Volumetric CBC

(This is an advanced topic, and requires customized data processing of the .CHS file. See the section in this documentation on .CHS File Format for file format information.)

In some situations, it might make sense to use allocation-based choice tasks, but to not force the answers to sum to any particular value. For example, for FMCG (fast-moving-consumer-goods) we might ask respondents how many of each product within a richly defined task they would purchase. There is some debate in the industry whether respondents can complete such a task reliably; but, if they could provide accurate answers to these questions, it would allow the researcher to examine whether the overall category volume would increase or decrease given a certain competitive scenario. Furthermore, we would be able to report absolute shares of unit volume using the market simulator rather than just relative shares of preference.

We do not necessarily know the best way to model such data, but we offer the following suggestion (which has been applied by other experienced users as well):

1. Use a script-based *program to modify the .CHS file. First, change the header for each respondent so that it reflects that a "None" concept was asked in each task (though you didn't actually display a "None" concept in the questionnaire).

2. Add a new row of zeros to each choice task, reflecting the "None" concept.

3. For each respondent, scan the choice tasks and determine the largest volume of product ever "purchased" (the sum of allocations across concepts within a choice task). Call that volume max_volume (each respondent has a different value for max_volume). For each respondent, set the "None" alternative to receive zero allocation for that one choice task reflecting the highest max_volume.

4. For each respondent, set the allocation for the "None" concept equal to max_volume minus the volume "purchased" in each other task.

5. Estimate individual-level part-worth utilities using CBC/HB.

6. Import the part-worth utilities into the SMRT market simulator. Merge a weighting variable (through SMRT's File | Merge Variables) for each respondent, equal to max_volume. Use max_volume as the weight in weighted simulations (select Weights... from the Scenario Specification dialog). Include the "None" concept in market simulations (set the "None" weight to 1.0 under the Advanced Settings within the Scenario Specification dialog.) The resulting shares of preference are shares of volume. The share allocated to the "None" concept reflects potential sales volume not captured by the products in this particular simulation scenario.

Notes and Cautions:

One should take care that the use of max_volume as a weight does not result in a few respondents exerting too much weight on the final population estimates. Furthermore, relying on max_volume as the definitive potential volume "purchased" for each respondent and the relative weight against which the "None" parameter is scaled places a great deal of reliance on this one data point from a single choice task. If a respondent accidentally records an erroneous and unrealistically high volume for a single task, it can greatly affect the scaling of this respondent's data with respect to the "None" parameter and this respondent's influence upon the simulated shares of preference.

CBC/HB normalizes the allocations within each task to sum to a constant value. For this reason, one should reapply the max_volume weight in weighted simulations.

* We have written such a program to perform steps 1-4 above, and it is available for free download from http://www.sawtoothsoftware.com/products/ssiweb/tools.