Francesca De Battisti

Robust analysis of bibliometric data

This work stems from the idea of describing the scientific productivity of Italian statisticians. There are several problems that must be addressed in achieving this goal: What data should be used? Have the data been cleaned? What techniques can be used? We propose the use of multiple sources and multiple metrics to get a complete information base. We check the correctness of the data using multivariate outlier identification techniques. We appropriately transform the data. We apply robust clustering to verify the existence of homogeneous groups. We suggest the use of forward search to establish a ranking among scholars. The proposed methodology, which, in this case, allowed us to group scholars into four homogeneous groups and sort them according to multidimensional data, can be applied to other similar applications in bibliometrics.

The Rasch Model to Measure Service Quality

In this paper the Rasch model will be considered, a statistical tool arising from psychometric field, which allows the examination of the service quality through the known variables: for each of those an objective measure is obtained. In particular, the application of Rasch model will concern the quality of university teaching. Moreover a method will be proposed to obtain a segmentation of student population only based on satisfaction index

The Rasch Model in Customer Satisfaction Survey Data

Abstract This paper deals with the measurement of a service or product quality using Customer Satisfaction Survey results. Many different methods are used to analyse customer satisfaction data. Some use statistical models which estimate the relationship between the latent and manifest variables (LISREL, PLS, etc.), whilst others use dimensionality reduction methods (FA, PCA, etc.). All of these methods require a numerical quantification of the categories and consequently the distance between the numerical labels is fixed and the linear relationship between the variables implicitly assumed. Moreover these methods produce a customer satisfaction measure for each subject and an evaluation of its importance on the satisfaction level for each item. When analyzing quality and satisfaction levels together, the Rasch model (RM) appears to be particularly appropriate. A Likert scale is not required and non-linear relationships are involved. Moreover, a Rasch analysis can also act as a useful diagnostic tool for calibrating the questionnaire itself. In this paper we will present three different applications of the Rasch Model for the purposes of measuring quality and customer satisfaction levels. For each technique we will highlight its peculiarities, give an interpretation of the parameters used, analyse the model’s fit with the data and perform a critical analysis of the results.

A decade of research in statistics: a topic model approach

Topic models are a well known clustering approach for textual data, which provides promising applications in the bibliometric context for the purpose of discovering scientific topics and trends in a corpus of scientific publications. However, topic models per se provide poorly descriptive metadata featuring the discovered clusters of publications and they are not related to the other important metadata usually available with publications, such as authors affiliation, publication venue, and publication year. In this paper, we propose a methodological approach to topic modeling and post-processing of topic models results to the end of describing in depth a field of research over time. In particular, we work on a selection of publications from the international statistical literature, we propose an approach that allows us to identify sophisticated topic descriptors, and we analyze the links between topics and their temporal evolution.

Effects of interpersonal trust, corporate sustainability and propensity to trust on impersonal trust

Past research acknowledges that impersonal trust emanates from employees’ perception that they have been treated fairly by their organization. The present study seeks to advance this knowledge by demonstrating the role of further factors, i.e. (i) perception that they have been treated fairly by organizational intermediaries – supervisors and colleagues; (ii) perception that any stakeholder is treated fairly by the organization; and (iii) a dispositional propensity to trust others, regardless of information on organizational fairness. The results, obtained through a questionnaire administered to a probabilistic sample of 6,000 employees in six European countries, show that (i) the variables hypothesized are all significant antecedents of impersonal trust, and (ii) the forms of interpersonal trust towards supervisors and colleagues are both relevant, but present specificities that suggest to consider them separately. The implications of the findings are discussed, as well as limitations of the study and av...