How to find mean relative differences?

I'm trying to describe mean differences between two populations $x_1$ and $x_2$, which are non-zero and positive. Their distribution is approximately beta with a positive skew. For example, with R:

# x1 <- round(rbeta(10, 1, 100)*1000, 1)
# x2 <- x1 + round(rbeta(10, 1, 100)*100, 1)
x1 <- c(1.7, 12.6, 22.3, 37.3, 15.2, 7.1, 31, 4.4, 9.5, 1.9)
x2 <- c(1.9, 14.2, 25.6, 39.2, 15.9, 8.7, 32.2, 7, 9.7, 1.9)

The two ways I can think of to determine the mean relative differences yield different numbers:

mean((x2 - x1)/x1)             # 0.1365628
(mean(x2) - mean(x1))/mean(x1) # 0.09300699

Why are they different, and which method is more descriptive of what I'm looking for? I.e., is $x_2$ 13.6% or 9.3% greater than $x_1$?

In the first formula, mean((x1 - x2)/x1) you are describing the differences between paired members of each group, (Wikipedia). Think of individuals before and after treatment.

In the second formula, (mean(x2) - mean(x1))/mean(x1), you are describing the differences between two, presumably independent, groups as a whole. Think of two independent samples.