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The greatest challenge in accelerating the realisation of a sustainable and competitive bioeconomy is to demonstrate that enshrining sustainability principles at the very heart of a production line can generate value and improve its overall system. Strategies for reducing emissions, pollutants, indirect land use change or soil depreciation are all perceived as costs or necessary inconveniences to comply with stringent, climate change-focused policy frameworks. System dynamics modelling and competitive priorities are tools that can accurately and intelligently expand on the cross-value chain approach, which integrates both technical and environmental performances, to address the issue of harmonising sustainability and technical operations as one overall dimension of performance. A stock-and-flow model is developed to map a full biofuel value chain and quantitatively and coherently integrate factors of emissions, carbon, land, production, and technology. As such, environmental and operational impacts of innovative practices are measured, and subsequently linked to a qualitative framework of competitive priorities, as defined by transparency, quality, innovation and flexibility. Sustainability and productivity functions are found to reinforce each other when all competitive priorities are optimised. Equally, the framework provides a clear understanding of trade-offs engendered by value chain interventions. Advantages and limitations in the accessibility, scope and transferability of the multi-pronged analytical approach are discussed.

The European Bioeconomy Strategy aims to facilitate the transition from a take–make–dispose fossil economy into one fostering circular bio‐based value chains linking sustainable land use with cutting‐edge products. Optimized designs, implementation and monitoring rely on continuous interactions between policymakers and modellers who run multiple scenarios for environmentally, economically and socially desirable futures. This paper leverages a multi‐layered framework that cross‐references 39 policies and 32 models to assess how they address the five principle objectives of the Bioeconomy Strategy in terms of accompanying sectors, value chains and multi‐dimensional indicators. The framework identifies gaps in bioeconomy knowledge both in policy and modelling. Overall, the analysis found little mention of the wide range of bio‐based products, technologies and processes, bio‐refineries, waste and land conservation. Bio‐based product policies can be simulated only in a limited number of models, compared, for example, to the wide range of modelling capacities that can model bioenergy. Additionally, in both policy and modelling realms, integration of market and biophysical drivers within the full scope of the value chain is scarce. Multidisciplinary studies combining multiple models perform best in this respect by integrating a more comprehensive range of relevant policies, bioeconomy drivers and indicators. Findings point to a more significant issue in policy‐modelling information exchange, and this paper discusses the challenges and opportunities for future improvements in this collaboration.

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