Marketers routinely make use of stated consumer preferences and the relative attribute-importance weights implied by these preferences when making decisions on issues such as advertising messages and product design. Using this information as a basis for managerial decision making is risky,...

The positioning and pricing of a new brand requires knowledge about the relationship of both demand and cost with potential attribute locations and prices. This paper addresses this problem and illustrates it in the context of the automobile market. Multi-attribute expected utility theory which...

The efficient operation of a salesforce is a critical element in the profitability of many firms. Three factors play key roles: the salesforce's size, its allocation and its productivity. This gives rise to the following questions: can salesforce performance be improved by (1) hiring more...

This paper extends the scanner-based choice literature by explicitly incorporating individual-level brand-preference data. We illustrate our model using a unique data set that combines survey and scanner data collected from the same individuals. The addition of individual-specific...

Linear programming-based estimation procedures are used in a variety of arenas. Two notable areas are multiattribute utility models (LINMAP) and production frontiers (data envelopment analysis (DEA)). Both LINMAP and DEA have theoretical and managerial advantages. For example, LINMAP treats...

Ordinal preference measures have a number of advantages relative to cardinal measures in the estimation of individual level multi-attribute utility functions. This paper: (a) outlines a theoretical foundation for estimating a cardinal scaled utility function from ordinal preference data, in...