Conjoint Measurement- for Quantifying Judgmental Data

Conjoint measurement is a new development in mathematical psychology that can be used to measure the joint effects of a set of independent variables on the ordering of a dependent variable. In this (primarily expository) article, the techniques are applied to illustrative problems in marketing. In addition, a number of possible areas of application to marketing research are discussed, as well as some of the methodology's limitations.

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Preference Measurement with Conjoint Analysis. Overview of State-of-the-Art Approaches and Recent Developments

GfK Marketing Intelligence Review ◽

10.2478/gfkmir-2014-0054 ◽

2011 ◽

Vol 3 (1) ◽

pp. 36-47 ◽

Cited By ~ 13

Author(s):

Felix Eggers ◽

Henrik Sattler

Keyword(s):

Conjoint Analysis ◽

State Of The Art ◽

Consumer Preferences ◽

Measurement Techniques ◽

Marketing Research ◽

Conjoint Measurement ◽

Preference Measurement ◽

Research Setting ◽

Specific Research ◽

Recent Developments

Abstract Determining consumer preferences is still one of the most important topics in marketing research. Not surprisingly, numerous approaches have been developed for this task. Conjoint measurement techniques are among the most prominent and different forms have emerged over the years. Depending on the specific research setting, all of them have their advantages and drawbacks. The authors discuss the nature and applicability of recent conjoint approaches and provide examples. Guidelines for selecting the optimal technique help to identify which approach works best in a given situation.

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Advertising Claim Objectivity: Antecedents and Effects

Journal of Marketing ◽

10.1177/002224299305700408 ◽

1993 ◽

Vol 57 (4) ◽

pp. 100-113 ◽

Cited By ~ 33

Author(s):

William K. Darley ◽

Robert E. Smith

Keyword(s):

Marketing Research ◽

Elaboration Likelihood Model ◽

Purchase Intentions ◽

Elaboration Likelihood ◽

Brand Attitudes ◽

Broadcast Media ◽

Independent Variables ◽

Likelihood Model ◽

Central Route

The authors examine the role of advertising claim objectivity under central route processing conditions. Past studies are reviewed and two distinct components of claim objectivity are identified: attribute tangibility and factualness of description. Specific predictions are made concerning the effects of claim objectivity on perceived ad credibility, brand beliefs, ad attitudes, brand attitudes, and purchase intentions. Using the Elaboration Likelihood Model different results are predicted for print and broadcast media. A study is conducted in which the degree of claim objectivity (objective, subjective, and mixed) and the type of media (radio or print) are manipulated as independent variables while various message and consumer variables are controlled or measured as covariates. Results show that both tangibility and factualness contribute to claim objectivity effects, that objective claims are more effective than subjective claims, and that no content differences emerge between print and radio media. Implications for marketing research and practice are discussed.

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SWAT: Do We Need Conjoint Measurement?

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129503901902 ◽

1995 ◽

Vol 39 (19) ◽

pp. 1233-1237 ◽

Cited By ~ 4

Author(s):

David W. Biers

Keyword(s):

Rating Scales ◽

Conjoint Measurement ◽

Composite Measure ◽

Card Sort ◽

Assessment Technique ◽

Independent Variables ◽

Composite Measures ◽

Simulator Study ◽

Highly Correlated ◽

Percentage Measure

The present study sought to determine the utility of the unweighted sum as an alternative to conjoint measurement in forming a workload composite measure with the Subjective Workload Assessment Technique (SWAT). The data from a simulator study designed to identify pilot workload associated with alternative cockpit configurations in a night air interdiction mission were reanalyzed using a percentage measure (SUMPCT) based on the unweighted sum of the three SWAT rating scales. Results indicated that the CONJOINT and SUMPCT workload composites were highly correlated and were equally sensitive to detecting differences in the independent variables. The reasons for the equal sensitivity of the two composite measures are discussed. This study adds to the growing body of evidence that one can form a composite measure of workload using the SWAT rating scales without the necessity of having to conduct the time-consuming card sort.

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Checking the Success of Manipulations in Marketing Experiments

Journal of Marketing Research ◽

10.1177/002224378602300401 ◽

1986 ◽

Vol 23 (4) ◽

pp. 317-326 ◽

Cited By ~ 142

Author(s):

Barbara C. Perdue ◽

John O. Summers

Keyword(s):

Construct Validity ◽

Marketing Research ◽

Independent Variables ◽

The Past ◽

Potential Sources ◽

Alternative Approaches

The authors discuss several issues in the timing, construction, and analysis of manipulation and confounding checks in marketing experiments. A review of 34 experiments involving latent independent variables reported in the Journal of Marketing Research over the past decade suggests that most researchers are familiar with the concept of manipulation checks but few systematically evaluate potential sources of confounding in experimental manipulations. Three alternative approaches for assessing the construct validity of experimental manipulations also are discussed.

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D-test: A New Test for Analyzing Scale Invariance Using Symbolic Dynamics and Symbolic Entropy

Methodology ◽

10.1027/1614-2241/a000026 ◽

2011 ◽

Vol 7 (3) ◽

pp. 88-95 ◽

Cited By ~ 2

Author(s):

Jose A. Martínez ◽

Manuel Ruiz Marín

Keyword(s):

Symbolic Dynamics ◽

Scale Invariance ◽

Rating Scales ◽

Rating Scale ◽

Marketing Research ◽

Response Patterns ◽

Measurement Scales ◽

Improve Measurement ◽

Entropy Measures ◽

The Difference

The aim of this study is to improve measurement in marketing research by constructing a new, simple, nonparametric, consistent, and powerful test to study scale invariance. The test is called D-test. D-test is constructed using symbolic dynamics and symbolic entropy as a measure of the difference between the response patterns which comes from two measurement scales. We also give a standard asymptotic distribution of our statistic. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. We applied D-test to a real marketing research to study if scale invariance holds when measuring service quality in a sports service. We considered a free-scale as a reference scale and then we compared it with three widely used rating scales: Likert-type scale from 1 to 5 and from 1 to 7, and semantic-differential scale from −3 to +3. Scale invariance holds for the two latter scales. This test overcomes the shortcomings of other procedures for analyzing scale invariance; and it provides researchers a tool to decide the appropriate rating scale to study specific marketing problems, and how the results of prior studies can be questioned.

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