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In this paper, we investigate the promises that are employed within and around clusters that were formed in the evolving bioeconomy: bioclusters for short. Our paper aims to provide a conceptual clarification of the biocluster concept. To that effect, we employ the prism of sociotechnical imaginaries. We argue that both industrial clusters and the bioeconomy constitute separate, but partly overlapping sociotechnical imaginaries that shape stakeholder attitudes towards bioclusters. We applied a Q-methodology study in two bioeconomy clusters, one in Germany and one in The Netherlands, to investigate the resonance of different imaginaries in the cluster regions. Five distinct narratives, combining specific elements of cluster and bioeconomy imaginaries, are shared by different stakeholder groups. We revealed bioeconomy imaginaries at large to be far more contested than different cluster imaginaries. The latter mobilise overwhelmingly positive associations across diverse stakeholder groups. From this perspective, the popularity of biocluster promotional policies can be explained as they support some of the contested elements of bioeconomy imaginaries in gaining traction.

Diese Dissertation beantwortet verschiedene politikrelevante ökonomische Fragen in den Bereichen Handelspolitik, Geldpolitik, sowie Rohstoffmärkte und Energieökonomik mit Hilfe von strukturellen Vektorautoregressionsmodellen (SVAR). SVARs stellen eine effektive Möglichkeit dar, die Beziehungen zwischen verschiedenen makroökonomischen und/oder Finanzmarkt-Variablen zu modellieren und werden verwendet, um die dynamischen kausalen Effekte von ökonomischen Schocks zu schätzen. Für jede ökonomische Fragestellung wird eine Identifikationsstrategie angewandt, die auf die betrachteten Daten und ihre statistischen Eigenschaften sowie die zugrundeliegenden Annahmen über ökonomische Mechanismen zwischen den betrachteten Zeitreihen zugeschnitten ist. Im Einzelnen besteht diese Dissertation aus vier Kapiteln. In den ersten beiden Kapiteln werden die Auswirkungen von Handelspolitik auf Finanzmärkte und auf die Makroökonomie geschätzt. Das dritte Kapitel liefert einen methodischen Beitrag zur SVAR-Literatur, der in einer Anwendung zu den Effekten von Geldpolitik dargestellt wird. Das letzte Kapitel verlässt die Felder der Handels- und Geldpolitik und wendet sich Rohstoffmärkten und der Energiewirtschaft zu, stützt sich dabei aber ebenfalls auf Zeitreihenmethoden. Es analysiert die Rolle von Metallen in der Energiewende. This dissertation answers various policy relevant economic questions in the fields of trade policy, monetary policy, and commodity markets and energy economics using structural vector autoregression (SVAR) models. SVARs constitute a parsimonious way to model the relations between different macroeconomic and/or financial variables and they are used to estimate the dynamic causal effects of economic shocks. For each economic question, this dissertation applies an identification strategy that is tailored to the relevant data and its statistical properties as well as the underlying assumptions about economic mechanisms among the regarded time series. Specifically, this dissertation consists of four chapters. The first two chapters estimate the effects of trade policy on financial markets and on the macroeconomy. The third chapter makes a methodological contribution to the SVAR literature in an application to monetary policy shocks. The final chapter moves away from trade and monetary policy to commodity markets and energy economics but also relies on time series methods. It analyzes the role of metals for the clean energy transition.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

Abstract This article examines and conceptualizes the implications of the adoption of circular economy (CE) business models on operations management (OM) decision-making processes, in the areas of product design, production planning and control, and logistics/supply chains. A systematic literature review was conducted in order to identify and examine the following key areas: (1) the new demands faced by OM decision-making regarding changes in capability, work procedures, intra- and inter-organizational relationships and technologies; (2) the specific changes OM decision-making must make in order to support CE business models (based on the ReSOLVE framework); and (3) guidelines which will help designers and operations and logistics/supply chain managers develop the necessary skills to meet society and the global market's emerging demands. The findings of this research will allow operations managers to foresee the unfolding needs for capacity building in CE, and scholars can build on the results of this article to develop new research themes. Furthermore, this is the first article to describe the ways in which OM knowledge can support the transition towards the circular economy based on the perspective of dynamic capabilities.

Highlights •Biomass resource constraints impact the effectiveness of bioeconomy policies. •Bioeconomy policies may have an important impact on the sector structure in the long run, but the sector growth remains ultimately constrained by the availability of inputs. •Solutions to reduce the biomass constraint have to be included in innovation policy for the biobased economy.

Background. Laws that enable a circular economy (CE) are being enacted globally, but reliable standardized and digitized CE data about products is scarce, and many CE platforms have differing exclusive formats. In response to these challenges, the Ministry of The Economy of Luxembourg launched the Circularity Dataset Standardization Initiative to develop a globalized open-source industry standard to allow the exchange of standardized data throughout the supply cycle, based on these objectives: (a) Provide basic product circularity data about products. (b) Improve circularity data sharing efficiency. (c) Encourage improved product circularity performance. A policy objective was to have the International Organization for Standardization (ISO) voted to create a working group. Methods. A state-of-play analysis was performed concurrently with consultations with industry, auditors, data experts, and data aggregation platforms. Results. Problem statements were generated. Based on those, a solution called Product Circularity Data Sheet (PCDS) was formulated. A proof of concept (POC) template and guidance were developed and piloted with manufacturers and platforms, thus fulfilling objective (a). For objective (b), IT ecosystem requirements were developed, and aspects are being piloted in third party aggregation platforms. Objective (c) awaits implementation of the IT ecosystem. The policy objective related to the ISO was met. Conclusions and future research. In order to fully test the PCDS, it is necessary to: conduct more pilots, define governance, and establish auditing and authentication procedures.

Technological change has altered labor market demands within well-developed societies implying global competition for skilled labor and, as a consequence, new forms of labor migration. So far, patterns of this labor migration have been underexplored. Thus, the article analyzes characteristics, geographies and possible underlying drivers of workers migrating from Germany as an exemplary case for a well-developed country. Relying on probability-based and unique data, our findings reveal that, besides demand for people with higher levels of education, performing specific occupational tasks is also in demand in the global competition for talent. Hence, Germans in jobs with a high proportion of analytical non-routine tasks are more likely to emigrate than those with predominantly manual routine tasks. Moreover, the results show that global discrepancies concerning the technological development between the country of origin and the country to which they emigrate are a crucial contextual driver attracting this specifically demanded work force. Workers mainly performing analytical non-routine tasks within their job tend to move to countries which are technologically more developed than Germany while individuals performing jobs with a high share of non-routine manual or interactive tasks tend to emigrate to countries that are less technologically developed than Germany.

Climate change is worsening the number, frequency and duration of natural hazards across the globe, making disaster risk reduction and resilience building among the most pressing challenges ahead. According to UN-Habitat, informal settlements are where the impacts of climate change are the most acute in urban areas and strengthening resilience in these neighbourhoods represents a very complex yet urgent challenge. Today, urban areas are home to 56 per cent of the world’s population and this figure is projected to increase to 60 per cent by 2030 and 68 per cent by 2050, with 90 per cent of the growth by 2050 expected to occur in less developed economies. In these countries, population growth and displacement (including climate-driven migrations) will lead to rapid and unplanned urbanisation forcing a growing number of people into informal settlements. Currently, one billion people live in informal settlements, mostly in Asia, Sub-Saharan Africa and Latin America and this figure is expected to grow to 3 billion in 2050. Horizon 2020 MSCA-RISE, Grant Agreement #873119

In recent years, the literature in the field of general equilibrium modeling has increased. For long-term energy projections, general equilibrium models are more adequate than standard econometrics in evaluating alternative economic policies in a theoretically consistent framework. The well-known structure and economic mechanism of those models makes it easier to analyze structural changes of prices and quantities demanded or supplied for a given data set of an economy, national income accounts figures, and trade balance effects. The dynamic formulation of these models via investment decisions and capital formation also enables an intertemporal interpretation of structural adjustment and growth processes.