Design of Experiments is an effective approach for answering questions like the one you’ve described.
Use DOE when more than one input factor is suspected of influencing an output. For example, it may be desirable to understand the effect of temperature and pressure on the strength of a glue bond.
DOE can also be used to confirm suspected input/output relationships and to develop a predictive equation suitable for performing what-if analysis.
(from ASQ.org)
In your case, you have an output variable (willingness to do job) and three input variables (x, y, z). You’ll want to test the relative impact of x, y, or z and whether combinations of x, y, and z matter. For example, x may not matter on its own, but xy might matter a lot. In Design of Experiments (DOE) this is called a three factor design.
It is also important to understand what levels of x, y, and z need to be tested. When determining levels, it will matter if x, y, and z are continuous or discrete variables. Salary is an example of a continuous variable since it could be any salary on the number line, bounded by a low value ($20,000) and a high value ($90,000). Project might be a discrete variable, since your company has a limited number of projects and an employee must be on one of them (project A, B, or C).
Once you know how many factors you’re testing (3) and how many levels there are for each factor you’ll be able to use a template to plan an experiment. In the experiment, you’d offer people jobs with different values for x, y, and z. Based on which jobs people pick, you can infer how much impact x, y, z, and their interactions have on job offer acceptance.
DOE can be a little complicated when there are lots of factors. But in your situation with 3 factors it is pretty easy to use. In college we used the text book Response Surface Methodology.
Note: You may already have a good enough answer. It sounds like you’ve done a lot of research already. Before doing any more research, it’s worth thinking about the expected value of perfect information. Basically ask yourself two questions and stop doing more research if 2 is greater than 1.
- How much could we save if we get more information?
- How much will it cost to get more information?