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Attribute Importance Weights Modification in Assessing a Brand's Competitive Potential

Author

Listed:
  • Paul E. Green

    (University of Pennsylvania)

  • Abba M. Krieger

    (University of Pennsylvania)

Abstract

Increasingly, researchers in marketing are recognizing the “lability” of attribute importance weights derived from measurement techniques, such as conjoint analysis. As has been suggested by Simonson and Tversky, attribute importance weights can be sensitive to competitive product context and to purchase situation. This paper describes and applies a procedure for adjusting conjoint importance weights to predict consumers' actual or potential product choices. We discuss the approach from both a descriptive and prescriptive viewpoint. In particular, the latter perspective provides strategic insights into how attribute importance modifications can increase brand share. An industry case, based on real data, is used to illustrate the approach.

Suggested Citation

  • Paul E. Green & Abba M. Krieger, 1995. "Attribute Importance Weights Modification in Assessing a Brand's Competitive Potential," Marketing Science, INFORMS, vol. 14(3), pages 253-270.
    • Handle: RePEc:inm:ormksc:v:14:y:1995:i:3:p:253-270
    DOI: 10.1287/mksc.14.3.253
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    Citations

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    Cited by:

    1. Teichert, Thorsten Andreas, 1997. "Schätzgenauigkeit von Conjoint-Analysen," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 444, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    2. Carlberg, Jared G. & Ward, Clement E. & Holcomb, Rodney B., 2006. "Success Factors for New Generation Cooperatives," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 9(1), pages 1-20.
    3. Tripathi Sanjeev & Sinha, Piyush Kumar & Sinha, Piyush Kumar, 2006. "Family and Store Choice - A Conceptual Framework," IIMA Working Papers WP2006-11-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    4. Sandeep R. Chandukala & Yancy D. Edwards & Greg M. Allenby, 2011. "Identifying Unmet Demand," Marketing Science, INFORMS, vol. 30(1), pages 61-73, 01-02.
    5. Srinivasan, V. Seenu & Netzer, Oded, 2007. "Adaptive Self-Explication of Multi-attribute Preferences," Research Papers 1979, Stanford University, Graduate School of Business.
    6. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.
    7. Cornelia Schön, 2010. "On the Optimal Product Line Selection Problem with Price Discrimination," Management Science, INFORMS, vol. 56(5), pages 896-902, May.
    8. Vishal Narayan & Vithala R. Rao & Carolyne Saunders, 2011. "How Peer Influence Affects Attribute Preferences: A Bayesian Updating Mechanism," Marketing Science, INFORMS, vol. 30(2), pages 368-384, 03-04.
    9. Luce, Mary Frances & Payne, John W. & Bettman, James R., 2000. "Coping with Unfavorable Attribute Values in Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 81(2), pages 274-299, March.
    10. Huang, Rong & Sarigöllü, Emine, 2008. "Assessing satisfaction with core and secondary attributes," Journal of Business Research, Elsevier, vol. 61(9), pages 942-949, September.
    11. John R. Hauser & Olivier Toubia, 2005. "The Impact of Utility Balance and Endogeneity in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(3), pages 498-507, August.

    More about this item

    Keywords

    competitive strategy; scaling methods;

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