Cristina Davino

Cristina Davino
University of Naples Federico II | UNINA · Department of Economics and Statistics

Professor
Associate Professor of Statistics

About

57
Publications
6,323
Reads
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427
Citations
Citations since 2017
24 Research Items
294 Citations
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Introduction
Cristina Davino currently works at the Department of Economics and Statistics, University of Naples Federico II. Cristina does research in Statistics (Multivariate Analysis, Composite indicators, Quantile Regression)
Additional affiliations
November 2009 - November 2011
University of Macerata
Position
  • Professor (Associate)
Description
  • Evaluation of social services
November 2005 - present
University of Macerata
Position
  • Professor (Associate)
Description
  • Social Statistics
November 2000 - present
University of Macerata
Position
  • Professor (Associate)
Description
  • Statistics
Education
November 1994 - March 1998
University of Naples Federico II
Field of study
  • Statistics
November 1989 - March 1994
University of Naples Federico II
Field of study
  • Statistics

Publications

Publications (57)
Article
Full-text available
Quantile composite-based path modeling is a recent extension to the conventional partial least squares path modeling. It estimates the effects that predictors exert on the whole conditional distributions of the outcomes involved in path models and provides a comprehensive view on the structure of the relationships among the variables. This method c...
Article
Full-text available
External preference mapping is widely used in marketing and R&D divisions to understand the consumer behaviour. The most common preference map is obtained through a two-step procedure that combines principal component analysis and least squares regression. The standard approach exploits classical regression and therefore focuses on the conditional...
Article
Full-text available
In many fields of applications, linear regression is the most widely used statistical method to analyze the effect of a set of explanatory variables on a response variable of interest. Classical least squares regression focuses on the conditional mean of the response, while quantile regression extends the view to conditional quantiles. Quantile reg...
Book
Full-text available
The volume collects the papers presented at the conference “Stat.Edu’21 -New Perspectives in Statistics Education” which was held at the Department of Political Sciences of the University of Naples Federico II (25-26 March 2021). The conference was the final event of the “ALEAS - Adaptive LEArning in Statistics”, an ERASMUS+ project (https://aleas-...
Article
Full-text available
Composite-based path modeling aims to study the relationships among a set of constructs, that is a representation of theoretical concepts. Such constructs are operationalized as composites (i.e. linear combinations of observed or manifest variables). The traditional partial least squares approach to composite-based path modeling focuses on the cond...
Article
Full-text available
This article proposes a quantitative analysis to measure social vulnerability in a urban space, specifically in the area of the Municipality of Rome. Social vulnerability can be defined as a situation in which people are characterized by a condition of multidimensional deprivation that encompasses multiple aspects of life and exposes population to...
Chapter
Full-text available
This book includes 25 peer-reviewed short papers submitted to the Scientific Opening Conference titled “Statistics and Information Systems for Policy Evaluation”, aimed at promoting new statistical methods and applications for the evaluation of policies and organized by the Association for Applied Statistics (ASA) and the Department of Statistics,...
Chapter
Full-text available
This book includes 40 peer-reviewed short papers submitted to the Scientific Conference titled Statistics and Information Systems for Policy Evaluation, aimed at promoting new statistical methods and applications for the evaluation of policies and organized by the Association for Applied Statistics (ASA) and the Dept. of Statistics, Computer Scienc...
Conference Paper
Full-text available
Over the years, several studies have shown the relevance of one-to-one compared to one-to-many tutoring, shedding light on the need for technology-based platforms to assist traditional learning methodolo-gies. Therefore, in recent years, tutoring systems that collect and analyse responses during the user interaction for an automated assessment and...
Article
Full-text available
The aim of the paper is to propose a quantile regression based strategy to assess heterogeneity in a multi-block type data structure. Specifically, the paper deals with a particular data structure where several blocks of variables are observed on the same units and a structure of relations is assumed between the different blocks. The idea is that q...
Article
Massive Open Online Courses, universally labelled as MOOCs, become more and more relevant in the era of digitalization of higher education. The availability of free education resources without access restrictions for a plenty of potential users has changed the learning market in a way unthinkable only few decades ago. This form of web-based educati...
Article
Full-text available
This paper analyzes the determinants of stated individual support towards environmental action. The analysis is realized by means of an original Partial Least Squares Path model of Environmental Awareness-Social Capital-Action and it is based on survey data provided in the fifth wave of the World Values Survey (2005–2009) regarding 34.612 individua...
Conference Paper
Full-text available
Massive Open Online Courses (MOOCs) phenomenon is the new frontier of online learning, where unlimited time and no location restrictions allow users to follow different strategies of learning. In the learning analytics literature there are many contributes dealing on how MOOC learners' behaviour affects their performance and influences reaching the...
Chapter
Teaching mediated by computers allows tracing some forms of students’ participation as all their actions/reactions are recorded including time spent on any pedagogical resource offered. For a quiz, response time provides an additional variable enriching the simple correctness of answers. The present study intends to describe and model different pat...
Conference Paper
This paper considers the visual arts as an external source for luxury brands to draw positive associations and strengthen brand value from a consumer-based perspective. The artification process that stems from luxury and art collaboration is analysed at brand level. The article goes beyond the art-infusion effect hypothesis. The experiment consider...
Article
Full-text available
An interesting measure for equitable and sustainable well-being has been proposed recently by the National Institute of Statistics in Italy and the National Council for Economy and Labour. It is called BES (from the Italian Benessere Equo e Sostenibile). A set of indicators, partitioned into several domains and themes, is used for measuring the BES...
Article
In many real data applications, statistical units belong to different groups and statistical models should be tailored to incorporate and exploit this heterogeneity among units. This paper proposes an innovative approach to identify group effects through a quantile regression model. The method assigns a conditional quantile to each group and provid...
Chapter
The aim of the present chapter is to discuss a recent contribution in the partial least squares path modeling framework: the quantile composite-based path modeling. We introduce this recent contribution from both a methodological and an applicative point of view. The objective is to provide an exploration of the whole dependence structure and to hi...
Conference Paper
The paper aims to introduce assessment and validation measures in Quantile Composite-based Path modeling. A quantile approach in the Partial Least Squares path modeling framework overcomes the classical exploration of average effects and highlights how and if the relationships among observed and unobserved variables change according to the explored...
Article
The paper aims at introducing a quantile approach in the Partial Least Squares path modeling framework. This is a well known composite-based method for the analysis of complex phenomena measurable through a network of relationships among observed and unobserved variables. The proposal intends to enhance potentialities of the Partial Least Squares p...
Article
The authors of this paper propose a method, based both on confirmatory and exploratory data analysis, aiming to assess the variability arising from the Composite Indicators (CIs) construction process. This research refers to an evaluation exercise very important for universities: the assessment of scientific research. The aim of every evaluation sy...
Chapter
This paper aims to propose an innovative approach to identify a typology in a quantile regression model. Quantile regression is a regression technique that allows to focus on the effects that a set of explanatory variables has on the entire conditional distribution of a dependent variable. The proposal concerns the use of multivariate techniques to...
Article
Full-text available
The synthesis of a number of single observed indicators into a unique composite indicator involves various subjective choices related, for instance, to the type of combination (linear, non-linear) and to the aggregation method (simple average, geometric average) used in its construction. Thus, it is clearly important to analyse the variability of a...
Chapter
Given its properties, quantile regression (QR) can be considered a versatile method for use in several frameworks, unlike the classical regression model. This chapter deals with the main extensions of QR: its application in nonparametric models and nonlinear relationships among the variables, in the presence of censored and longitudinal data, when...
Chapter
Quantile regression is a statistical analysis that does not restrict attention to the conditional mean and therefore permits to approximate the whole conditional distribution of a response variable. This chapter offers a visual introduction to quantile regression (QR) starting from the simplest model with a dummy predictor, moving then to the simpl...
Chapter
This chapter focuses on the quantile regression estimators for models characterized by heteroskedastic and by dependent errors. It considers the precision of the quantile regression model in the case of independent and identically distributed (i.i.d.) errors, taking a closer look at the computation of confidence intervals and hypothesis testing on...
Chapter
The development and dissemination of quantile regression (QR) started with the formulation of the QR problem as a linear programming problem. Such formulation allows to exploit efficient methods and algorithms to solve a complex optimization problem offering the way to explore the whole conditional distribution of a variable and not only its center...
Chapter
This chapter shows the behavior of quantile regressions in datasets with different characteristics. Using simulated data, the chapter also shows the empirical distribution of the quantile regression estimator in the case of independent and identically distributed (i.i.d.) errors, non-identically distributed (i.ni.d.) errors and dependent (ni.i.d.)...
Chapter
To appreciate the meaningful potentialities of quantile regression (QR), it is necessary to have a greater understanding of the interpretations and the evaluation tools. This chapter deals with some typical issues arising from a real data analysis, highlighting the capability of QR and its differences compared with other methods. It discusses the e...
Article
The main objective of this paper is to describe and discuss the use of classification trees in consumer studies. Focus will be given to the use of the method in relating segments of consumers, based on their acceptance pattern, to additional consumer characteristics, including attitudes, habits and demographics variables. Advantages of the method i...
Chapter
Full-text available
In this paper a method for assessing different multi-item scales in sub-jective measurement is described and discussed. The method is a combination of analysis of variance models and multivariate techniques. It allows us comparisons among the scales by considering the multivariate information provided by the items. Focus is given on the way individ...
Book
Statistical surveys represent an important source of scientific knowledge and a valid decision support tool in many fields, from social studies to economics, market research, health studies, and others. Scientists have tackled most of the methodological issues concerning surveys and the scientific literature offers excellent proposals for planning...
Article
A guide to the implementation and interpretation of Quantile Regression models. This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensive description of the main iss...
Chapter
Full-text available
The paper proposes a multivariate approach to study the dependence of the scientific productivity on the human research potential in the Italian University system. In spite of the heterogeneity of the system, Redundancy Analysis is exploited to analyse the University research system as a whole. The proposed approach is embedded in an exploratory da...
Conference Paper
The aim of this paper is to provide a Structural Neural Network to model Customer Satisfaction in a business-to-business framework. Neural Networks are proposed as a complementary approach to PLS path modeling, one of the most widespread approaches for modeling and measuring Customer Satisfaction. The proposed Structural Neural Network allows to ov...
Article
Association Rules (Agrawal et al., 1993) represent a consolidated tool in data mining applications. They allow to find frequent patterns and associations in large databases characterized by the presence of a set of transactions, where each transaction is a subset of items. Nowadays, the considerable advances in the computational field allow to anal...
Article
Full-text available
The paper aims to analyse the internal effectiveness of an niversity educational process by means of quantile regression. In particular, the goal is to evaluate how the students features affect the utcome of the University careers taking into account that this effect can be different for students with good or bad performances.
Book
Full-text available
Il volume presenta i risultati dell’attività dell’Osservatorio sulla qualità della vita e la vivibilità nelle Circoscrizioni di Napoli. L’Osservatorio, istituito nel 2002 con l’obiettivo di monitorare i diversi aspetti che incidono sulla vita economica, sociale e culturale della città (Costo della vita; Ambiente, territorio e sicurezza; Trasporti e...
Article
Association rules (AR) represent a consolidated tool in data mining applications as they are able to discover regularities in large data sets. The information mined by the rules is very often difficult to exploit because of the presence of too many associations where to detect the really relevant logical implications. In this framework, by combinin...
Article
Full-text available
Nowadays mining association rules in a database is a quite simple task; many algorithms have been developed to discover regularities in data. The analysis and the interpretation of the discovered rules are more difficult or almost impossible, given the huge number of generated rules. In this paper we propose a three step strategy to select only int...
Chapter
Nowdays neural networks (NN) are applied in the most various fields and are actually receiving a lot of attention among the researcher’s community. In this paper we will provide a review of some NN applications in economics. We distinguish the applications according to the main objectives achieved by NN in this field: prediction, classification and...
Article
Although neural networks have been borned in engineering field they are actually receiving a lot of attention among the statisticians. This paper provides an overview on supervised and unsupervised neural networks modeling with particular attention to their use and overuse in statistics. The performance of neural networks with respect to tree-growi...
Chapter
Full-text available
Association Rules are one of the most widespread data mining tools because they can be easily mined, even from very huge database, and they provide valuable information for many application fields such as marketing, credit scoring, business, etc. The counterpart is that a massive effort is required (due to the large number of rules usually mined) i...

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Projects

Projects (2)
Project
The project aims to design and implement an Adaptive LEArning system for Statistics (ALEAS) that will be used to reduce the gap spotted in Statistics courses. Targets groups of ALEAS are undergraduate university students attending first courses in statistics in several degree programs: from Psychology, to Political Science, Humanities and Social Sciences, Primary Education. ALEAS must be intended as an innovative and complementary tool with respect to the traditional courses in Statistics and it will offer personalized learning paths to students, with the purpose to provide them remedial advices to deal with the "statistics anxiety". The use of real world examples taken from the specific domains aims to motivate the students' interest and curiosity for Statistics. ALEAS will also represent a useful work tool for teachers because at the end of a course or of a learning session, it will provide statistics about the impact of the adaptive learning system on the learning capability of the class. The system will be experimented and tuned among the undergraduate classes in Statistics of the involved partners' institutions.