To dig in a little more into your methodology, what do readers need to know about the foresight approach that you took in this work?
TS: We used a foresight approach because we want to look into the future of EU cohesion during the twin transition by using indicators which predict economic growth potential. Those indicators include high skilled labour, institutional quality, infrastructure quality, investment and innovation which are key for economic prosperity and growth (innovation being especially important for both a digital and green transition). We therefore collected a large amount of data and made comparisons across regions; the higher the values, the stronger the outlook for future growth.
Can you elaborate on the specific indexes involved and whether there was any controversy involved in their selection?
TS: What is new to our study is that we developed these ‘readiness scores’ which determine how well regions are doing in transforming to a green and digital economy. We picked the indicators behind the scores based on rigorous literature research. Eventually, we ended up with indicators such as labour productivity and internet accessibility for the digital readiness score, as well as greenhouse gas emissions or number of road vehicles for the green readiness score. These indicators are not controversial per se, but reduction of complex reality in this economic model is and was. For example, we received feedback from a region that considered themselves more ‘ready’ than a neighbour and they therefore doubted our results. We checked the data again, but in the end we confirmed that the region was indeed performing worse in every single aspect. Research like this is always a reduction of complex reality, but I think we explain the most important aspects on how regions differ quite well.