Measuring technological similarity in the wine industry

Abstract Technological similarity enables wine operators to share best practices, benchmark against industry standards, and identify new areas of innovation. Despite this, measuring similarity is notoriously challenging. In this paper, I use sentence embeddings on wine patent data to show how similarity compares across different models. I validate the results both internally and externally, showing large discrepancies in annual trends. The results underscore the importance of selecting suitable models for market assessment, providing a valuable primer for both wine operators and technologists.