According to a consolidated tradition of research about the psychology of decisions (Newell et al. 2007) and the psychometric psychology (Sartori 2008), the present study aims at analysing the preferences of individuals between the main numeric expressions of uncertainty: the probabilistic form (expressed by percentages) and the fractional form (expressed by fractions). The purpose is to verify a different management of credit on the basis of a different expression of the representation of risk. The scientific outline refers to the most relevant studies in the field of decision making, which show the demonstrations and the experiments carried out by different authors starting from the investigations by Kahneman and Tversky. These results joined in their most accredited two theories: the Framing Effect and the Cumulative Prospect Theory, an evolution of the Prospect Theory. The following survey is designed to experimentally demonstrate the change in preferences on the basis of a different numeric representation of uncertainty. The study considers a generic sample of 100 individuals who were submitted two questionnaires especially designed. The obtained data were drawn up with statistic means in order to find out common norms in decision-making processes. The results showed the tendency of individuals to assign a different preference on the basis of the numeric representation, probabilistic or fractional. Referring to this feedback, one hypothesis is proposed as well as a new theory linked to the informative context of the options is presented.
Quality & Quantity – Springer Journals
Published: Oct 9, 2010
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera