First choice, sometimes called discrete choice, involves the selection of an item from a number of mutually exclusive items. This means that when a consumer chooses an item, this choice necessarily implies that all other items are rejected. There are numerous models to account for first choice and often these models predict the probability of choice based on a continuous function of driver variables. In this report we instead focus on a discrete approach to optimization, meaning that we use tools from discrete mathematics to account for the choices made by consumers.
This technical report appears as:
Ennis, J. M. and Fayle, C. M. (2010). Portfolio Optimization Based on First Choice. IFPress, 13(2) 2-3.
Download the entire technical report here:
Portfolio Optimization Based on First Choice
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This technical report also appears in our book, Tools and Applications of Sensory and Consumer Science.