In 2012, the Italian “National Strategy for Inner Areas” (SNAI) was approved to enhance essential services (transport, education, healthcare) and boost economic growth in underdeveloped areas. After more than ten years since the first SNAI programming cycle (2014-2020) and at the beginning of the second one (2021-2027), this research analyses the thematic scopes and funding of projects implemented during the first SNAI cycle to support local authorities in the second cycle. The analysis focuses on the four Inner Areas of Piedmont to support the SNAI strategy development process in Valsesia, which was designated as one of the new Piedmont Inner Areas in 2022. The study, part of the B4R - Branding4Resilience project, uses government open data and Exploratory Data Analysis to examine the geographic and thematic distribution of SNAI interventions. Results show the allocation of projects and public funds, identifying popular themes and gaps. Among the most significant findings, the thematic scopes of “Transport and Mobility” and “Social Inclusion and Health” emerged as the most funded, while scopes such as “Environment”, “Research and Innovation” and “Employment and work” were significantly underrepresented, especially in Piedmont. Understanding the strengths and weaknesses of the first cycle is crucial for refining future strategies, avoiding past inefficiencies, and maximising the impact of upcoming interventions. Insights drawn from the analyses aim to support local authorities in addressing new interventions and actions, enhancing strategic planning for territorial projects.

The article aims to examine how the armed conflict affects the environmental safety and resilience of the urban environment in Ukraine. The author analyzes the impact of infrastructural, social, economic, and environmental resistance on the city’s ability to maintain a socioeconomic and ecological balance and minimize the mass destruction of its infrastructure. The article employs general scientific and special methods, including theoretical generalization, comparison, systematization, abstract-logical, prognostic, logical, and analytical methods. The article relies on an integrated approach when assessing environmental safety and its preservation; it primarily involves implementing preventive measures necessary to ensure the viability and sustainability of urban areas in the conditions of war and after its end. The findings confirm that a close interaction between public authorities, scientific institutions, public organizations, and the population can help to achieve sustainable development and urban environment safety in Ukraine. It is suggested to focus on climate-neutral post-war recovery and strengthen the potential of territorial communities in further scientific research.

Mass appraisal has significant applications, such as urban planning, real estate appraisal, and property tax. Due to the challenges of analyzing massive models, they are often developed using semi-automatic assessment methods and machine learning techniques. This article explores different appraisal model methods that utilize statistics and machine learning. It also looks at incorporating spatial information to see if the chosen method can effectively capture the typical spatial dependency of the real estate market. This can help reduce the spatial autocorrelation observed in the residuals. The study compared nine machine learning methods with traditional statistical approaches using a dataset of over 43,000 apartments in Fortaleza, Brazil. The results of the machine learning algorithms were similar. The XGBoost minimized spatial autocorrelation. The easiest interpretations were with MRA, M5P, and MARS techniques. Although, these techniques had the greatest residual spatial autocorrelations. There is a trade-off between the methods, depending on whether the aim is to improve accuracy or provide a clear explanation for property taxation.

The paper presents a parametric approach to quantify the economic value of hedges in urban green spaces. The model integrates indexes that allow for an aesthetic estimate of green infrastructure. Both field and desk phases are developed to depict and sample hedgerows in a case study in Italy (Cascine Park, Florence). Street view and Google Maps applications are used in the preliminary steps to spatialize hedges. An equation, incorporating nine variables including financial, dendrometric, and correction factors, is developed to appraise economic value. The results highlight the relevance of species, plant height, and the number of hedge rows for the unitary and total value of green infrastructures. Phytosanitary condition, the presence of gaps in linear traits, and the degree of tree canopy coverage also influence the economic performances of hedges. The technique facilitates application for both researchers and practitioners, potentially allowing for damage estimates and calibrated management of urban green in different locations.

Flea markets are important as economic and cultural phenomenon in several cities around the world. There is little attention to their influence on real estate prices. The “Brique da Redenção” occur every weekend since 1978 in Porto Alegre, Brazil. There could be positive effects on surrounding properties. However, the positioning of this flea market implies on reduce the accessibility on weekends to properties placed in the same street and it could reduce property prices. The aim of this paper is to evaluate the influence of this flea market in residential prices. It was developed hedonic models to explore these effects, with a sample of more than 5.3 thousand apartment sales. The analysis shows a satisfactory statistical performance of the hedonic model. The study indicates that Brique’ effect is capitalized in the market prices, with an average loss on value around to 7.8% to properties placed in front to the Brique.

Society's awareness of livestock production conditions has increased interest in animal welfare (AW), prompting farmers to consider it in their strategies. However, the adoption of digital devices and sensors to ensure AW is still relatively low. The aim of this study was to assess simultaneously the stated behaviour and intention of dairy farmers towards adopting technological tools for AW. The extended Theory of Planned Behaviour (e-TPB) was selected as theoretical base. It is “extended” since new predictors are integrated in the standard framework of the TPB. The research questions were addressed using a partial least squares structural equation modelling. The findings suggest the existence of a gap between farmers' intentions and behaviour. Perceived Behavioural Control plays a significant role in behaviour, indicating the predominant influence of self-confidence in farmers' choices. Operating margin and technological specialization of the farms are significant predictors of farmers' behavior.

In the current Italian real estate market, estimates of the market value of rural properties are carried out by appraisers mainly using the single-parameter comparison procedure and, less frequently, the income capitalization method. To overcome problems of appraiser subjectivity and other issues related to these methods, and to gradually comply with real estate appraisal standards, this research paper aims to develop and validate a scientifically rigorous method. This article carries out a first attempt to apply the mixed approach based on the integration of Market Comparison Approach (MCA) and General Assessment System (GAS) to agricultural land, currently used only in the field of urban real estate appraisal. The study focuses on the first steps of this valuation procedure: choice of the parameters which characterise the market segment and identification of the land characteristics to be included in the procedure. These two steps are preparatory to the following phase concerning the estimate of marginal prices, which represents the core of the whole valuation procedure. In the current Italian real estate market, estimates of the market value of rural properties are carried out by appraisers mainly using the single-parameter comparison procedure and, less frequently, the income capitalization method. To overcome problems of appraiser subjectivity and other issues related to these methods, and to comply with real estate appraisal standards, this research paper aims to develop and validate a scientifically rigorous method. The Market Comparison Approach (MCA) is used as a starting point for a comparative multiparameter approach, which is currently only used in the field of urban real estate appraisal.This paper carries out a first attempt to apply the MCA to agricultural land, contributing an initial exploration of developing the proposed methodologies. Specifically, this paper reports the first steps that have been carried out in this line of research: choosing the parameters to identify the market segment; identifying the characteristics to include in the procedure for which to determine the respective marginal prices.

The aim of this study is to develop a value-based GeoValueIndex with AHP weights and GIS for the criteria of the Mersin University (MEU) Çiftlikköy Campus real properties, and it is referred to as the “GeoValueIndex” in this study. GeoValueIndex is a symbolic value that combines geographic and non-geographic features of real properties. The data of the real properties on the campus were collected and arranged for mass appraisal. One of the Multi Criteria Decision Analysis (MCDA) methodologies, Analytic Hierarchy Process (AHP), was used to weight the criteria. GeoValueIndex was calculated by multiplying each parcel’s geographic and non-geographic data by their weights and adding them. GeoValueIndex Map is obtained by associating GeoValueIndex and parcel in GIS software. GeoValueIndex of real properties save time, effort, and cost in mass appraisal processes. There are many techniques for doing GeoValueIndex operations, and the ones presented in this study are only proposals.

The paradigm shift towards a more humanistic and ecological paradigm evoked by United Nations and the Green Deal is increasingly required in this period of growing unsustainability, especially during ongoing COVID-19 pandemic. The challenge today is to reduce poverty and inequalities, while preserving the vitality of natural ecosystems and ensuring inclusive economic growth and wellbeing, both now and in the future, thus including future generations. To this end, new models for city development and new tools for operationalizing them are necessary. This paper is focused on the circular economy model and, in particular, on the functional reuse of cultural heritage as the entry point for triggering circular processes in the cities. The attention is focused on the evaluation tools and a methodological proposal is presented starting from the Level(s) tool (developed by European Commission) for assessing the multidimensional impacts of cultural heritage functional reuse projects in the circular economy perspective.