Translation and localization of food menus on mobile delivery apps in the United Arab Emirates: a multimodal and reception study

This study investigates the quality of menu translation and localization on food delivery apps and its impact on the user experience. A corpus of food menus was collected from the Talabat app and analyzed from a multimodal perspective adopting Li's (2019) framework and using NVivo qualitative data analysis software. A coding framework was created in NVivo to systematically identify translation and localization strategies, and issues related to images of food items. Additionally, an online survey targeting app users was utilized to gather data on preferences and the impact of menu translation and localization on user experience, satisfaction, and purchasing decisions. The analysis revealed that the meaning of food menus involves several layers, including semiotic and textual means, which necessitate approaching their translation from a multimodal perspective. Dish names were mostly transliterated into English and accompanied by an acceptable and clear description of dish information in English. The survey results also revealed that translation quality has a great role in shaping user experience, satisfaction, trust, and expenditure. The findings of this study will be of value to translators, translation trainers, restaurant owners, and food delivery app developers.