Discrete Choice Modeling In Marketing Research

Related Articles

There are 11 articles in our archive related to this topic. Below are 5 selected at random and available to all users of the site.

Discrete choice modeling: Understanding a "better conjoint than conjoint"

Since its introduction 20 years ago as an innovative new way to determine consumers’ true product and service preferences, shortcomings have been discovered with conjoint analysis. This article discusses discrete choice modeling, which was developed as an analytical technique to resolve the problems with conjoint analysis.

Discrete choice modeling in pharmaceutical marketing research

This article discusses discrete choice modeling in pharmaceutical marketing research, including the difference between a conjoint study and a discrete choice study, what a discrete joint analysis does, validation and simulation, and limitations.

Data Use: Using discrete choice conjoint to validate stated-choice data

Offers ways to validate stated-choice data and compares the pros and cons of standalone questions types.

Conjoint evolves into discrete choice modeling

This article profiles discrete choice modeling which, unlike conjoint modeling, does not require pairing of all attributes. Therefore, unrealistic products are not produced. The respondent does not rate, sort or rank-order, but instead acts as if he or she is in the marketplace, selecting which product to buy.

Competitive strategy

The theory of business strategy stems from the need of managers to be able to counter the effects of external market forces. Without the tools needed to support it, firms may fall back on crisis management in reaction to unforeseen market forces. This article discusses competitive strategy, including discrete choice modeling.

See more articles on this topic

Recent Articles

Below are the 3 most recent articles on this topic. These articles were published within the last three years and are only available to registered subscribers.

Putting choice modeling to work for new product sales forecasting

The author discusses the differences between 21st-century choice modeling vs. old legacy forecasting systems and explains how choice modeling can offer a distinct advantage in being 3-D-compatible and simpler way to achieve more complete results.

Data Use: A good choice for choice modeling

Maximum difference scaling lets researchers present respondents with large numbers of choice options without making the process onerous. The article uses examples of a hotel loyalty program and restaurant menu optimization to show the technique in action.

Overcome these common hazards to seize their potential

This article explains to how effectively execute a mixed-method market research project and avoid having the many facets end up as little more than disparate parts of an incomplete whole.