When there are multiple competing objectives in a decision-making process, Multi-Attribute Choice scoring models are excellent tools, permitting the incorporation of both subjective and objective attributes. However, their accuracy depends upon the subjective techniques used to construct the attribute scales and their concomitant weights. Conventional techniques using local scales tend to overemphasize small differences in attribute measures, which may yield erroneous conclusions. The Range Sensitivity Principle (RSP) is often invoked to adjust attribute weights when local scales are used. In practice, however, decision makers often do not follow the prescriptions of the Range Sensitivity Principle and under-adjust the weights, resulting in potentially poor decisions. Examples are discussed as is a proposed solution: the use of global scales instead of local scales.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Volume (Year): 4 (2009) Issue (Month): 6 (October) Pages: 492-508 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF
Handle: RePEc:jdm:journl:v:4:y:2009:i:6:p:492-508
Contact details of provider:
For technical questions regarding this item, or to correct its listing, contact: (Jonathan Baron).