, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Subjective expected utility, prospect theory and most other formal models of decision making under uncertainty are probabilistic: they assume that in making choices people judge the likelihood of relevant uncertainties. Clearly, in many situations people do indeed judge likelihood. However, we present studies suggesting that there are also many situations in which people do not judge likelihood and instead base their decisions on intuitively generated, non-probabilistic rules or rationales. Thus, we argue that real-world situations are of two types. In situations eliciting a probabilistic mindset, people rely on judgments of likelihood. In situations eliciting a non-probabilistic mindset, they neglect judgments of likelihood. We suggest three factors that may influence the tendency towards either probabilistic or non-probabilistic mindsets. We also outline how extant probabilistic theories may be complemented by non-probabilistic models.
Description:
Subjective expected utility, prospect theory and most other formal models of decision making under uncertainty are probabilistic: they assume that in making choices people judge the likelihood of relevant uncertainties. Clearly, in many situations people do indeed judge likelihood. However, we present studies suggesting that there are also many situations in which people do not judge likelihood and instead base their decisions on intuitively generated, non-probabilistic rules or rationales. Thus, we argue that real-world situations are of two types. In situations eliciting a probabilistic mindset, people rely on judgments of likelihood. In situations eliciting a non-probabilistic mindset, they neglect judgments of likelihood. We suggest three factors that may influence the tendency towards either probabilistic or non-probabilistic mindsets. We also outline how extant probabilistic theories may be complemented by non-probabilistic models.
