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The Effects of Splitting Attributes on Weights in Multiattribute Utility Measurement

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Author Info

  • Martin Weber

    (Rheinisch-Westfälische Technische Hochschule Aachen, Lehr- und Forschungsgebiet Allgemeine Betriebswirtschaftslehre, Templergraben 64, 5100 Aachen, Federal Republic of Germany)

  • Franz Eisenführ

    (Rheinisch-Westfälische Technische Hochschule Aachen, Lehr- und Forschungsgebiet Allgemeine Betriebswirtschaftslehre, Templergraben 64, 5100 Aachen, Federal Republic of Germany)

  • Detlof von Winterfeldt

    (Systems Science Department, Institute of Safety and Systems Management, University of Southern California, Los Angeles, California 90089-0021)

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    Abstract

    This study examined how weights in multiattribute utility measurement change when objectives are split into more detailed levels. Subjects were asked to weight attributes in value trees containing three objectives which were specified by either three, four, five, or six attributes. The robust finding was that the more detailed parts of the value tree were weighted significantly higher than the less detailed ones. This overweighting bias was found for several weighting techniques, but the techniques that used holistic judgments to derive weights were affected somewhat less than techniques that used decomposed attribute weights. This bias is interpreted in terms of the increased salience and availability of attributes that are spelled out in more detail.

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    File URL: http://dx.doi.org/10.1287/mnsc.34.4.431
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 34 (1988)
    Issue (Month): 4 (April)
    Pages: 431-445

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    Handle: RePEc:inm:ormnsc:v:34:y:1988:i:4:p:431-445

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    Keywords: multiattribute utility; value trees; structuring;

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    Cited by:
    1. Humphrey, Steven J., 2000. "The common consequence effect: testing a unified explanation of recent mixed evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 41(3), pages 239-262, March.
    2. Doyle, J. R. & Arthurs, A. J. & Green, R. H. & McAulay, L. & Pitt, M. R. & Bottomley, P. A. & Evans, W., 1996. "The judge, the model of the judge, and the model of the judged as judge: Analyses of the UK 1992 research assessment exercise data for business and management studies," Omega, Elsevier, vol. 24(1), pages 13-28, February.
    3. Mustajoki, Jyri, 2012. "Effects of imprecise weighting in hierarchical preference programming," European Journal of Operational Research, Elsevier, vol. 218(1), pages 193-201.
    4. Gilberto Montibeller & Alberto Franco & Ewan Lord & Aline Iglesias, 2008. "Structuring multi-criteria portfolio analysis models," LSE Research Online Documents on Economics 22693, London School of Economics and Political Science, LSE Library.
    5. Zhang, Jiao & Hsee, Christopher K. & Xiao, Zhixing, 2006. "The majority rule in individual decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 99(1), pages 102-111, January.
    6. Steven J Humphrey & Luke Lindsay & Chris Starmer, 2012. "Consumption experience, choice experience and the endowment effect," Discussion Papers 2012-16, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    7. Doyle, John R. & Green, Rodney H. & Bottomley, Paul A., 1997. "Judging Relative Importance: Direct Rating and Point Allocation Are Not Equivalent," Organizational Behavior and Human Decision Processes, Elsevier, vol. 70(1), pages 65-72, April.
    8. Schuwirth, N. & Reichert, P. & Lienert, J., 2012. "Methodological aspects of multi-criteria decision analysis for policy support: A case study on pharmaceutical removal from hospital wastewater," European Journal of Operational Research, Elsevier, vol. 220(2), pages 472-483.
    9. Hämäläinen, Raimo P. & Alaja, Susanna, 2008. "The threat of weighting biases in environmental decision analysis," Ecological Economics, Elsevier, vol. 68(1-2), pages 556-569, December.
    10. Strager, Michael P. & Rosenberger, Randall S., 2006. "Incorporating stakeholder preferences for land conservation: Weights and measures in spatial MCA," Ecological Economics, Elsevier, vol. 57(4), pages 627-639, June.
    11. Peter Wakker & Danielle Timmermans & Irma Machielse, 2007. "The effects of statistical information on risk ambiguity attitudes, and on rational insurance decisions," Natural Field Experiments 00338, The Field Experiments Website.
    12. Arondel, Cecile & Girardin, Philippe, 2000. "Sorting cropping systems on the basis of their impact on groundwater quality," European Journal of Operational Research, Elsevier, vol. 127(3), pages 467-482, December.
    13. Vetschera, Rudolf, 1996. "A recursive algorithm for volume-based sensitivity analysis of linear decision models," Discussion Papers, Series 1 279, University of Konstanz, Department of Economics.
    14. Strager, Michael P. & Rosenberger, Randall S., 2006. "Incorporating stakeholder preferences for land conservation: Weights and measures in spatial MCA," Ecological Economics, Elsevier, vol. 58(1), pages 79-92, June.
    15. Marttunen, Mika & Hamalainen, Raimo P., 1995. "Decision analysis interviews in environmental impact assessment," European Journal of Operational Research, Elsevier, vol. 87(3), pages 551-563, December.
    16. van Calker, K.J. & Berentsen, P.B.M. & Romero, C. & Giesen, G.W.J. & Huirne, R.B.M., 2006. "Development and application of a multi-attribute sustainability function for Dutch dairy farming systems," Ecological Economics, Elsevier, vol. 57(4), pages 640-658, June.
    17. Abellan-Perpiñan, Jose Maria & Bleichrodt, Han & Pinto-Prades, Jose Luis, 2009. "The predictive validity of prospect theory versus expected utility in health utility measurement," Journal of Health Economics, Elsevier, vol. 28(6), pages 1039-1047, December.
    18. Poyhonen, Mari & Vrolijk, Hans & Hamalainen, Raimo P., 2001. "Behavioral and procedural consequences of structural variation in value trees," European Journal of Operational Research, Elsevier, vol. 134(1), pages 216-227, October.

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