Consumer attitudes and preference exploration towards fresh-cut salads using best–worst scaling and latent class analysis

This research explored the preferences and buying habits of a sample of 620 consumers of fresh-cut, ready-to-eat salads. A best–worst scaling approach was used to measure the level of preference stated by individuals regarding 12 attributes for quality (intrinsic, extrinsic and credence) of fresh-cut salads. The experiment was carried out through direct interviews at several large-scale retail outlets in the Turin metropolitan area (north-west of Italy). Out of the total number of questioned consumers, 35% said they did not consume fresh-cut salads. On the contrary, the rest of the involved sample expressed the highest degree of preference towards the freshness/appearance attribute, followed by the expiration date and the brand. On the contrary, attributes such as price, organic certification and food safety did not emerge as discriminating factors in consumer choices. Additionally, five clusters of consumers were identified, whose preferences are related both to purchasing styles and socio-demographic variables. In conclusion, this research has highlighted the positive attitude of consumers towards quality products backed by a brand, providing ideas for companies to improve within this sector and implement strategies to answer the needs of a new segment of consumers, by determining market opportunities that aim to strengthen local brands

Animal welfare and gender: a nexus in awareness and preference when choosing fresh beef meat?

The modern consumer is now more attentive towards animal welfare practices and this represents an important factor when purchasing meat, whereby ethical, sociological and economic implications are evaluated. In addition, the socio-demographic characteristics of consumers evidence different sensitivities with regard to selection patterns and consumption styles. This study aims to explore the role of Gender in beef meat purchasing preferences, assessing consumer awareness of responsibility towards animal welfare, through the use of cross-tabulation with χ2 to test the different behaviour of men and women and the use of principal component analysis and cluster analysis to classify attitudes of choice according to gender. Among the research aims, this study examined consumer attitudes towards certain 'ethically incorrect' animal products, as well as their awareness of the institutional responsibility in controlling animal welfare standards during the meat production process. The study conducted in Northwest Italy, involving 512 respondents, shows that women are more sensitive to AW aspects and place trust in those responsible for certification of animal welfare standards, such as veterinarians and consumer associations, and also shows that it is possible to identify an 'animal welfare sensitive' profile of meat consumer.HIGHLIGHTS Modern consumer evaluates ethical, sociological and economic implications in animal friendly meat purchasing process Gender affects awareness of the responsibilities of veterinary, public health control bodies and consumer associations to verify animal welfare Cluster highlighted consumer differences in perception towards animal welfar

A new beach topography-based method for shoreline identification

The definition of shoreline is not the same for all contexts, and it is often a subjective matter. Various methods exist that are based on the use of different instruments that can determine and highlight a shoreline. In recent years, numerous studies have employed photogrammetric methods, based on different colours, to map the boundary between water and land. These works use images acquired by satellites, drones, or cameras, and differ mainly in terms of resolution. Such methods can identify a shoreline by means of automatic, semi-automatic, or manual procedures. The aim of this work is to find and promote a new and valid beach topography-based algorithm, able to identify the shoreline. We apply the Structure from Motion (SfM) techniques to reconstruct a high-resolution Digital Elevation Model by means of a drone for image acquisition. The algorithm is based on the variation of the topographic beach profile caused by the transition from water to sand. The SfM technique is not efficient when applied to reflecting surfaces like sea water resulting in a very irregular and unnatural profile over the sea. Taking advantage of this fact, the algorithm searches for the point in the space where a beach profile changes from irregular to regular, causing a transition from water to land. The algorithm is promoted by the release of a QGIS v3.x plugin, which allows the easy application and extraction of other shorelines