Assessing quality improvement initiatives when expert judgements are uncertain

E D Hahn () and C L Knott
Additional contact information
E D Hahn: Salisbury University
C L Knott: Marymount University

Journal of the Operational Research Society, 2008, vol. 59, issue 2, 252-258

Abstract: Abstract A new approach for examining quality improvement initiatives regarding errors in the US Census Bureau's Master Address File (MAF) and the Topologically Integrated Geographic and Referencing System (TIGER) databases is presented. A stochastic multi-criteria decision-making method involving Bayesian weighted hierarchical multinomial logit models is used to conduct inference on the priorities in a multiple-expert decision scenario. Quality initiatives regarding basic street address-level address matching, geocoding completeness, and geocoding quality were judged to be the most important for MAF/TIGER improvement at the 95% probability level. The approach allows managers to go one step further in understanding the relative impact of various types of errors on overall quality and thus be better prepared to select approaches to reduce these errors.

Keywords: decision support systems; stochastic multi-criteria decision making; government; geographic information systems; group decision making (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2602484 Abstract (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:pal:jorsoc:v:59:y:2008:i:2:d:10.1057_palgrave.jors.2602484

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

DOI: 10.1057/palgrave.jors.2602484

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().