The decarbonization of the transport sector is essential to meeting the goals of the Paris Agreement and the Net Zero Emissions strategies. In the automotive sector, this has led to increased momentum for sustainability and a recognition of the need to develop sustainable mobility alternatives. In the sector, there are certain players which appear to be far ahead in the transition, whereas there are others that are considered "laggards". We consider how the biggest global players in the automotive sector position sustainability and its subtopics on their agenda and the extent to which their actions match their positioning on sustainability. Moreover, the contrasting of actions with communication on sustainability will highlight discrepancies between sustainability performance and communication - e.g. are there certain players who are actually better at sustainability, but not good at communicating what they do?We adopt a multimethod approach, using a topic model which is complemented by a multi equation regression model. The topic model is applied to sustainability reports, using natural language processing to identify the focus of each manufacturer's sustainability strategies. The results from this model are then used to form the outcome variables in a seemingly unrelated regression model (SUR model). Further variables in the model are derived from quantitative data relating to e.g. proportion of zero-emission vehicles or indicators of sustainable production like energy consumption etc. This way, the model can compare the actual sustainability performance of the manufacturers to their communication. In combining both the topic model based on automated language processing techniques with a more traditional quantitative SUR model, this paper combines two different research approaches in a complementary way to address a complex research problem which has not been empirically investigated like this before