  Background: Dedicated model transformation languages are claimed to provide
many benefits over the use of general purpose languages for developing model
transformations. However, the actual advantages and disadvantages associated
with the use of model transformation languages are poorly understood
empirically. There is little knowledge over what advantages and disadvantages
hold in which cases and where they originate from. In a prior interview study,
we elicited expert opinions on what advantages result from what factors
surrounding model transformation languages as well as a number of moderating
factors that moderate the influence.
  Objective: We aim to quantitatively asses the interview results to confirm or
reject the influences and moderation effects posed by different factors and to
gain insights into how valuable different factors are to the discussion.
  Method: We gather data on the factors and quality attributes using an online
survey. To analyse the data and examine the hypothesised influences and
moderations we use universal structure modelling based on a structural equation
model. Universal structure modelling will produce significance values and path
coefficients for each hypothesised and modelled interdependence between factors
and quality attributes that can be used to confirm or reject correlation and to
weigh the strength of influence present.
  Limitations: Due to the complexity and abstractness of the concepts under
investigation, a measurement via reflective or formative indicators is not
possible. Instead participants are queried about their assessment of concepts
through a single item question. We further assume that positive and negative
effects of a feature are more prominent if the feature is used more frequently.
