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The bioeconomy represents a transformative approach to economic development and sustainability by harnessing biological resources and knowledge to produce goods, services, and energy while reducing dependence on non-renewable resources. In order to understand and support the bioeconomy, scholars and policymakers rely on an accurate measurement and monitoring of biobased economic activities. However, existing statistical frameworks and industry classifications often fall short in capturing the unique characteristics and complexities of the bioeconomy. This article addresses this challenge by developing a methodological approach for comprehensive measurement and mapping of biobased economic activities. We build a novel data set of bioeconomy firms in Germany using web-mining and machine learning techniques. This data set enables detailed analysis of biobased economic activities, providing valuable insights into the spatial organization of the bioeconomy. The paper demonstrates the applicability of the data set by testing several stylized facts about the bioeconomy. Our research contributes to a better understanding of the bioeconomy's regional impacts and offers a valuable resource for policymakers and researchers interested in understanding the geography of biobased economic activities. We make an aggregated version of the data set freely available online.
Kriesch et al. (Mon,) studied this question.