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The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Purpose – This chapter compares bioenergy policy developments in Germany and Denmark to better understand the responses of EU country policy regimes to global shocks; to examine potentially emerging new trends of productivist policy models; and to explore potential land use conflicts in the context of a multifunctional EU agricultural policy.

Design/methodology/approach – The chapter reviews the bioenergy policy development pathways taken by Germany and Denmark, highlighting key consequences for agricultural land use and rural development. Findings from both case studies are then compared in summary tables, followed by a discussion of the possible emergence of productivist policy approaches in the bioenergy sector in these countries.

Findings – The bioenergy policies pursued by both countries differ in key respects and yet have had the same result-an increase in the productivist orientation of agriculture, legitimised by the environmental concerns of bioenergy policy. The Danish and German case studies also demonstrate that the particular pathways taken to establish bioenergy policies in each country have been strongly influenced by local political, farming and technological dynamics.

Originality/value – This chapter presents a telling case of what Burton and Wilson (this volume) call “repositioned productivism”, where productivist approaches benefit from environmental or multifunctional policy rationale to continue at the farm level.

This study aims to explore Taiwan's potential for bioenergy production using feedstocks grown on set-aside land and discusses the consequent effects on Taiwan's energy security plus benefits and greenhouse gas (GHG) emission.

The Modified Taiwan Agricultural Sector Model (Modified TASM), based on price endogenous mathematical programming, was used to simulate different agricultural policies related to bioenergy production. To do this simulation, the TASM model was extended to include additional bioenergy production possibilities and GHG accounting.

Taiwan's bioenergy production portfolio depends on prices of ethanol, electricity and GHG. When GHG prices go up, ethanol production decreases and electricity production increases because of the relatively stronger GHG offset power of biopower.

Taiwan is interested in producing bioenergy but only limited information is available. This study provides the information on potential bioethanol and bioelectricity production from various energy crops, GHG emission offset from bioenergy, and regional energy security.

Agricultural food residues (agro-residues) receive low economic returns and experience disposal problems. The food production and processing is often not configured to supply agro-residues for production of bioenergy needed in food processing. The feasibility of utilising agro-residues through advances in postharvest technology for sustainable bioenergy conversion is reviewed. The paper aims to discuss this issue.

Agro-residues from maize, sugarcane and potatoes in five African countries were assessed from secondary data to identify suitable conversion technologies, energy products and configurations of bioenergy plants for applications in postharvest food processing.

Strategic alignment of postharvest technology to bioenergy production systems is vital to advancing both food production and bioenergy that benefit rural communities in Africa. High economic returns are possible when the bioenergy plants are either annexure to existing agro-processing operations or operate as a biorefinery.

Assessment of energy self-sufficiency of food production and processing systems is required.

Agro-residues for bioenergy production require investments in infrastructure for storage, transportation and processing of the residues, and development of new risk management techniques.

The rural communities will be energy secure resulting in food security through reduced postharvest losses and increased agricultural productivity.

The study stimulates innovative thinking in establishing sustainable bioenergy systems for food processes.

The purpose of this paper is to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value‐added chain of biomass and bioenergy and comparing them accordingly.

A tri‐dimensional approach (sustainability issues; technical biomass conversion routes; physical trade flows) was developed for testing the coverage of various sustainability dimensions in different phases of the value‐added chain with the chosen certification schemes and sustainability principles.

Using the tri‐dimensional approach, a comparison of the chosen schemes and principles demonstrated that the application of existing schemes and the development of new ones have placed a major emphasis on the primary production of biomass. Economic and social dimensions related to biofuels and bioenergy processing and trade were either emphasised less or they were covered inadequately. In view of this, the schemes sometimes seem to ignore that the utilisation of renewable energy as such guarantee no positive or neutral climate impact and may not be economically sustainable, especially when bioenergy can often be more expensive than energy generated from fossil energy sources.

The analysis showed that the tri‐dimensional model is an applicable framework that could facilitate policy makers to formulate policies that comprehensively take into consideration the various sustainability dimensions throughout the entire value‐added chain, now and in the future. It can be applied to the future outlining and completion of certification schemes and sustainability principles for biomass and bioenergy, as well as in the testing of their applicability in the implementation.

Bioenergy is a key component of climate change mitigation strategies aiming at low stabilization. Its versatility and capacity to generate negative emissions when combined with carbon capture and storage add degrees of freedom to the timing of emission reductions. This paper aims to explore the robustness of a bioenergy-based mitigation strategy by addressing several dimensions of uncertainty on biomass potential, bioenergy use and induced land use change emissions.

Different mitigation scenarios were explored by two different energy-economy optimization models coupled to the same land use model, which provides a common basis for the second generation bioenergy dynamics in the two energy-economy models.

Using bioenergy is found to be a robust mitigation strategy as demonstrated by high biomass shares in primary energy demand in both models and in all mitigation scenarios.

A variety of possible storylines about future uses of biomass exist. The comparison of the technology choices preferred by the applied models helps understand how future emission reductions can be achieved under alternative storylines.

The presented comparison-based assessment goes beyond other comparison studies because both energy-economy models are coupled to the same land use model.

This research explores the effect of bioenergy use on carbon dioxide releases in 28 European Union (EU-28) affiliated members starting from 1990 to 2018.

Applying panels' fixed effect (FE) estimator and random effect (RE) estimator, the regressed findings are highly validated as they were robust by panel least square dummy variable corrected (LSDVC) and pooled ordinary least square (Pooled OLS) estimators.

The findings claimed that carbon dioxide releases decrease with an incline in bioenergy use and trade openness. On the other hand, fossil-fuel and economic growth indicators mounting carbon dioxide releases. The result implies that carbon dioxide releases in EU-28 region members can be mitigated significantly by mounting the quantity bioenergy use in generation channel. This will mostly participate in combating environmental pollution.

The study suggests for EU28 region members to enhance the portion of bioenergy in their fuel access to decrease emitted carbon dioxide. Governors in EU28 members should mainly encourage bioenergy expansion to raise its security and availability. The politicians of the EU28 members must assert on efficacy and productivity of bioenergy production to achieve energy accessibility and decrease dependency on conventional energy.

This research applies the recently improved model, the panel data analysis approach, which considered for the first-class impacts of estimators on the dependent variable and deals with the several problems of the common Pooled OLS estimator's manner and performance. Finally, this research contributes to the previous studies on ecological sustainability by examining the presence correlation among carbon dioxide emissions, bioenergy sustainability, trade openness, fossil fuel and gross domestic product in the EU28 region. Hence, it proves our research novelty, originality and contribution to the body of knowledge.

The purpose of this paper is to identify the most significant uncertainties for bioenergy applications, in order to identify factors determining the success of introducing bioenergy into the current energy system.

A framework is built for identifying the most significant uncertainties based on studies exploring the positive potentials as well as possible negative effects of bioenergy. The framework is applied to explore uncertainties of bioenergy-based transport fuels and heat and power generation through two real life case studies.

The results indicate that the most significant uncertainties are environmental and economic. Bioenergy applications have potential to mitigate climate change, but also come with negative environmental effects. Case studies show that operations in developing nations contain higher political/institutional and social uncertainty than those in developed countries, due to weaker regulations and enforcement.

The paper is part of an on-going research project. Results will be verified with stakeholder interviews and analysis. Further institutional analysis of the country settings is necessary.

The use of a feedstock with high environmental, social and institutional uncertainties will lower public acceptance. Acting in accordance to the law is not sufficient to ensure sustainability and additional, voluntary measures should be undertaken.

The paper identifies the most significant uncertainties for bioenergy. Uncertainties from social acceptance and institutional settings are higher in developing countries and acceptability requires more than following regulations.

The purpose of this study is to evaluate the profit efficiency of bioenergy industry and its determinants in EU28 region roadmaps for the transition towards energy efficiency which is increasingly perceived by stakeholders, researchers and the public as a pathway to bring dependency on fossil resources to a significant reduction. Many studies overlooked the importance of profit efficiency as a factor for bioenergy industry business improvement. More so, external environmental variables can play a key role in achieving profit efficiency in the industry.

This paper seeks to answer the questions on the following: (1) the profit efficiency level using the data envelopment analysis (DEA) approach in the EU28 region during the period between 1990 and 2018; and (2) to explore the impacts of external environmental variables on the profit efficiency level using panel regression model in the EU28 region during the period between 1990 and 2018.

Results revealed that gross domestic product, size of biomass and investment are essential for the development of the bioenergy industry and positively influence on profit efficiency level. The increase in temperature change decreased the profit efficiency level during 1990–2018.

For those profit-inefficient bioenergy industries in countries such as Cyprus and Ireland, participation in innovative programs, expanding a knowledge-based economic system and implementation of support policy for bioenergy technologies, by investing in biomass sources that are suitable for their respective renewable energy development will enhance specialization, resource efficiency and improved profitability can be expected in future.

Unlike other previous studies, this study investigated the profit efficiency by applying the DEA statistical method. Moreover, the authors have applied a second regression analysis to estimate the impacts of macroeconomic and microeconomic variables on the profit efficiency level. This study has focused on the EU28 region, including both developed and developing countries, to compare the level of profit efficiency levels in the selected sample. The authors have applied data panel analysis for the period from 1990 to 2018. No previous study has applied the methods, samples and periods as those used in this study. Therefore, this study contributes significantly to the bioenergy industry specifically and the renewable energy industry in general and to the associated extant research.

Bioenergy from agriculture is considered to be a way to reduce GHG emissions and thus global warming and climate change. Bioenergy also presents other environmental externalities as impacts on air, soil and water quality, biodiversity, etc. In addition, bioenergy presents socio‐economic externalities as impacts on human health, social wellbeing, local prosperity, etc. These externalities must be assessed in order to enhance responsible politics' choice of the best bioenergy routes to support through incentives as subsidies or quotas. The aim of this research project is to enhance the political choice of bioenergy routes to support through incentives as subsidies or quotas.

From the literature review and assessment of certification initiatives, the paper has derived a list of environmental externalities, i.e. environmental sustainability criteria, and a list of socio‐economic externalities, i.e. socio‐economic sustainability criteria, to be taken into account in bioenergy routes evaluation. Environmental and socio‐economic externalities selected are interlinked and cannot be assessed in isolation. They are thus articulated into a qualitative model, which defines links between externalities and characterizes them into positive or negative correlations, and indeterminate relations.

From this model, it appears that many interactions between environmental externalities or between socio‐economic externalities from bioenergy are not straightforward. Many of them are time or space‐dependent. Agricultural practices vary from one region to another; indirect effects are far from being understood and assessed correctly, long‐term effects of climate change are still unknown, etc. Moreover, environmental externalities should be articulated together with socio‐economic externalities.

On the basis of the consolidated qualitative model, a quantitative model will be built. It will enable the monetization of externalities and their introduction in a political decision‐making tool. This tool will help politics to compare different bioenergy routes and choose the best according to their sustainability.

The quantitative model should allow the monetization of externalities and their introduction in a political decision‐making tool. This instrument will help politics to take into account sustainability in their comparison of different bioenergy routes when they want to promote: employment, GHG emissions reduction, biodiversity conservation, etc.