Are we really trying to maximize response rates?

I sometimes speculate that we may be in a situation where the following is true:

Our goal is to maximize response rate
We research methods to do this
We design surveys based on this

Of course, the real world is never so "pure." I'm sure there must be departures from this all the time. Still, I wonder what the consequences of maximizing (or minimizing) something else would be. Could research on increasing response still be useful under a new guiding indicator?

I think that in order for older research to be useful under a new guiding indicator, the information about response has to be linked to some kind of subgroups in the sample. Indicators other than the response rate would place different values on each case (the response rate places the same value on each case). So for methods to be useful in a new world governed by some other indicator, those methods would have to useful for targeting some cases. On the simplest level, we don't want the average effect on response of incentives, for example, we want the effect of incentives on the subgroup that we need to get because it will help us balance response (as an example).

Sometimes we have this in existing research, sometimes we don't. I'm thinking that it might be there a fair amount since, in fact, we aren't pure maximizers of response rates.

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