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Likely, the after-pandemic world won’t be as it used. To properly imagine and build our future, we should forget the progressive growth of past times and even the concept of “normality” of pre-pandemic years is going to change inasmuch as a new social concept is coming true ("surprise free" scenarios are no longer contemplated). The disposition of Italians towards their future was surveyed with three indicators: 1) the depression rate as measured with PHQ9, a standard psychological test for clinical depression measurement; 2) the pro-activeness orientation, as measured with an 8-item psychological test; and 3) the clearness rate of own future vision, as measured with a focused, dichotomous question. The indicators have been measured through a convenience sample on Italian adults during the second half of 2021. The analysis showed that the fear of contagion and the never-ending emergency due to Covid-19 pandemic caused such a psychological awkwardness to repress the disposition of Italians towards their possible futures. The repression was harder on youngsters, living alone persons, disrupted families, and people with psychic and/or depressive symptoms. A regressive model was furtherly fit on the collected sample. It showed multiple determinants of the future repression, say, that the fear of contagion was more relevant than the contagion itself and the uncertainty about the pandemic end was as disheartening as the contagion risk for the yearning hope of a positive after-pandemic lifestyle.

During the Covid-19 pandemic, remote working (RW) has been a way to producing despite limiting contacts. In Italy, about a half of the workers experienced, at least for a part of their working time, RW during the years 2020 and 2021. In this paper we analyse the data collected through a web-based survey conducted in the second half of 2021 at a convenience sample of Italian adults. The survey was aimed at highlighting how Italians experienced the pandemic and how they perceived their future. Also, we measured the frequency and the intensity of the RW phenomenon, the feelings of those who practiced and the opinion of workers about the possibility to practice it in the future. The data show that so many adults practiced RW during the pandemic. Their judgement of the experience is largely positive: 60.8% stated they were inclined to pursue it again as a normal work strategy. Though, there are distinctions. The type of job and the recent experience entail people’s commitment towards RW. Even what people expect from work may influence their disposition to take in RW as normal. The convolution of wells of the RW disposition, scouted through a multivariate statistical analysis, showed that, on top of the well-known suitability of RW to certain job types (white-collar, gig activities, self-employed), the workers’ propensity to RW is higher if commuting cost saving, own time optimisation and not-too-open schedules, work-family balance and a free time surplus, the possibility of interaction and socialisation with other company’s employees and customers and a secure web connection characterise their jobs.

Over the years, official statistics have shown increasing attention to the territory in providing detailed and quality information and, in this sense, the Population and Housing Census has always guaranteed the availability of sub-municipal data useful for decision-making processes in the social, economic and environmental fields. The Istat modernization programme introduced the Permanent Census that, differently from the traditional decennial census essentially drew on collecting data from people, is strongly based on the integration of administrative and sample data, and planned for providing yearly statistical figures. This change requires new methodological and IT architectures. It is a revolution that – on the medium term – is expected to provide more stable and coherent figures at various territorial levels.In this framework, sub-municipal data derives from the integration of the Basic Register of Individuals and the Basic Register of Places. The quality of data depends on the quality of the Registers and the procedures adopted to integrate and elaborate input data. In this regard, Istat is working to improve the geocoding information and linkage procedures. One of the problem encountered is that of non-geocoded units. These are units without an allocation into an enumeration area because of problems in administrative data. Istat has studied a procedure integrating deterministic and probabilistic approaches for assigning the enumeration area to those critical units. An experimental study is carried out to evaluate the quality of the imputation procedure. In this paper, we discuss the approach adopted, the evaluation process, the results obtained and the impact on the quality of the data and the spatial analyses that can be carried out.

How did individual and social aspects influence depression feelings during the pandemic? In this paper, we analyse the data collected through a survey conducted in the second half of 2021 among a convenience sample of Italian adults. The survey was aimed at highlighting how Italians experienced the pandemic and the way they perceived their future. A total of 556 Italians answered the CAWI survey. The analyses of the collected data show that, while having been infected by the virus or having had a family member infected by it did not influence the depression level, other individual characteristics and subjective feelings did. In particular, being female, younger, having had low trust in information delivered by television, no experiences of smart working or remote learning, little support from friends and family, and being unable to imagine the future increased the likelihood to feel higher levels of depression. Being able to imagine the future mediated the relationships of age and smart working or remote learning experiences with depression. The results indicate that, having a lower ability to imagine the future, younger people and individuals who did not work or study remotely have also a greater tendency to feel depressed.

Are Italian youngsters adequately equipped for an after-pandemic upswing?All over the world young people seem to be particularly dazed by the Covid-19 pandemic. Indeed, they were touched just lightly by the disease, though the isolation due to the distancing need and the remote learning mode may be the sources of depressive ailments and other psychological distresses. In this paper we analyse the data collected through a survey conducted in the second half of 2021 among a convenience sample of Italian adults. The survey was aimed at highlighting how Italians experienced the pandemic and the way they perceived their futures. About one third of the sample was below 35 and we consider them the young. Most of them were students, a few worked, some were looking for a job. The analysis of the collected data shows that so many young Italians were disturbed by the pandemic, even though the sanitary impact of the disease on them was much less relevant than other age classes. Among the youngsters, the depression and anxiety rates was significantly higher than other adults, the perception of a future role was limited to them and their potential resources for future life was also jeopardized. The possible causes of the reduction capacity among young adults was scouted through a multivariate statistical analysis. It showed that the perception of personal difficulties is correlated to a feeling of uncertainty for their future roles, to a pressure over their social-economical and personal resources to face their future and to a sort of apathy that could limit their pro-activeness.

The Delphi-based scenarios (DBS) development implies the assumption of different choices, through the gathering of information and the assessment of alternative resolutions (Panpatte and Takale, 2019). During the last decades, the spread of environmental hazards has increased quickly, much to request different responses in order to develop a sustainable future for humanity planning the present (McMichael and Lindgren, 2011). Since the DBS is a creative process (Nowack et al., 2011), different figures are selected to make choices, including academics, stakeholders and citizens. However, one of the main challenges remains the measurement of expertise, in fact, during the process, the experts should be assessed based on their competences in order to avoid any conflict in the final results and, eventually, weigh their answers. In recent years, some contributions adopted the self-assessments for the experts’ evaluation (Sossa et al., 2019), but many issues still remain (such as strong subjectivity and cognitive biases which produce over or underestimation). We develop a new method to estimate the expertise by using Natural Language Processing to acquire information, extracting the contributions of experts in each topic. First, starting from a draft list of selected experts, we identify the category of reference (e.g., academia, industry, local authority, citizens etc.). We build a data repository with the personal pages (URLs) of each expert to then use Python to extract from the URLs, the number of contributions related to a keyword, different for each category (e.g., publications for academics, reports and projects for stakeholders etc.). Finally, we proceed adopting a coefficient of production with a weighted sum of the results. To practically demonstrate our approach, we applied this method to a cohort of known experts, part of the “Smart control of the climate resilience” (SCORE) H2020 European project to estimate their expertise in specific areas.

In the context of Futures Studies, the scenario development process permits to make assumptions on what the futures can be in order to support better today decisions. In the initial stages of the scenario building (Framing and Scanning phases), the process requires much time and efforts to scanning data and information (reading of documents, literature review and consultation of experts) to understand more about the object of the foresight study. The daily use of social networks causes an exponential increase of data and for this reason here we deal with the problem of speeding up and optimizing the Scanning phase by applying a new combined method based on the analysis of tweets with the use of unsupervised classification models, text-mining and spatial data mining techniques. For the purpose of having a qualitative overview, we applied the bag-of-words model and a Sentiment Analysis with the Afinn and Vader algorithms. Then, in order to extrapolate the influence factors, and the relevant key factors (Kayser and Blind, 2017; 2020) the Latent Dirichlet Allocation (LDA) was used (Tong and Zhang, 2016). Furthermore, to acquire also spatial information we used spatial data mining technique to extract georeferenced data from which it was possible to analyse and obtain a geographic analysis of the data. To showcase our method, we provide an example using Covid-19 tweets (Uhl and Schiebel, 2017), upon which 5 topics and 6 key factors have been extracted. In the last instance, for each influence factor, a cartogram was created through the relative frequencies in order to have a spatial distribution of the users discussing each particular topic. The results fully answer the research objectives and the model used could be a new approach that can offer benefits in the scenario developments process.

The Analytic Hierarchy Process (AHP) is a Multi-Criteria method in which a number of decision factors (typically criteria and alternatives) are compared pairwise by one or more experts, using the Saaty scale, with the goal of sorting the alternatives (Saaty, 1977; 1980). For group AHP the Delphi method can be used in parallel with the AHP (Di Zio and Maretti, 2014), and this allows the search for a consensus on each pairwise judgement. A big issue of the AHP regards the inconsistency of the pairwise comparison matrices and here we propose a new method to reduce the inconsistency. As a solution we exploit the Nudge theory (Thaler and Sunstein, 2008) and from the second round of the Delphi survey, we calculate and circulate a Nudge to “gentle push” the experts towards more consistent evaluations. Furthermore, we propose the representation of the AHP matrices through graphs. In a direct graph two nodes are linked with two direct and weighted edges (or one edge with the direction based on the weights), where the weights indicate the evaluation given by an expert or, for a group, the geometric mean of the judgements. This type of visualization facilitates the reading of the results and could also be used as real-time feedback in the Delphi process, by displaying on the edges also a measure of variability. An application is proposed, on the evaluation of four future scenarios on the regulation of genetic modification experiments, assessed by a panel of 27 experts according to different criteria (plausibility, consistency and simplicity). The application demonstrated that it is possible to: a) reduce the inconsistency; b) collect useful textual material which enrich the AHP itself; c) use the inconsistency index as a stopping criterion for the Delphi rounds; d) display the pairwise comparison matrices with graphs.