Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

Suffering a Loss Is Good Fortune: Myth or Reality?

Cui-Xia Zhao | Si-Chu Shen | Li-Lin Rao | Rui Zheng | Huan Liu | Shu Li
Journal of behavioral decision making | 2018

We sometimes decide to take an offered option that results in apparent loss (e.g., unpaid overtime). Mainstream decision theory does not predict or explain this as a choice we want to make, whereas such a choice has long been described and highly regarded by the traditional Chinese dogma "" (suffering a loss is good fortune). To explore what makes the dogma work, we developed a celebrity anecdote-based scale to measure "Chikui" (suffering a loss) likelihood and found that:(i) people with higher scores on the Chikui Likelihood Scale (CLS) were more likely to report higher scores on subjective well-being and the Socioeconomic Index for the present and (ii) the current Socioeconomic Index could be positively predicted not only by current CLS scores but also by retrospective CLS scores recalled for the past, and the predictive effect was enhanced with increasing time intervals. Our findings suggest that "suffering a loss is good fortune" is not a myth but a certain reality.

Pubmed ID: 30008514

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


AMOS (tool)

RRID:SCR_013067

A collection of tools and class interfaces for the assembly of DNA reads.

View all literature mentions