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With increasing world population and an unsettling resource scarcity in the back, sustainble consumption has moved to the foreground of political, economical and social discussions. One major school-of-thought is Circular Economy (CE), an approach summarizing various sustainable consumption activites under one roof. However, quantitative studies on the consumer are rare, yet crucial for a transfer from linear to circular consumption. This dissertation adds to literature by providing pioneer insights into consumer behavior in CE as an overarching concept, instead limiting research on singular subconcepts. Namely, four consumer activities are studied: recycling, upcycling, renting and sharing. In order to identify relevant insights for both academics and practitioners in CE, the research question ("what drives participation in CE?") is broken down into sub-hypotheses, which are addressed by three empirical studies. Using the SOR-Model (adaption Belk 1975) as overarching logic, the three studies deal with (1) the consumer (and their motivation) and situational stimuli (both (2) offline and (3) online). Respectively, three data sets are consulted to assess the sub-hypotheses and to identify overarching insights on how to accelerate consumer participation in CE, The research methodology employed ranges from a structured equation model (SEM), a random allocation field experiment during Fashion Week in Berlin to a discrete-choice model with best-worst scaling. The dissertation succeeds in revealing that (1) different activities in CE can be summarized in one latent variable, proving CE as a wholesome concept in consumer-related activities; that (2) Trust has a leveraging effect on participation in CE activities. Further, Trust can be enhanced offline via face-to-face interaction and online via third-party online attributes.; and that (3) experience in CE activities affects perception of online attributes, implying the need for adapted measures when dealing with CE-unexperienced consumers as compared to consumers with prior experience in CE activities.
The contribution of the EU bioeconomy to sustainable development depends on how it is implemented. A high innovation potential is accompanied by considerable risks, in particular regarding the exacerbation of global land use conflicts. This article argues that a systemic monitoring system capable of connecting human-environment interactions and multiple scales of analysis in a dynamic way is needed to ensure that the EU bioeconomy transition meets overarching goals, like the Sustainable Development Goals. The monitoring should be centered around a dashboard of key indicators and targets covering environmental, economic, and social aspects of the bioeconomy. With a focus on the land dimension, this article examines the strengths and weakness of different economic, environmental and integrated models and methods for monitoring and forecasting the development of the EU bioeconomy. The state of research on key indicators and targets, as well as research needs to integrate these aspects into existing modeling approaches, are assessed. The article concludes with key criteria for a systemic bioeconomy monitoring system.