377,427 research outputs found
Incentive-aligned Conjoint Analysis
Get PDFBecause most conjoint studies are conducted in hypothetical situations with no consumption consequences for the participants, the extent to which the studies are able to uncover "true" consumer preference structures is questionable. Experimental economics literature, with its emphasis on incentive alignment and hypothetical bias, suggests that more realistic incentivealigned studies will result in stronger out-of-sample predictive performance of actual purchase behaviors and provide better estimates of consumer preference structures than hypothetical studies. To test this hypothesis, the authors design an experiment with conventional (hypothetical) conditions and their parallel incentive-aligned counterparts. Using Chinese dinner specials as the context, the authors conducted a field experiment in a Chinese restaurant during dinnertime. The results provide strong evidence in favor of incentive-aligned choice conjoint analysis, in that incentive-aligned choice conjoint outperforms hypothetical choice conjoint in out-of-sample predictions (59% versus 26% for incentive-aligned choice conjoint and hypothetical choice conjoint, respectively for the top two choices). As expected, subjects in the incentive-aligned choice condition exhibit preference structures that are systematically different from the preference structures of subjects in the hypothetical condition. Most notably, the subjects in the incentive-aligned choice condition are more price sensitive and exhibit different heterogeneity patterns. To determine the robustness of these results, the authors conducted a second study that used snacks as the context and only considered the choice treatments. This study confirmed the results by again providing strong evidence in favor of incentive-aligned choice analysis in out-of-sample predictions (36% versus 16% for incentive-aligned choice conjoint and hypothetical choice conjoint, respectively for the top two choices). The results provide a strong motivation for conjoint practitioners to consider conducting their studies in realistic settings using incentive structures that require participants to æ–—ive with?their decisions.
The Importance of Apple attributes: A Comparison of Self-explicated and Conjoint Analysis Results
Get PDFthe goal of this article was to determine the importance of apple attributes using two research techniques – self-explicated procedure and conjoint analysis. Research was conducted on a sample of 426 consumers of apples in Zagreb, Croatia. The results of self-explicated and conjoint analysis procedures revealed differences in ranking of apple attributes regarding their importance. It is demonstrated that conjoint analysis gives more detailed results and that it is not influenced by respondents’ tendency to give socially acceptable answers. The results of conjoint analysis also give more information for the producers of apples who can use them to create a product that matches consumers’ wishes.apple, conjoint analysis, self-explicated method, Demand and Price Analysis,
ANALYZING CUSTOMER VALUE USING CONJOINT ANALYSIS: THE EXAMPLE OF A PACKAGING COMPANY
Get PDFThe fulfillment of customers’ wishes in a profitable way requires that companies understand which aspects of their product and service are most valued by the customer. Conjoint analysis is considered to be one of the best methods for achieving this purpose. Conjoint analysis consists of generating and conducting specific experiments among customers with the purpose of modeling their purchasing decision. This article will give an overview of the method and apply it to an Estonian packaging company. As a result of the empirical study the author is able to estimate the value creation models of 34 respondents (customers) both on a group and individual basis.customer value, conjoint analysis, market research methods
Correspondence analysis and categorical conjoint measurement
Get PDFWe show the equivalence between the use of correspondence analysis (CA) of concadenated tables and the application of a particular version of conjoint analysis called categorical conjoint measurement (CCM). The connection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of the analysis and shows how to pass between the results of each analysis.Correspondence analysis, conjoint analysis, canonical correlation, categorical data
Analysis of Cardinal and Ordinal Assumptions in Conjoint Analysis
Get PDFOf twenty-three agricultural economics conjoint analyses conducted between 1990 and 2001, seventeen used interval-rating scales, with estimation procedures varying widely. This study tests cardinality assumptions in conjoint analysis when interval-rating scales are used, and tests whether the ordered probit or two-limit tobit model is the most valid. Results indicate that cardinality assumptions are invalid, but estimates of the underlying utility scale for the two models do not differ. Thus, while the ordered probit model is theoretically more appealing, the two-limit tobit model may be more useful in practice, especially in cases with limited degrees of freedom, such as with individual-level conjoint models.ordered probit, two-limit probit, conjoint analysis, cardinality, Research Methods/ Statistical Methods,
A comparison between correspondence analysis and categorical conjoint measurement
Get PDFWe show the equivalence of using correspondence analysis of concatenated tables and a particular algorithm of conjoint analysis named categorical conjoint measurement. The connection is made using canonical correlation. However, although we have proved that equivalence, the standard practice of conjoint analyses to focus in one dimension (the optimal solution) has some shortcomings once we introduce interaction effects. In that case, the use of visual techniques, like correspondence analysis, provides a faster and easier way to compile the preference structure. Finally, we provide an application of our setting making use of an experiment of perfumes where interaction effects between type of essences and strength of essences are shown
ASSESSING THE IMPORTANCE OF APPLE ATTRIBUTES: AN AGRICULTURAL APPLICATION OF CONJOINT ANALYSIS
Get PDFThe 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.Food Consumption/Nutrition/Food Safety,
Estimating nonuse values using conjoint analysis
Get PDFConjoint analysis is a stated-preference technique for eliciting valuations of nonmarket, multi-attribute commodities. Recently it has begun to be used in environmental economics as an alternative to contingent valuation. In applications to environmental economics, though, conjoint analysis has been used to estimate use values or total values—the sum of use and nonuse values. We show a simple way to estimate the value of a resource to those who should have only nonuse values and illustrate using two surveys about national parks in Maine.
Bridiging designs for conjoint analysis: The issue of attribute importance.
Get PDFAbstract: Conjoint analysis studies involving many attributes and attribute levels often occur in practice. Because such studies can cause respondent fatigue and lack of cooperation, it is important to design data collection tasks that reduce those problems. Bridging designs, incorporating two or more task subsets with overlapping attributes, can presumably lower task difficulty in such cases. In this paper, we present results of a study examining the effects on predictive validity of bridging design decisions involving important or unimportant attributes as links (bridges) between card-sort tasks and the degree of balance and consistency in estimated attribute importance across tasks. We also propose a new symmetric procedure, Symbridge, to scale the bridged conjoint solutions.Studies; Cooperation; Data; Problems; Effects; Decisions;
Ranking Models in Conjoint Analysis
Get PDFIn this paper we consider the estimation of probabilisticranking models in the context of conjoint experiments. By usingapproximate rather than exact ranking probabilities, we do notneed to compute high-dimensional integrals. We extend theapproximation technique proposed by \\citet{Henery1981} in theThurstone-Mosteller-Daniels model for any Thurstone orderstatistics model and we show that our approach allows for aunified approach. Moreover, our approach also allows for theanalysis of any partial ranking. Partial rankings are essentialin practical conjoint analysis to collect data efficiently torelieve respondents' task burden.conjoint experiments;partial rankings;thurstone order statistics model
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