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2014 | OriginalPaper | Buchkapitel

8. Applications for Pricing Decisions

verfasst von : Vithala R. Rao

Erschienen in: Applied Conjoint Analysis

Verlag: Springer Berlin Heidelberg

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Abstract

One significant application of conjoint analysis is in helping the manager with pricing decisions. Determination of optimal price for a new product (or brand) is a typical application. One way to determine the best price is to estimate the market obtainable from the new product at different feasible prices for the new product profile. We described the use of conjoint simulators in Chap. 3. Additional information on cost functions can be integrated into the estimates of market share to yield estimates of profit from the new product at various prices. The price at which the computed profit is highest can be deemed to be the best price for the new product. This approach can also yield a generic estimate of price elasticity for the product category as a whole.

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Vorheriges Kapitel Applications for Product Positioning and Market Segmentation

Nächstes Kapitel Applications to a Miscellany of Marketing Problems

Nur mit Berechtigung zugänglich

While we use the notion of maximum price for a reservation price here (i.e. the probability of buying a product beyond the price is zero), other concepts using other probabilities can be employed. See Wang et al. (2007).

See Mahajan et al. (1982)

This procedure can also incorporate dynamics of the market, if desired. For this purpose, a brand-switching matrix can be constructed for each experimental price condition by forming subgroups of respondents according to the brand last purchased and the matrix of average of responses for each subgroup or brand constitutes the brand-switching matrix. Using the initial market shares as the base, this brand-switching matrix can be powered to obtain market shares for subsequent (hypothetical) periods of time. The market shares for a future time period can be the starting point for logit analysis

This discussion is adapted from Kohli and Mahajan (1991)

This is a convenient assumption. It can be relaxed, if needed.

Ignoring the constant m, the derivative is: −h(p_n)(p_n−c_n)−(1−H(p_n)) and when this is set equal to zero, we get the solution in (8.7).

Reservation prices can also be elicited directly for product concepts. Kalish and Nelson (1991) found that the method of direct elicitation of reservation prices has worse predictive validity than the conjoint methods using ranking or rating.

We will return to this issue in the section on separating the informational and allocative effects of price.

Both preferences were measured on a zero to 100 scale. The authors explicitly tested the assumption of equality of effects of attributes (excluding price) in the unconstrained and constrained preferences at the individual level and found that this assumption is justified for over 82 % of the respondents at a 0.10 significance level. Thus, the estimation method employed seems appropriate.

The data were also analyzed using a latent class model and the results were about the same in terms of fit and predictive ability for the two procedures. Both methods account for heterogeneity among the sample individuals. The paper contains predictive validity results as well.

The catering company also sets fixed fees for setting up the catering arrangement and arranging special banquets; but these were beyond the scope this study.

This method involves dividing the range for each parameter into a number of intervals and computing the value of the objective function for various combinations of the intervals across parameters.

The authors also developed a two-segment solution for choice data that excludes the bundle option. But, for our purpose, the choice data with bundle is more appropriate.

In an unpublished paper, Iyengar and Jedidi (2012) applied choice-based conjoint methods for determining quantity discounts.

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Titel: Applications for Pricing Decisions
verfasst von: Vithala R. Rao
Verlag: Springer Berlin Heidelberg
Buch: Applied Conjoint Analysis
Print ISBN: 978-3-540-87752-3

Electronic ISBN: 978-3-540-87753-0

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-540-87753-0_8