Francesca Gagliardi

Food insecurity has increasingly emerged as a structural concern in high-income countries, yet its territorial dimensions and the role of local welfare infrastructures remain underexplored. This study addresses this gap by analyzing the spatial and temporal dynamics of food assistance systems in Italy using administrative data from the Fund for European Aid to the Most Deprived (FEAD) program over the period 2019–2023. Adopting an exploratory and system-oriented approach, the paper develops three operational indices to capture key dimensions of local food assistance: demand intensity (Food Aid Index, FAI), organizational coverage (Land Coverage Index, LCI), and functional diversification (Food Aid Diversification Index, FDI). These indicators are used to examine territorial disparities and identify structural patterns across provinces. The results reveal marked spatial heterogeneity, persistent North–South divides and diverse configurations of demand and service provision. The analysis highlights potential mismatches between the intensity of food assistance demand and the capacity of local systems to respond, pointing to differentiated territorial trajectories. Rather than directly measuring food insecurity, the study interprets food assistance as a proxy for the interaction between social need and institutional response. This perspective helps identify infrastructural inequalities and improve understanding of how food assistance systems are embedded within broader welfare configurations.

Ensuring sustainability in the agri-food sector requires comprehensive data analysis. This study examines missing data patterns in a large-scale survey of Italian agri-food companies within the Italian National Research Center for Technology in Agriculture (Agritech), focusing on sustainability variables. The underlying idea is that failure to report a value for these variables indicates low attention to sustainability. We employ graphical Ising models to infer the conditional independence structure among missingness indicators and fully observed farm characteristics, which are modeled as binary variables. The graph structure is selected through node-wise logistic regressions with variable selection based on a backward stepwise procedure guided by the Bayesian Information Criterion (BIC). This approach enables the recovery of sparse and interpretable graphs while controlling for model complexity. We are not interested in causal relationships between missingness indicators and fully observed variables; rather, our focus is on the dependence structure among these variables. The method is applied to the Agritech data, yielding both a national graph and macro-regional graphs, as well as differential networks that highlight structural differences between each macro-region and the national graph. These results provide new insights into systematic patterns of missing data, offering a rigorous framework for improving data quality in terms of completeness and reliability.

Studying consumers’ willingness to pay (WTP) for sustainable certification labels and preferences in consumption is a relevant issue for policymakers. Several studies have revealed a positive WTP a premium price for many certified products. The aim of this paper is to assess an overview of Italian consumers’ WTP for eight different sustainable certification labels and to collect information about their consumption preferences and perceptions in consumption. Participants were selected by stratified simple random sampling, using regional distribution, gender, and age as stratification criteria, to obtain a representative sample of n = 3600. Eight ordered logit models were estimated to understand how consumer sociodemographic characteristics influence the price premium. The results show important differences in WTP among different certification labels; a higher WTP emerged for ethical certifications than for environmentally focused labels. Younger individuals; women; and those with higher education, income and life satisfaction, as well as consumers in southern regions, were significantly more willing to pay premiums for certified products. However, a key finding for policymakers is that the stated price premium consumers are willing to pay falls significantly short of the actual higher costs of these products in supermarkets. Furthermore, insights into consumer perceptions and preferences revealed that quality and origin are perceived as key price drivers, while method of production holds less importance. It also emerged that consumers primarily seek a balance between quality and price, with only a small segment prioritizing certified products.

Studying consumers' willingness to pay (WTP) for sustainable certification labels and preferences in consumption is a relevant issue for policymakers. Several studies have revealed a positive WTP a premium price for many certified products. The aim of this paper is to assess an overview of Italian consumers' WTP for eight different sustainable certification labels and to collect information about their consumption preferences and perceptions in consumption. Participants were selected by stratified simple random sampling, using regional distribution, gender, and age as stratification criteria, to obtain a representative sample of N=3600. Eight ordered logit models were estimated to understand how consumer socio-demographic characteristics influence the price premium. The results show important differences in WTP among different certification labels; a higher WTP emerged for ethical certifications than for environmentally focused labels. Younger individuals, women, those with higher education, income, and life satisfaction, as well as consumers in Southern regions, were significantly more willing to pay premiums for certified products. However, a key finding for policymakers is that the stated price premium consumers are willing to pay falls significantly short of the actual higher costs of these products in supermarkets. Furthermore, insights into consumer perceptions and preferences revealed that quality and origin are perceived as key price drivers, while method of production holds less importance. It also emerged that consumers primarily seek a balance between quality and price, with only a small segment prioritizing certified products.

The agri-food sector is undergoing profound transformations driven by ecological and digital transitions, as well as evolving consumer and nutritional choices. These shifts pose significant challenges but also open new opportunities for businesses to enhance sustainability and competitiveness through circular economy principles. In response, Spoke 9 of the National Agritech Center (PNRR) has launched a survey to analyze agri-food companies and sustainability practices and promote circular strategies. A large-scale survey conducted in early 2024 gathered data from 3002 agri-food companies, covering 20 Italian regions and six major supply chains (wine, olive oil, dairy, milk, fruit and vegetables, and beekeeping). The study is the first attempt in Italy to get metrics on these topics from agri-food companies, and it provides a comprehensive assessment of circular economy practices in the sector. The key objectives of the work are as follows: (1) developing integrated sustainability indicators; (2) sector-specific circular metrics; (3) identifying best practices and gaps; (4) supporting policy and decision-making; and (5) benchmarking and monitoring.

The study, carried out by the University of Siena within the framework of Spoke 9 of the National Agritech Centre, examines the sustainability performance of 3,002 Italian agri-food firms. The analysis, primarily focused on small and medium-sized enterprises (SMEs), reveals substantial disparities with respect to large ones in terms of energy efficiency, water management, and social inclusion. Despite these criticalities, the study highlights an increasing uptake of sustainable practices and ESG certifications. Overall, the results portray a sector undergoing transition, in which innovation and institutional support emerge as key drivers in enhancing the sustainable competitiveness of the national agri-food system.

The report, realized by the University of Siena within the framework of Spoke 9 of the National Agritech Centre, analyzes the sustainability practices of 574 Italian wine companies, comparing them with the broader national agri-food sample. The findings indicate that wine-sector SMEs, although constrained by limited resources and organizational structures, are making progress in the adoption of renewable energy, certifications, and short supply chains. Nevertheless, critical issues remain in energy efficiency, water management, and social inclusion. The study underscores the need for targeted policies and innovation tools to support the sustainable competitiveness of the national wine industry.

This paper arises from an ONRR project on “New technologies and methodologies for traceability, quality, safety, measurements and certifications to enhance the value and protect the typical traits in agrifood chains”. It has a first aim of performing an exhaustive review pertaining to the construction of indicators of the quality and safety of agrifood products, creating information systems dashboards of unidimensional and multidimensional indicators and applying such indicators, in the context of consumer choices and decisions of policy-makers and firms. Since it has been found that the literature offers no single proposal linking all such aspects, a second central and innovative aim is to propose an original step-by-step procedure for integrating information systems of statistical indicators for citizens, institutions and policy-makers with a specific focus on new technologies and methods for traceability, quality and safety of agrifood systems. The final output is a smart and user-friendly online database that is an absolute innovation on the topic.

The best evaluation for the proportion of defective units in a batch of fruits and vegetables can be achieved by an exhaustive checking of all the boxes in the batch, that is prohibitive to perform in most cases. Usually, only a sample of boxes is checked. In EU countries, EU regulations establish to estimate the proportion of defective units in a batch by the proportion of defective units in the sample, without giving any rule for selecting boxes. Therefore, results are highly dependent on the subjective choice of boxes. In the present study, an objective design-based approach is considered to select boxes from batches, adopting balanced spatial schemes with equal inclusion probabilities. The schemes are able to select samples of boxes evenly spread throughout the batch also ensuring good statistical properties for the proportion of defective units in the sample as estimator of the proportion of defective units in the batch. The performance of these strategies is evaluated by means of a simulation study performed on real and artificial batches of apples, peppers and strawberries. A case study is considered to estimate the proportion of defective units in a batch of courgettes stored in a distribution center of a supermarket chain in Central Italy.