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The increasing numbers of wild animals in Europe is leading, on the one hand, to growing problems stemming from their interaction with human activities. On the other, many European countries have still not developed national supply chains to market wild game. Instead, these supply chains could represent a win–win strategy in providing a sustainable alternative to production via intensive livestock farming and developing rural territories. Our aim was to understand consumer behaviour towards wild game meat. We conducted a choice experiment on wild boar meat on a sample of Italian consumers (625). The application of a hybrid model combining a structural equation model and a latent class analysis allowed us to identify the antecedents of attitude towards wild game meat and to analyse consumer choices by utilising attitude as an explanatory variable. The results provide useful suggestions to implement rural development policies and offer food for thought in the area of consumer behaviour.

Consumers’ interest in product information, such as nutrition, environment, and social aspects, is increasing in the food market. Blockchain technology can enhance credibility of quality signals on labels through transparency and accountability in the supply chain. This study examines the impact of blockchain technology on reducing consumer uncertainty about credence attributes and facilitating informed choices. It is particularly relevant for food policies, as greater consumer awareness promotes proactive involvement in sustainability and public health. We conducted a choice experiment with 300 Italian consumers, focusing on craft beer and analysing how blockchain technology in strengthens organic and DOP certification. The results provide valuable insights for producers and policymakers to develop voluntary approaches that engage society in objectives that concern the collective well-being. They highlight the potential of blockchain technology in communicating credence attributes and empowering consumers. However, our study reveals that the impact of blockchain technology on choices is influenced by a different level of trust, likely due to the complexity of understanding its functioning.

The transition of food systems towards more sustainable organizational models is increasingly positioning Short Food Supply Chains as a key channel to value the specific attributes of local products, while also meeting the growing demand for diversified consumption based on both socio-economic and socio-cultural drivers. The aim of this paper is to offer new insights into evolutionary multi-stakeholder organization strategies within SFSCs, analysing drivers and barriers to their adoption, and investigate consumer acceptance of such new models. We draw upon the case study of the Km0 Newsstand project, an initiative launched to enhance and promote the biocultural heritage of the Tuscany region through the direct sale of traditional agricultural products, local food specialities and crafts, as well as related services in newsstands. We adopted a mixed-methods approach to conduct an in-depth analysis of this innovative SFSC model. To investigate the perspective of producers and retailers, we developed a Strengths, Weaknesses, Opportunities, and Threats analysis and also a Social Business Model Canvas of this newly designed business model by collecting and analysing existing documents and carrying out in-depth interviews with key informants. On the demand side, we implemented an online survey (N = 1000) to explore the factors influencing the intention of consumers to use the Km0 Newsstand services, along with potential drivers and barriers for their purchasing behaviour. Results show how the model ensures a balance between financial sustainability and the mission of promoting sustainable local consumption while fostering economic, social, and environmental benefits for all stakeholders involved.

The large retail chains represent the main distribution channel for wine sales in Italy. Retailers, therefore, define the wine supply of their points-of-sale based on their own commercial strategies, taking into account evolving consumer demand, producer characteristics, and product types. Wine bottles from different producers with varying characteristics, sales performances, and commercial trends can be found on shelves next to each other. The aim of this study is to investigate the performance of various producers whose wines were sold in large retail chains in Italy before the pandemic. This analysis enabled us to observe market trends without disruptions. We focused on the two most sold Protected Designation of Origin (PDO) wines, Chianti DOCG and Montepulciano d’Abruzzo DOC. For this purpose, cluster segmentation was implemented using variables related to sales (value of sales, number of labels, average price, discount units, discount percentage, units sold above a certain price), and sales trends of each producer present in large retail chains with these products. The results show that, although there are different trends and commercial strategies among the producers of each of the two denominations of origin, there are similarities between the clusters of the two different denominations. In particular, in the domain of large-scale retail, wine sales are dominated by a few wineries with a strategy based on high sales volume, a wide range of labels, low prices, and promotional sales. The remaining sales refer to wines from producers with different characteristics that record positive sales trends and producers characterised by the declining value of sales. The identified results provide valuable insights for a better understanding of the dynamics of the large retail chain in Italy.

In recent years, European consumers have increasingly concentrated their fish consumption on a few marine species, which have a high monetary value. Unfortunately, the intensive fishing pressure exerted on few species can jeopardize the stability of marine ecosystems and produce a huge amount of discarded fishes. To address this, promoting the consumption of low-commercial-value fish could be a solution to foster responsible and sustainable consumption. As these species are not easy to handle and require time and cooking skills to be prepared, we tested the use of implicit conditioning tools to promote the consumption of low-market-value fish in restaurants. Therefore, a choice experiment was conducted on a sample of 774 Italian consumers. The participants were randomly divided into two information treatments plus a control group. They were presented with a menu containing one option with low-market-value fish species, selecting fish soup as a traditional and recognizable dish, thereby proposing a familiar dish option that can include such species and facilitate consumer acceptance. The low-market-value fish option was accompanied by a small image and a message highlighting its sustainability (first group) or traditionality (second group). The results indicated that the instrument related to traditionality was the only one effective in influencing consumer choices toward the low-market-value fish option, particularly for high-income consumers. Other consumer segments, such as those who care about the environment, were not particularly susceptible to the environmental cue.

The purpose of this study was to provide a detailed framework of wine purchases in supermarkets during the COVID-19 pandemic. The unexpected diffusion of the virus and the restrictions imposed in Italy to prevent its spread have significantly affected the food purchasing habits of consumers. By analyzing the scanner data of the wine sales in the Italian mass market retail channel, this study was intended to show whether and how the dynamics triggered by the pandemic have modified the overall value and type of wine purchases, focusing on prices, formats, and promotional sales. In particular, this study explores sales in two separate periods, namely March–April (the “lockdown”, with general compulsory closing and severe restrictions) and June–July 2020 (the “post-lockdown”, in which some limitations were no longer effective). The analysis of wine sales during lockdown and post-lockdown and the study of the variations compared to the sales of the previous years showed some significant changes in purchase behavior. The results could provide managers, researchers, and policy makers with extensive insights into the purchasing patterns of consumers during this unprecedented time and reveal trends that may characterize the structure of the future wine demand.

In some Anglo-Saxon countries, such as Australia and the United States, initiatives have already emerged to promote standardized evaluation practices. However, in Italy, this process is still evolving. Since 1994, the International Valuation Standards Committee (IVSC) has been working on various documents to establish uniform evaluation practices globally. These International Valuation Standards (IVS) are gradually gaining recognition in Italy. Through the efforts of organizations like ABI, Tecnoborsa, the Revenue Agency, and professional associations, IVS are being integrated into evaluation practices for credit approval and public administration requirements.

Rural areas play a crucial role in achieving sustainable development, yet they face persistent and recurring social issues such as demographic decline, limited access to essential services, and economic stagnation. Framed on community revitalization and place-based development, this study examines the factors influencing quality of life in marginal rural areas at high risk of abandonment, focusing on Basilicata and Tuscany—two Italian regions with distinct socio-economic profiles. Adopting a qualitative approach, semi-structured interviews were conducted with local stakeholders to capture their lived experiences and perceptions of rural well-being and development opportunities. The analysis, supported by textual data processing, highlights shared and region-specific challenges. Key themes include service accessibility, demographic dynamics, economic opportunities, and governance capacity. Findings reveal that while both regions emphasize essential services and economic revitalization, their approaches differ: Basilicata stakeholders stress infrastructural deficits and demographic decline, whereas Tuscany stakeholders highlight rural diversification and place-based initiatives. These insights underscore the importance of local stakeholder perceptions in shaping rural development strategies. The study contributes to theoretical debates on rural well-being by demonstrating how stakeholder perspectives influence policy priorities and intervention strategies. It advocates for place-sensitive policies that enhance institutional capacity and leverage regional assets to promote sustainable rural community revitalization. These findings support the need for a context-specific approach to rural policy that integrates both qualitative and quantitative measures of well-being.

This study analyses the impacts of the COVID-19 pandemic on food consumption at the end of the first lockdown in the New York State (USA) and in Italy (spring 2020). The results of our study show that important changes occurred in food habits in these two countries, in which lockdown was very similar. Three models of response to the shock of the lockdown were noted in both countries. The first model (40%) includes individuals who largely increased their food consumption, the second model (26%) showed a more virtuous and responsible behaviour, while the third model (34%) displayed no change in food consumption. Diet quality in terms of healthiness and sustainability declined in the USA, while in Italy, approximately one-third of the sample showed an improvement in diet in these same areas. The use of sociodemographic, motivational, and behavioural variables to profile subjects who adhered to each food model has made it possible to obtain information that can be used to develop communication campaigns and policies for a healthier and more sustainable diet.

Estimating the 3D shape of objects from monocular images is a well-established and challenging task in the computer vision field. Further challenges arise when highly deformable objects, such as human faces or bodies, are considered. In this work, we address the problem of estimating the 3D shape of a human body from single images. In particular, we provide a solution to the problem of estimating the shape of the body when the subject is wearing clothes. This is a highly challenging scenario as loose clothes might hide the underlying body shape to a large extent. To this aim, we make use of a parametric 3D body model, the SMPL, whose parameters describe the body pose and shape of the body. Our main intuition is that the shape parameters associated with an individual should not change whether the subject is wearing clothes or not. To improve the shape estimation under clothing, we train a deep convolutional network to regress the shape parameters from a single image of a person. To increase the robustness to clothing, we build our training dataset by associating the shape parameters of a “minimally clothed” person to other samples of the same person wearing looser clothes. Experimental validation shows that our approach can more accurately estimate body shape parameters with respect to state-of-the-art approaches, even in the case of loose clothes.