This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivariate framework. A panel of 16 EU countries was analyzed over the 1990–2017 period. The results of the Dumitrescu-Hurlin panel causality tests reveal the existence of a one-way causality running from ICT usage and electricity consumption and which, in turn, causes a rise in CO₂ emissions and improves GDP. Panel Mean-Group regression results highlight that economic growth is also an important driver of electricity demand as a 1% economic growth rate is associated with a 0.13% increase in per capita electricity consumption. These results demonstrate for the first time in the literature a single assessment on the linkages among ICT, electricity use and environmental pollution with a novel focus on the EU. Based on these results, adequate measures should encompass the adverse environmental effects of ICT, while energy saving policies must be carefully implemented in order not to hinder economic growth.

Climate-smart agriculture (CSA) is a technologically innovative response to the challenges faced by agriculture due to climate change. Its implementation needs a change of mentality in the direction of an approach that takes into account how the increase in technologically induced productivity affects climate change. In the belief that the in-depth analysis conducted by scientific research plays a fundamental role, we explore the characteristics, actors, and pillars of CSA, examining both the scientific literature and financed projects. Specifically, through a systematic review of the literature we address both the application and barriers to implementation at a global level, and then we focus on a case study of the geographical distribution of CSA projects in Europe. Our results show a heterogeneous framework in which we can note discrepancies among countries. Finally, as conclusive remarks, we consider the type of policies that could be implemented to improve the diffusion of CSA in the near future.

Earthquake insurance can be a useful tool to build more sustainable societies and disaster-resilient communities. However, the coverage is not common in many countries. This article aims to contribute to the literature through an empirical analysis of the online interest in earthquake insurance through Google Trends. The proposed methodology implies to move from a top-down conceptual approach to a bottom-up/data-enabled one. It allows us to explore potential triggers and dynamic patterns of online interest in earthquake insurance at daily time-scale through the lens of Big Data. In order to validate the methodology, the article considers Italy as a test area. For this country, where the coverage rate is low, we fuse multiple databases to create 16-year daily time series of public search activities about the insurance in Italy and analyse it with other data sources. As a result, the peak analysis shows a connection with the occurrences of large domestic earthquakes, overseas earthquakes, and policy decisions, which create time windows of opportunities for insurers and policymakers to boost the public’s motivation towards the coverages. The research outcomes suggest that the data-enabled approach can additionally be applied in other countries where the coverage rate is low and stakeholders are facing the challenge to strive against earthquake under-insurance.