Formulating an emergency plan based on expectation-maximization is one thing, but applying it to a single case is another

Hong-Yue Sun, Li-Lin Rao, Kun Zhou and Shu Li

Journal of Risk Research, 2014, vol. 17, issue 7, 785-814

Abstract: This research extends the exploration of single-play/multiple-play distinctions from monetary gambling paradigm to emergency management situation. We conducted three studies (two survey studies and one eye tracking study) to test whether an emergency plan we formulated in advance based on expectation-maximization would be likely to be applied in a single case. In the first two survey studies we found that the plan with the higher EV was more likely to be preferred when the plan was applied 100 times or to 100 areas than when the plan was applied only once or to only one area. We also found significant framing and reflection effects, both of which violated the invariance principle in the single-application condition, but not in the multiple-application condition. Furthermore, in the eye tracking study, we found distinctly different eye movement patterns in the single-application condition and the multiple-application condition. The eye movement patterns in the multiple-application condition are more consistent with the predictions deduced from expectation computation. The overall results suggest that a gap exists between the formulation and the implementation of an emergency plan. Formulating an emergency plan based on expectation-maximization is doable, but applying it to a single case may be more challenging.

Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13669877.2013.816333 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jriskr:v:17:y:2014:i:7:p:785-814

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJRR20

DOI: 10.1080/13669877.2013.816333

Access Statistics for this article

Journal of Risk Research is currently edited by Bryan MacGregor

More articles in Journal of Risk Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().