In 2009 the Faculty of Economics of Foggia started a project called "Analisi della student satisfaction" with the aim to create an internal quality control system based on its students’ feedback. Every year a customer satisfaction survey is carried out, where all attending students are asked to evaluate the services provided. This paper presents an evaluation of the satisfaction degree of the students over the last two academic years. In order to understand the level of satisfaction and the psychological mechanism behind the students’ evaluation process an approach based on CUB models is adopted. At the end a multidimensional scaling has been proposed to investigate the existence of student subgroups with similar attitudes in terms of feeling and uncertainty towards the Faculty’s services and their overall satisfaction about them and eventually confirm the presence of the latent variables estimated by CUB models

A new meat burger produced from dairy cattle at the end of their milk production was proposed in this study. Dairy cattle are not used for slaughter because this meat is perceived by consumers as tough and hard difficult to chew, even if it is rich in iron and fiber, and has a high nutritional value. The new meat burger was obtained by optimizing meat formulation and a consumer test was carried out to judge its acceptability respect to a traditional meat burger. Overall acceptability and five meat sensory characteristics related to tenderness, juiciness, taste, odor and chewiness were selected and thoroughly defined for profiling. Consumers were asked to assign marks on a Likert scale for each sensory meat characteristic. A total of 215 subjects were involved in the survey. A new integrated approach was also used for evaluating the consumer acceptability, by paying attention to the psychological mechanism behind the consumers’ evaluation process. In particular, to assess how consumer judgments are influenced by their personal feeling towards the items under investigation and to evaluate the inherent uncertainty associated with the choice of the ordinal values featuring on the questionnaire responses, CUB models were used. In addition, a multidimensional scaling was proposed to confirm the presence of the latent variables estimated by CUB models and to compare different profile of evaluation. Results of this study showed the proposed integrated approach can be considered a valid tool for evaluating consumer acceptability towards new food products, thus confirming that CUB models are suitable to analyze consumer preferences by Likert scales. A good level of acceptance of the new burger was obtained, thus suggesting that this new product could represent an opportunity to exploit these livestock productions and a tool to reduce the environmental impact resulting from the disposal of animal carcasses.

Proceedings of Spatial Data Methods for Environmental and Ecological Processes – 2nd Edition, the 2011 European Regional Conference of The International Environmetrics Society and satellite of the 58th World Statistics Congress of the International Statistical Institute (ISI).

The goal of this study is to analyse the spatial distribution of a wheat production indicator in a field trial located in southeastern Italy, in order to ascertain how the plant characteristics and spatial dependence influence its quantity. In standard agronomical applications this kind of data, recorded in georeferenced locations jointly with crop and soil variables, is quite commonly mapped by using kriging with external drift. Such a predictor assumes covariates to have a linear effect on the crop response variables, but it is well known how this assumption is seldom verified and often violated in a typical agronomic trial. In this work we propose the use of geoadditive models for analysing grain weight of a wheat crop in the presence of other covariates, because these models allow the user to investigate both linear and nonlinear relationships between response and exploratory variables simultaneously with modelling. Moreover, in addition to the original geoadditive model formulation by Kammann andWand (2003), the use of the exponential and the Gaussian spatial correlation structures was explicitly considered. Different models were compared using a set of cross validation criteria. The results showed that the geoadditive model with an exponential correlation structure was preferred to kriging with external drift in terms of unbiasedness of the predictor, accuracy of the mean squared prediction and goodness of fit for this agricultural trial.