Abstract
Conjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 678-690 |
| Number of pages | 13 |
| Journal | Decision Sciences |
| Volume | 11 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jan 1 1980 |
| Externally published | Yes |
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Keywords
- Decision Processes
- Human Information Processing
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Strategy and Management
- Information Systems and Management
- Management of Technology and Innovation
Cite this
SOME CAUTIONARY NOTES ON THE USE OF CONJOINT MEASUREMENT FOR HUMAN JUDGMENT MODELING. / Messier, William F.; Emery, Douglas.
In: Decision Sciences, Vol. 11, No. 4, 01.01.1980, p. 678-690.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - SOME CAUTIONARY NOTES ON THE USE OF CONJOINT MEASUREMENT FOR HUMAN JUDGMENT MODELING
AU - Messier, William F.
AU - Emery, Douglas
PY - 1980/1/1
Y1 - 1980/1/1
N2 - Conjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.
AB - Conjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.
KW - Decision Processes
KW - Human Information Processing
UR - http://www.scopus.com/inward/record.url?scp=84925924365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925924365&partnerID=8YFLogxK
U2 - 10.1111/j.1540-5915.1980.tb01169.x
DO - 10.1111/j.1540-5915.1980.tb01169.x
M3 - Article
VL - 11
SP - 678
EP - 690
JO - Decision Sciences
JF - Decision Sciences
SN - 0011-7315
IS - 4
ER -