But still if research think to use convenience sampling, some rules are given below
From Hair et al. 2014 book
PLS-SEM has higher levels of statistical power in situations with complex model structures or smaller sample sizes.
Unfortunately, some researchers believe that sample size considerations do not play a role in the application of PLS-SEM. This idea is
fstered by the often-cited 10 times rule (Barclay, Higgins, & Thompson,
the sample size should be equal to the larger of
1. 10 times the largest number of formative indicators used to
measure a single construct, or
2. 10 times the largest number of structural paths directed at a
particular construct in the structural model.
This rule of thumb is equivalent to saying that the minimum
sample size should be 10 times the maximum number of arrowheads
pointing at a latent variable anywhere in the PLS path model. While
the 10 times rule offers a rough guideline for minimum sample size
requirements, PLS-SEM-like any statistical technique-requires
researchers to consider the sample size against the background of the
model and data characteristics (Hair, Ringle, & Sarstedt, 2011).
Specifically, the required sample size should be determined by means
of power analyses based on the part of the model with the largest
number of predictors.