• Energy Research
• economics and business close
• 13. Climate action close
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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.

This paper analyzes the effect of environmental policies on the direction of energy innovation across countries over the period 1990-2012. Our novelty is to use threshold regression models to allow for discontinuities in policy effectiveness depending on a country's relative competencies in renewable and fossil fuel technologies. We show that the dynamic incentives of environmental policies become effective just above the median level of relative competencies. In this critical second regime, market-based policies are moderately effective in promoting renewable innovation, while command-and-control policies depress fossil based innovation. Finally, market-based policies are more effective to consolidate a green comparative advantage in the last regime. We illustrate how our approach can be used for policy design in laggard countries.

Presently, an increasing human population, customer consumption, and global market competition result in the reduction of natural resources and growing environmental damage. Therefore, the current practice in the use of resources is not sustainable. The production companies have to focus not only on cost-effective and profitable operation, but at the same time environmentally friendly and sustainable production in order to increase competitiveness. New innovative technologies are required, improving the efficiency of the processes and the optimization of global supply chains (GSC) in order to establish sustainability in environmental, social, and economic aspects. The aim of the study is the GSCs’ optimization, which means forming the optimal combination of the chain members (suppliers, final assemblers, service providers) to achieve cost-effective, time-effective, and sustainable operation. This study introduces an elaborated single- and multi-objective optimization method, including the objective functions (cost, lead time) and design constraints (production and service capacities; volume of inventories; flexibility and sustainability of the chain members). Based on the elaborated method, software has been developed for the optimization of sustainable GSCs. The significance and novelty of the developed method and software is that the chain members have been required to fulfill the sustainability design constraint built into the software. A real case study is introduced, for the optimal design of a sustainable GSC, to confirm that our developed optimization method and software can be applied effectively in practice for the optimization of both profitable and sustainable GSCs.

Abstract The sheer complexity of sustainability transitions makes it vital to develop simplifying conceptual frameworks. Starting from the contrast between the mainstream innovation-economics and systems-innovation/evolutionary literatures, this paper begins by summarising the “Three Domains” framework, which relates technology innovation and adoption choices to different domains of socio-economic decision-making, at successively larger scales of time and social structures. We note the high-level implications for policy mixes and illustrate the main themes through three electricity technology examples (lighting, fossil fuel generation, and low carbon power systems), and use these also to show that the relative importance of different policy pillars may differ substantially according to the technology and context. We then relate this to the “innovation chain” (another simplifying framework) approach to vertical innovation and show how this can help to explain radical differences in innovation intensities between different sectors. We then expand the innovation chain framework from technology to the multiple journeys required for successful innovation, ordered according to levels of decision-making and hence domains. We conclude by indicating how this can help identify key blockages in energy transformations, and potentially help to reconcile the classical innovation-economics with systems innovation/evolutionary perspectives, and explain their currently divergent policy recommendations.

The bioeconomy occupies the centre of the Green Deal, the EU’s plan to support transformative growth following the COVID-19 episode. However, parts of the EU, such as countries in Central and Eastern Europe (CEE) continue to lag behind in harnessing the potential held by the bioeconomy. This article argues that in CEE countries, where the primary and conventional bioeconomy sectors play a more important role, ‘early’ transition pathways such as improvements in productivity and practice- as well as commercialisation-oriented innovation (the do–use–interact model: DUI) are just as important as approaches based on (generally publicly supported) R&D, innovation adoption, and technology transfer (science–technology–innovation model: STI), typically associated with high-value bioindustrial applications. The argument is tested by conducting a survey of 352 experts in the region that gives an insight into the CEE macro-region’s assets with respect to deploying the bioeconomy’s potential and assessing the transition pathways relevant to the better performance of bioeconomy (primary, manufacturing, and other related) sectors. The results show the particular relevance of consolidating the primary and traditional sectors to support improvements in productivity based on the vertical and horizontal interaction typically associated with DUI, while the relevance of STI is mostly linked to advanced sectors, which are narrowly distributed across the region. The findings are relevant to policy given that the EU’s bioeconomy policy has thus far chiefly focused on STI support that better corresponds to the needs of countries at more advanced stages of developing the bioeconomy, but is less appropriate for the specific context and needs of CEE.

We conducted a labelled discrete choice experiment (DCE) to assess consumers’ preferences and willingness to pay (WTP) for fresh hens’ eggs produced via different production systems (caged, barn, free range, or organic). We estimated purchase intentions and WTP for different possible reductions (0%, 10%, 20%, and 30%) of greenhouse gas (GHG) emissions and water use in the egg production systems. Data were collected using an online open-ended questionnaire completed by a representative sample of 1045 Spanish egg consumers. The results of a random parameter logit (RPL) model showed heterogeneous preferences for different types of eggs with higher marginal utility and WTP for a production system ensuring higher animal welfare level, such as free-range eggs. However, consumers showed a lower preference for organic eggs at the actual market prices since they were unwilling to pay for this category of eggs. Moreover, there were positive marginal WTPs for reductions in GHG emissions and water use, but only for significant reductions (20% or 30%) with respect to the current situation. Potential buyers for free-range eggs were identified to be persons under 40 years old, persons with a monthly income of more than €1500, and persons who were pro-environment. Our findings provide producers, sellers and policy makers with useful information that may guide them in the development of successful communication and pricing strategies.

The optimal response to a potential productivity shock which becomes more imminent with global warming is to have carbon taxes to curb the risk of a calamity and to accumulate precautionary capital to facilitate smoothing of consumption. This paper investigates how differences between regions in terms of their vulnerability to climate change and their stage of development affect the cooperative and non-cooperative responses to this aspect of climate change. It is shown that the cooperative response to these stochastic tipping points requires converging carbon taxes for developing and developed regions. The non-cooperative response leads to a bit more precautionary saving and diverging carbon taxes. We illustrate the various outcomes with a simple stylized North–South model of the global economy.