CORDIS

It is currently believed that the major markets of the future will have a strong ecological dimension, since available resources are valuable, energy production is costly and ecological amenities increase in importance. Therefore, alternative energy sources, waste management and recycling systems should be identified, while processes with greater resource efficiency ought to be developed. As such, eco-innovation becomes of increasing importance; however its outputs and inputs are yet poor.

The MEI project focused on the measurement aspects of eco-innovation, which was defined as the development, assimilation and exploitation of a product, process, service or method which was novel to the company developing or adopting it and which resulted, throughout its life cycle, in the reduction of environmental risks, pollution and impacts on resources in comparison to alternatives. A typology of eco-innovation was proposed to assist policy and statistical data collection. Moreover, companies were categorised with respect to the applied eco-innovation approach.

The usefulness of three implemented measurement methods was assessed as part of MEI. Firstly, the survey analysis method was investigated and the potential to include eco-innovation information in the applied techniques was evaluated. Suggestions on questionnaires were therefore formulated and optimal sets of questions were indentified, both for the determinants and the novelties’ control variables.

Moreover, the patent analysis was assessed as a tool for assessing proposals. Patents formed an important indicator of novelties and had the advantages of providing detailed technological information and being publicly available for rather long time series. In addition, they were directly linked to technical invention. Therefore, seven attributes of cutting-edge activities that could be evaluated through patent data were identified. However, the patents’ value was fluctuating, since their majority was never widely used, while available data only captured a restricted amount of the developed solutions.
A four-step method for patent analysis, which overcame the abovementioned hurdles, was developed as part of MEI. In was noted that patents’ investigation was useful to identify product innovations and ‘end of pipe’ technologies but did not suit other types of proposals.

Moreover, creativity could be measured using digital and documentary sources, through the monitoring of trade journals and product information databases. Since only a few datasets included environmental parameters, a database for eco-innovation output was created by sampling sections of interest from journals and including information provided by producers. The strengths and weaknesses of the implemented approach were subsequently identified.

Research on advances concluded that they occurred within a wide context that shaped processes, output and economic and environmental results. Therefore, the collection of data regarding these contextual factors was necessary. MEI examined six different approaches to investigate the systemic and dynamic novelty aspects in order to identify representative metrics. The analysis resulted in useful indicators which were categorised with respect to their relevance to the firm, the operating conditions, the developed linkages, the radical and incremental innovation and the overall performance.

In addition, possibilities for creating a benchmark indicator for eco-innovation were analysed, resulting in the development of a proposal which was pilot tested. The indicator was based on companies’ information which was obtained through survey. Data that were used in economic models for the determination of the effects of environmental and energy policies, as well as the expected future needs, were also investigated.

The potential effects of eco-innovation on the competitiveness of nations and sectors were additionally evaluated. It was noted that combinations of different measures and methods provided better estimates than the utilisation of single techniques. Two essential difficulties impacting the accuracy of the predictions were the lack of specific trade statistics and the necessity to undertake case study analyses to define existing conditions. Finally, the MEI team formulated suggestions for future research, based on the undertaken project activities and their outcomes.