Abstract
ABSTRACT This paper investigates which of the core types of innovation can be best predicted based on ’firms’ website data. In particular, we focus on four distinct key standard types of innovations in firms: product, process, organisational, and marketing innovation. Web mining of textual data on the websites of firms from Estonia, combined with the application of artificial intelligence (AI) methods, turned out to be a suitable approach to predict firm-level innovation indicators. The key novel addition to the existing literature is the finding that web mining is more applicable to predicting marketing innovation than the other three core types of innovation. As AI-based models are often black-box in nature, for transparency, we use an explainable AI approach (SHAP - SHapley Additive exPlanations), where we look at the most important words predicting a particular type of innovation. Our models confirm that the marketing innovation indicator from survey data was clearly related to marketing-related terms on the ’firms’ websites. In contrast, the results on the relevant words on websites for other innovation indicators were much less clear. Our analysis concludes that the effectiveness of web-scraping and web-text-based AI approaches in predicting cost-effective, granular and timely firm-level innovation indicators varies according to the type of innovation considered.
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