An ethnographic approach to communication in migrant businesses in Vienna: The role of language, culture and communication in businesses owned by migrants from the Balkans
Using the example of migrant economies from the gastronomy sector run by people of Balkan descent, this PhD thesis aims to investigate the interrelationship between language, home culture, host culture and business success. The term “migrant economies” refers here to businesses in which migrants have identified, created, and exploited economic opportunities to start a business in the host country (Dheer 2018, 558).
The aim is to examine the extent to which language is used as an opportunity to start a business and to explore how language and/or culture is commodified. In which way do the entrepreneurs construct their identity as migrants and entrepreneurs in their narratives? How do they position themselves within the host society and their community? To what extent do the entrepreneurs retain the linguistic and cultural practices from their home country or incorporate the practices of the host country into their business and work? How do these cultural and linguistic practices affect the spaces they create in their shops for themselves and for customers with similar backgrounds?
To answer these questions, a qualitative ethnographic approach will be adopted. The data will be collected through semi-structured narrative interviews and participant observation. For the analysis of the interviews, sociolinguistic narrative analysis will be applied with a special focus on positioning theories and the construction of spaces through interaction. The semiotic landscapes in the shops and their surroundings will also be examined.
The contribution of this thesis lies in investigating migrant businesses in Austria, more specifically in Vienna, as there are few publications on this topic at the current stage of research. The aim is to highlight the relevance of the linguistic and cultural elements for the success of migrant businesses.
Dissertation Lejla Atagan