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Obtaining indicators on the innovation activities of firms has been a challenge in economic research for a long time. The most frequently used indicators - R&D expenditures and patents - provide an incomplete picture as they represent inputs in the innovation process. Output measurement of innovation has strongly relied on survey data such as the Community Innovation Survey (CIS). However, this type of data suffers from several shortcomings typical of surveys, including incomplete coverage of the business sector, subjectivity concerns, low timeliness, and limited comparability across industries and firms. An alternative that has attracted growing interest is to use big data sources to collect innovation data at the firm level. This paper discusses recent attempts to use digital big data sources including websites and social media to generate firm-level innovation indicators. It summarises the main challenges of using big data and proposes practical guidelines for their use, including a research agenda that should be useful to practitioners as well as users of statistics derived from big data. • The paper discusses recent attempts to use digital big data sources to generate firm-level innovation indicators. • The paper summarises the main challenges of using big data. • The paper proposes practical guidelines and presents a research agenda. [ABSTRACT FROM AUTHOR]

The present study investigates the effects of energy-related technologies on economic performance at firm level. We distinguish clearly between adoption and use of energy-related technologies (process innovation in the broad sense) and product innovation in energy-related fields. We take into consideration four energy-related policy instruments (and expected demand for energy-related new products and services). We investigate the possibility of indirect effects of policy on performance via adoption or innovation by interacting adoption and innovation variables with policy instrument dummies. We test our hypotheses not only for the pooled data but also separately for the three countries (Austria, Germany, Switzerland) that are taken into consideration in this study. We find a positive direct effect of investment expenditures for energy-related technologies on labour productivity – that measure intensity of adoption of energy-related technologies – and a positive indirect effect of energy taxes via investment in energy-related technologies. Further, we find positive direct and indirect effects of regulation , standards and voluntary agreements via the adoption of production-related technologies and for technologies for the generation of renewal energy sources . We find neither direct nor indirect effects of the sales of innovative energy-related products – that measure product innovation in energy-related products – on labour productivity. No differences among the three countries could be detected with respect to investment in energy-related technologies and sales of innovative energy-related products. The indirect effects of regulation and standards and voluntary agreements can be primarily traced back to German firms. [ABSTRACT FROM AUTHOR]

Abstract: Competitive production costs compared to conventional fuels are imperative for biofuels to gain market shares, as current tax advantages for biofuels are only temporary. Comparing production costs of different biofuels with fossil fuels is a challenge due to the complexity of influencing factors. The objective of this research paper is threefold: 1) to project future bio-fuel feedstock prices based on the crude oil price development, the price index for agricultural products, growth in world population, growth in wealth per capita income, and change in energy consumption per capita, 2) to simulate production costs under consideration of likely economies of scale from scaling-up production size and technological learning and 3) to compare different biofuels and fossil fuels by scenario analysis. A calculation model for biofuel production is used to analyse projected production costs for different types of biofuels in Europe for 2015 and 2020. Unlike engineering oriented bottom–up approaches that are often used in other biofuel studies, the macro-economic top–down approach applied in this study enables an economic comparison and discussion of various fuel types based on reference scenarios of crude oil prices of €50, €100, €150 and €200 per barrel. Depending on the specific raw material prices as well as the conversion costs, the analysis delivered a differentiated view on the production costs and thus on the competitiveness of each individual type of fuel. The results show that 2nd generation biofuels are most likely to achieve competitive production costs mid- to long-term when taking into account the effects from technological learning and production scale size as well as crude oil price scenarios between €50 and €200 per barrel for both reference years. In all crude oil price scenarios, bioethanol from lignocellulosic raw materials as well as biodiesel from waste oil are associated with high cost saving potentials which enable them to outperform fossil fuels and 1st generation biofuels. [Copyright &y& Elsevier]