From fashion to sustainability

Sustainability issues are increasingly influencing firms’ decision making, leading to the creation of new business models for finding solutions to environmental and societal challenges. is work aims to explore what is the role played by industrial districts in firms’ orientation towards sustainability. It implements a Propensity Score Matching technique on a novel datatabase with information on 1300 Italian fashion firms. eir sustainability orientation is measured using the Quantitas Intelligent Business Analyzer (QIBA), an original Natural Language Processing-based data mining technique, which allows scraping firms' websites and analyzing their content adopting a Term Frequency–Inverse Document Frequency weighting scheme. Findings suggest the existence of a sustainability-driven industrial district effect, i.e. a positive association between the sustainability orientation of fashion firms and their localization in industrial districts.