Ana Cristina Santos Amaro

We examine the main existing challenges that currently arise in the assessment of European Union (EU) funds devoted to three thematic objectives (TOs): Research and Innovation (R&I); Low-carbon economy (LCE); and Information and Communication Technologies (ICT). In this regard, a literature review on the European Regional Development Fund (ERDF) initiatives is performed, with a special focus on the Portuguese (PT) case, also addressing their assessment and reporting practices. Data systematization is coupled with the European Commission (EC)’s main guidelines and with the guidance recommendations brought by Management authorities (MA) for the 2014–2020 period. A bibliometric analysis is conducted to further understand the current research interest in the evaluation of EU funds, and the type of assessment methods and reporting practices employed. Most of the approaches rely on cost–benefit analysis and place less attention on data availability, variable selection, and monitoring/assessment options. The selection and application of the framework indicators, either related to their financial execution or achievement, are assumed as critical factors concerning the monitoring, reporting, and assessment processes. Our findings emphasize the need for harmonization and simplification of the reporting techniques, also highlighting the sparse data availability and some reporting conflicts.

We evaluated the implementation of European Regional Development Funds (ERDF) devoted to Thematic Objective (TO) 4 in 23 beneficiary European Union (EU) Member States (MS). The assessment of each country was made through the value-based data envelopment analysis (VBDEA) approach in three phases. In the first phase, it was possible to conclude that 43% of the MS were efficient in the implementation of the ERDF devoted to a low-carbon economy (LCE), and the reasons for their efficiency were mainly explained by their execution rate. After running the second phase for the inefficient countries, it was possible to obtain the improvements that must be made for these countries to “emulate” their peers at the efficient frontier. Finally, in the third stage, we incorporated political concerns in the evaluation of the implementation of the ERDF by including constraints on the ranking order of the weights. A robustness analysis was also carried out, according to which it was found that only 22% of the MS under evaluation remained surely efficient for tolerances of δ = 5% and δ = 10%, with Spain being the most robust country. Other countries such as Romania (surely inefficient for δ = 5%), Hungary, and the Czech Republic (the most inefficient) did not manage to implement these funds efficiently. Considering these findings, the EU needs to further promote policies that ensure economic benefits from investing in an LCE, specifically for countries with fewer resources, while also providing them with better financial conditions and know-how.

The European Regional Development Fund devoted around 66 billion Euros to the financial support of innovation and productivity in European enterprises over the 2014–2020 programming period. In this framework, we assessed the implementation of the Operational Programmes dedicated to fostering research and innovation, particularly in small and medium-sized enterprises. With this aim, we used a network slack-based data envelopment analysis model paired with cluster analysis that encompasses a multitude of performance framework indicators to assess 53 Operational Programmes from 19 countries. Our findings suggest that compared to transition and less developed regions, more developed regions present a higher room for improvement. Also, less developed regions present a better performance when they employ their funding against more developed regions, suggesting that further funding should be channelled for leveraging research and innovation in the former regions. Finally, Operational Programme managers should focus on solving the problems both inherent to the poor outcomes in terms of enhancing the number of researchers working in improved research infrastructures and promoting the technology transfer between research institutions and enterprises.

Funds from the European Union that are devoted to fostering a low-carbon economy are aimed at assisting Member States and regions in implementing the required investments in energy efficiency, renewable energy, and smart distribution electricity grids, and for research and innovation in these areas. In this context, we assessed the implementation of these funds in small and medium-sized enterprises across different beneficiary countries and regions of the European Union. Therefore, this study uses a non-radial slack-based data envelopment analysis model coupled with cluster analysis that covers multiple aspects of evaluation, including two inputs and two outputs, to assess 102 programs from 22 countries. Overall, we were able to ascertain that there are 25 efficient operational programs that remain robustly efficient, whereas 51 remain robustly inefficient for data perturbations of 5 and 10%. Under the current output level, there was almost no input surplus. Therefore, to promote a low-carbon economy, operational program managers should concentrate on solving the problems behind the poor results achieved, both in terms of greenhouse gas emissions reduction and the pace of the programs’ implementation.

This paper studies the food waste problem in private and public collective catering units (CCU), served by a Portuguese catering company. The main objective is to develop data analysis and decision tools that may contribute to the waste control and to the operational planning of CCU. A set of novel key performance indicators (KPIs) are settled and evaluated to characterize food waste over time. For these indicators, several representations were studied, tested, and validated to create a dashboard intended to be clear and intuitive, regarding the food wastes. Operating practices require simple, objective, replicable, and ideally inexpensive data collection procedures. So, the proposed solution accounts for the trade-off between the details of the created data model and the associated data synthesis and visualization. The proposal (indicators and dashboard) was submitted to four weeks of tests, in six CCUs. The organizational validation achieved allows the conclusion about the interest of this contribution.