The Application of Conjoint Analysis in Forecasting
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Abstract:
In this paper, the general principles and methodology of conjoint analysis are discussed. When the effectiveness function is obtained through conjoint analysis, the forecast of product sales can be made to determine the best combination of product features. Based on the discussion, the bright prospect of the application of conjoint analysis in forecasting technology is suggested.Keywords:
Conjoint Analysis
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Conjoint Analysis
Unobservable
Market Segmentation
Rank (graph theory)
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Conjoint Analysis
Multidimensional scaling
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The conjoint approach to measurement and analysis is demonstrated in this article through a test of an evaluation utilizationprocess-model that includes two endogenous variables (predicted participation and predicted instrumental utilization). Conjoint measurement involves having respondents rate attribute profiles that are analogous to concepts based on cells in a factorial analysis of variance. Such multidimensional ratings result in ecologically valid measurements because respondents examine and react to wholes, rather than to single unidimensional items as in traditional survey research. Statistically, conjoint analysis is a "decompositional" technique in which respondents' overall reactions to profiles (hypothetical situations) are decomposed to determine how much importance is given to attributes (variables used in the profiles) and to levels of the attributes.
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Factorial
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This paper introduces HILCA, a new conjoint analysis procedure with which purchasing decisions on complex products can be better modelled. The survey and analysis procedures are described in detail. The procedure is compared in a methodology test with a standard conjoint analysis procedure used for such research issues. It produces with roughly the same length of interview much more valid and easier to interpret results.
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Background Concepts and Theory Design and Analysis of Conjoint Experiments Practical Applications of Conjoint Theory and Methods Predicting Likely Market Choices from Conjoint Studies and Other Strategic Applications of Conjoint Models
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Choice modelling with conjoint analysis - Trends in marketing applications; Historical Development; Conjoint Analysis as Successor of Conjoint Measurement; Some Commercial Applications of Conjoint Analysis; Why conjoint work
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Conjoint Analysis
Choice set
Consumer Choice
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We propose and empirically evaluate a new hybrid estimation approach that integrates choice-based conjoint with repeated purchase data for a dense consumer panel, and show that it increases the accuracy of conjoint predictions for actual purchases observed months later. Our key innovation lies in combining conjoint data with a long and detailed panel of actual choices, both before and after the product line introduction, for both survey respondents and a random sample of the target population. By linking the actual purchase and conjoint data, we can estimate preferences for attributes not yet present in the marketplace, while also addressing many of the key limitations of conjoint analysis, including sample selection and contextual differences. A counterfactual product and pricing exercise illustrates its managerial relevance.
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Consumer Demand
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