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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 accomplish several goals. First, it studies the relevance of the sports sector as part of the entertainment industry. Second, it identifies promising markets within the sports industry, paying special attention to the relative importance of soccer in the context of team-sport leagues. Finally, the paper helps entrepreneurs to recognized market opportunities in the sports industry by identifying the soccer clubs that were found to be low-risk global brands.

To evaluate the relevance of the entertainment and sports industries, both in the USA and EU-28, the authors rely on their respective contribution to the domestic product and to employment. Two procedures are proposed for establishing the status of global sport leagues: one is based on the annual revenues and the other on the degree of interest that the public shows for each professional sport league. (The latter is performed by comparing the intensity with which internet users search for contents related to each of the Top-10 sports leagues worldwide.) Finally, by estimating the fixed effects of a model in which sport performance is filtered out, we calculate the expected low-risk revenues that clubs generate due to their heterogeneous brand value.

This paper reaches some few relevant results. First, we find that the greater employment opportunities in the European sport industry are concentrated in the UK, Spain, France and Germany, which may orientate entrepreneurs to start projects in promising sport markets. Then, data on annual revenues is used to rank the main team-sport leagues worldwide: NFL, MLB, NBA, Premier League and NHL. Another rank is based on the degree of interest of fans (as captured by Google Trends) yields a different result, where the NFL, NBA and the UEFA Champions League are, respectively, at command. Besides, the paper also ranks clubs as valuable assets by identifying which of them are low-risk soccer brands. The empirical study provides insights to select business opportunities by targeting the less-risky clubs or leagues, by calculating the expected annual revenues of clubs regardless of their recent sports performances.

This paper is innovative in two ways. First, it develops an analysis based on Google Trends to establish the comparative status of team-sport leagues worldwide. Second, by adopting an original empirical approach, it identifies markets and brands to carry out low-risk entrepreneurial projects. The expected potential revenues derived from this procedure are not contingent to the risk due to poor sport achievements in a particular season. To our knowledge, researchers have not computed in the past such calculations as that we name here low-risk revenues.

The purpose of this paper is to measure and evaluate the efficiency of materials management in the European Union countries (EU-28) during the period of 2008–2017.

The study was conducted using the method of data envelopment analysis (DEA) and variables applied to determine the resource productivity indicator. Therefore, the components of domestic material consumption constituted inputs in the DEA method, while gross domestic product (GDP) was applied as an output.

The results of the analysis showed that the Netherlands, Luxembourg, Latvia and the UK are the efficiency leaders among all the member states of the European Union. One of the least efficient countries is Poland, which uses too much natural resources in the process of generating goods and services. However, this consumption is growing at a slower rate than the value of GDP, which is beneficial from the point of view of sustainable development. Poland, like other inefficient countries, should reduce its consumption of natural resources in line with the best international practices.

The obtained research results can be a valuable source of information for decision-makers, and contribute to the adoption of more effective policies in order to improve the relationship between materials consumption and economic growth.

The application of the DEA method for calculating the efficiency of materials management represents a new approach, and it is the first attempt of its kind in the European Union countries.

The aim of this paper is to examine the effects of the European Non-financial Reporting Directive (2014/95/EU) on firms' sustainability reporting practices, especially reporting quantity (i.e. availability of information) and quality (i.e. comparability and credibility).

To test the main hypotheses, the authors select 905 treated firms from the EU 28 + 2 countries for a difference-in-differences regression analysis of dependent variables from the Refinitiv ESG database.

The results suggest that the Directive influences sustainability reporting quantity and quality. Treated firms provide around 4 percentage points more sustainability information (i.e. availability) than propensity score matched control firms and are 19 percent more likely to receive external assurance (i.e. credibility). However, we also find that the Directive is not the decisive factor in the adoption of GRI guidelines (i.e. comparability).

The analysis is restricted to large listed firms and does not account for small, mid-sized and private firms. Further, cross-cultural differences which influence sustainability reporting are controlled for but not investigated in detail. The authors derive several suggestions for future research related to the NFR Directive and its revision.

The authors’ findings have practical implications for the future development of sustainability reporting in the EU and for other regulators considering the adoption of sustainability reporting.

This study is the first to provide evidence on the NFR Directive's reporting effects across multiple countries. It adds to the growing literature on the consequences of mandatory sustainability reporting. Additionally, this paper introduces a novel measurement approach sustainability information quantity that could benefit researchers.

This chapter models industrial, tech, and financial cooperation between Russia and the countries of the Asia-Pacific region. We use several complex methods of economic and mathematical modeling to analyze specific features of such cooperation and determine critical factors in industrial, technological, and financial development. The preferable choice for the Asia-Pacific region is cooperation with Russia, which is ready for an increase in imports of industrial and high-tech products as well as joint industrial innovational entrepreneurship. Investments would lead to synergetic effects, ensuring simultaneous industrial, technological, and financial development.

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.

The purpose of this paper is to provide a measure of competitiveness of the Spanish autonomous communities from a multidimensional and dynamic perspective for the period 2008-2016.

This paper adopts a broad definition of competitiveness based on five key environments (productive capital, human capital, social and institutional capital, infrastructure and knowledge) and comprising 53 indicators. The method used to construct the competitiveness index is based on the P-distance proposed by Pena Trapero (1979), which objectively assigns weights to the indicators. There is an important advantage in the methodological proposal of this study, as it allows analyzing the behavior of partial and aggregated indicators from a dynamic perspective, taking the same value as a reference for the entire period. Therefore, not only a classification obtained for each year but also the variation that occurs in terms of the reference period can be analyzed.

The classification of the autonomous communities is established using common intervals based on the results obtained for the whole period, i.e. 2008-2016. The data point to the unequal situations of the autonomous communities. The results also reveal that the evolution of the regional competitiveness synthetic index is clearly cyclical and the drop recorded in the recessive period is less pronounced than the increase recorded in the growth phase.

The main innovation of the competitiveness index presented here lies in its allowing comparisons over time.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.

European countries, which have many common policies and goals, are also having some disparities in their economic performance due to the existence of underlying country-specific reasons. The manufacturing sector is the key sector that promotes growth and increases the well-being of society. Thus, it is important to understand how these countries differ in engaging in industrial activities. Focusing on the manufacturing sectors of these economies, we aim to see the disparities between European Union (EU) countries in terms of their composition of manufacturing trade and the countries they are trading with. This chapter outlines some key stylized facts regarding trade over the past two decades by investigating the manufacturing data for EU countries.