Definition of 'Price of anarchy' The classical definition of Price of anarchy is the ratio of decentralised optimal utility to the centralised optimal utility. This concept is used to quantify how inefficient is it when agents behave selfishly, in comparison with a situation where a central planner takes optimal actions.

My question: why cannot Price of anarchy be defined as the difference between the two solutions? In my setting, I have a number of log based functions in the utilities. For example, in a network setting defined on a graph $G$, the central planner's utility function is $U_s=f_s(G)+\sum_i \log(l_i)$ and the individual firm's utility is $U_i=f_i(G)+\log(l_i)$, where $l_i$ are loss terms for node $i$. Having a difference as PoA helps me eliminate idiosyncratic losses and I am left with $f_s(G)-\sum_i f_i(G)$, and I have a means to compare dependence of PoA on network structure.

I am greatly benefited by having a difference in place of ratio. Is it fine to define that way? Is there some other term for the difference?
As hinted in a comment, the problem with using the difference instead of the ratio, is that the difference is not free of the units of measurement while the ratio is. And in general we want to not depend on units of measurement (whatever it is that we measure).  

Although I am not familiar with the literature, I understand that here utility is a fully quantitative, "cardinal" concept. Moreover, there exists the network $G$ whose characteristics generate utility, and then there are the "idiosyncratic" losses, which is the component we want to get out of our sight.  Then why not define a $\text {PoA}$ net of idiosyncratic losses, especially since they appear not to depend on the decision making framework, and so they are the same both in the decentralized set up and in the centralized one?
I mean,

$$\text {nPoA} \equiv \frac {\sum_iU_i -\sum_i\log(l_i) }{U_s - \sum_i\log(l_i)}=\frac {\sum_if_i(G)}{f_s(G)}$$

This seems to me as a meaningful concept to reflect the network contribution to utility and how it changes under the two decision-making cases.