Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-19T20:31:48.791Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessing the Importance of Apple Attributes: An Agricultural Application of Conjoint Analysis

Published online by Cambridge University Press:  10 May 2017

Alberto B. Manalo
Alberto B. Manalo*
Affiliation:
University of New Hampshire
Get access

Abstract

The use of conjoint analysis in assessing consumers’ preferences for attributes is demonstrated with the apple as an example. Conjoint analysis may be used to estimate the importance of attributes and attribute levels through decomposition of consumers’ ranking of alternative attribute combinations. It is shown that conjoint analysis provides results that may not be obtained from a survey where respondents are asked to directly state their assessment of the importance of attributes.

Type
Articles
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 19 , Issue 2 , October 1990 , pp. 118 - 124
Copyright
Copyright © 1990 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The comments of an anonymous reviewer are gratefully acknowledged.

This paper is Scientific Contribution no. 1700 of the New Hampshire Experiment Station.

References

Addelman, Sidney. “Orthogonal Main-Effect Plans for Asymmetrical Factorial Experiments.” Technometrics 4(February 1962):21–46.Google Scholar
Cattin, Philippe, and Wittink, Dick R. “Commercial Use of Conjoint Analysis: A Survey.” Journal of Marketing 46(Summer 1982):44–53.Google Scholar
Cohen, Jacob, and Cohen, Patricia. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Earlbaum Associates, Inc., 1983.Google Scholar
Currim, Imran S., Weinberg, Charles B., and Wittink, Dick R. “Design of Subscription Programs for a Performing Arts Series.” Journal of Consumer Research 8(June 1981):67–75.Google Scholar
Green, Paul E., and DeSarbo, Wayne S. “Additive Decomposition of Perceptions Data Via Conjoint Analysis.” Journal of Consumer Research 5(June 1978):58–65.Google Scholar
Green, Paul E., and Helsen, Kristiaan. “Cross-Validation Assessment of Alternatives to Individual-Level Conjoint Analysis: A Case Study.” Journal of Marketing Research 26(August 1989):346–50.Google Scholar
Green, Paul E., and Rao, Vithala R. “Conjoint Measurement for Quantifying Judgmental Data.” Journal of Marketing Research 8(August 1971):355–63.Google Scholar
Green, Paul E., and Srinivasan, V. “Conjoint Analysis in Consumer Research: Issues and Outlook.” Journal of Consumer Research 5 (September 1978):103–23.Google Scholar
Green, Paul E., and Tull, Donald S. Research for Marketing Decisions. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1978.Google Scholar
Green, Paul E., and Wind, Yoram. “New Way to Measure Consumers’ Judgments.” Harvard Business Review 53 (July-August 1975):107–17.Google Scholar
Hagerty, Michael R. “Improving the Predictive Power of Conjoint Analysis: The Use of Factor Analysis and Cluster Analysis.” Journal of Marketing Research 22 (May 1985):168–84.Google Scholar
Kamakura, Wagner A. “A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments.” Journal of Marketing Research 25 (May 1988):157–67.Google Scholar
Kotler, Philip. Marketing Management: Analysis, Planning, and Control. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1984.Google Scholar
Lancaster, Kelvin J. “A New Approach to Consumer Theory.” Journal of Political Economy 74 (1966):132–57.Google Scholar
Moore, William L. “Levels of Aggregation in Conjoint Analysis.” Journal of Marketing Research 17(November 1980):516–23.Google Scholar
Ratchford, Brian T. “The New Economic Theory of Consumer Behavior: An Interpretive Essay.” Journal of Consumer Research 2(September 1975):65–75.Google Scholar
Wittink, Dick R., and Cattin, Philippe. “Alternative Estimation Methods for Conjoint Analysis: A Monte Carlo Study.” Journal of Marketing Research 18 (February 1981):101–6.Google Scholar
Wittink, Dick R., and Cattin, Philippe. “Commercial Use of Conjoint Analysis: An Update.” Journal of Marketing 53(July 1989):91–96.Google Scholar