Skip to main content

Robust Preference Measurement A Simulation Study of Erroneous and Ambiguous Judgement’s Impact on AHP and Conjoint Analysis

  • Conference paper
Operations Research Proceedings 2005

Part of the book series: Operations Research Proceedings ((ORP,volume 2005))

Summary

Despite the recent methodological progress to unburden respondents in preference analysis the quality of consumers’ judgements is fundamental for marketing research results. Surprisingly, the impact of ambiguous and erroneous judgments given by the respondents is widely neglected in the marketing literature. In this paper we compare the Analytic Hierarchy Process and Conjoint Analysis with respect to the impact of random errors as well as ambiguities in preference statements by means of Monte Carlo simulation studies. Referring to Thurstone’s law of comparative judgements, we demonstrate the superior robustness of the Analytic Hierarchy Process in dealing with these kinds of perturbing effects.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Fischhoff, B. (1991). Value elicitation: Is there anything in there? American Psychologist, 46, 837–847.

    Article  Google Scholar 

  • Fujii, S. and Gärling, T. (2003). Application of attitude theory for improved predictive accuracy of stated preference methods in travel demand analysis. Transport Research A, 37(4), 289–402.

    Google Scholar 

  • Kuhfeld, W. F. (2004). Marketing Research Methods in SAS: Experimental Design, Choice, Conjoint, and Graphical Techniques. SAS, Carry.

    Google Scholar 

  • Pommerehne, W. W., Schneider, F., and Zweifel, P. (1982). Economic theory of choice and the preference reversal phenomenon: A reexamination. The American Economic Review, 72(3), 569–574.

    Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.

    Google Scholar 

  • Schmidt, F. L. and Hunter, J. E. (1999). Theory testing and measurement error. Intelligence, 27(3), 138–198.

    Article  Google Scholar 

  • Scholl, A., Manthey, L., Helm, R., and Steiner, M. (2005). Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison. European Journal of Operational Research, 164, 760–777.

    Article  MATH  Google Scholar 

  • Thurstone, L. (1927). A law of comparative judgment. Psychological Review, 34, 273–286.

    Article  Google Scholar 

  • Torgerson, W. (1958). Theory and methods of scaling. Wiley, New York.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Scholz, S.W., Meißner, M., Wagner, R. (2006). Robust Preference Measurement A Simulation Study of Erroneous and Ambiguous Judgement’s Impact on AHP and Conjoint Analysis. In: Haasis, HD., Kopfer, H., Schönberger, J. (eds) Operations Research Proceedings 2005. Operations Research Proceedings, vol 2005. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32539-5_96

Download citation

Publish with us

Policies and ethics