RESUMO
What is the real meaning of sustainable innovation? How is sustainable innovation different from other forms of innovation? How does sustainable innovation contribute to societal development? How can we measure the sustainable innovation of a country-which indicators and which synthesis methods should we use? In this paper we try to answer these previous questions. Starting from the concept of sustainable innovation, as it has been extensively discussed in recent years in a range of disciplines from economics to engineering and sociology, the paper focuses on the basic criteria (such as indicators and statistical models) required to evaluate the sustainable innovation at the regional level, choosing Italy as a case study. From the elementary indicators of innovation, on one hand, and sustainability, on other hand, a composite indicator of sustainable innovation has been computed. The statistical model used to compute this composite indicator has been a Higher-Order Partial Least Squares Path model. The results obtained applying this model to the Italian scenario are discussed, the ranking of the different Italian regions, and the impact of the composite indicator sustainable innovation on economic results of each region are discussed.
RESUMO
In recent years, the share of young people not in education, employment, or training (NEETs) has shown a remarkable increase in many European countries, such as Italy. The wide diffusion of NEETs represents an alarming social issue, as being NEET predisposes young people to long-term unemployment and social exclusion. It also has a significant negative impact on the economic growth and welfare equilibrium of countries. The aim of this paper is to analyze the determinants of the NEET condition in Italy through a step by step procedure beginning with the identification of their main characteristics and then proceeding with a focus on specific homogeneous clusters of NEETs. The decomposition of the gaps in the probabilities of being NEET between the various clusters allows verifying how personal characteristics effectively act. Furthermore, the influence of unobserved factors in the professional condition of young people has been analysed in more detail through a bivariate selection probit model on the propensity to look for a job against the condition of being inactive. The results confirm the crucial role of the education system, as well as the importance of the economic and social disparities between gender and the Italian territorial districts.
