In modern workplaces, alongside physical, chemical, and biological hazards, other risks are linke... more In modern workplaces, alongside physical, chemical, and biological hazards, other risks are linked to the organisation of work and to the nature of the work itself. This paper investigates the association between workers’ well-being and both psychosocial and physical risk factors at work proposing a synthetic measure suitable to generate insights on well-being at work and on individual risk factors. Exploiting data from the European Working Conditions Survey, we select as response variable the “self-assessed health”. As this proxy of well-being is measured on a Likert scale, Ordered Probit analyses are run, and respondents’ profiles are illustrated. Then, a Principal Component Analysis is carried out to build two synthetic measures summarising the selected risk determinants. The resulting first principal components are subsequently used as synthetic indicators in further, simplified, Ordered Probit models to explain the impact of different sets of risks on perceived health. Such a m...
This study aims at analysing consumer behaviour towards online advertising, focusing on the attit... more This study aims at analysing consumer behaviour towards online advertising, focusing on the attitude defined in terms of cognitive, affective and behavioural aspects. Likert scale was employed to capture these three aspects. However, subjective attitude is often a nebulous and vague feature to deal with. To this end, adopting a fuzzy clustering procedure, first a fuzzy coding of the levels of the Likert scale is adopted. Second, the Fuzzy k-Means clustering model for fuzzy data has been employed to segment a sample of web users. Two clusters have been identified that require different marketing communication strategies.
Riassunto: Nel presente lavoro viene proposto un approccio per la individuazione di break struttu... more Riassunto: Nel presente lavoro viene proposto un approccio per la individuazione di break strutturali in serie temporali quando si dispone di se rie esplicative. Il metodo si articola in uno schema iterativo basato sull’uso alternato della analisi canonica e della regressione ad albero. In particolare, l’informazione conte nuta nelle serie esplicative viene sintetizzata, a mezzo della analisi canonica, in combinazi oni lineari. Queste ultime sono successivamente impiegate come covariate nella regressione ad albero in cui la variabile di risposta ` e la serie temporale di cui si desiderano identificare i break strutturali. La proposta sar` a illustrata mediante uno studio di simulazione.
Physica a Statistical Mechanics and Its Applications, 2013
ABSTRACT This paper addresses the topic of classifying financial time series in a fuzzy framework... more ABSTRACT This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
In modern workplaces, alongside physical, chemical, and biological hazards, other risks are linke... more In modern workplaces, alongside physical, chemical, and biological hazards, other risks are linked to the organisation of work and to the nature of the work itself. This paper investigates the association between workers’ well-being and both psychosocial and physical risk factors at work proposing a synthetic measure suitable to generate insights on well-being at work and on individual risk factors. Exploiting data from the European Working Conditions Survey, we select as response variable the “self-assessed health”. As this proxy of well-being is measured on a Likert scale, Ordered Probit analyses are run, and respondents’ profiles are illustrated. Then, a Principal Component Analysis is carried out to build two synthetic measures summarising the selected risk determinants. The resulting first principal components are subsequently used as synthetic indicators in further, simplified, Ordered Probit models to explain the impact of different sets of risks on perceived health. Such a m...
This study aims at analysing consumer behaviour towards online advertising, focusing on the attit... more This study aims at analysing consumer behaviour towards online advertising, focusing on the attitude defined in terms of cognitive, affective and behavioural aspects. Likert scale was employed to capture these three aspects. However, subjective attitude is often a nebulous and vague feature to deal with. To this end, adopting a fuzzy clustering procedure, first a fuzzy coding of the levels of the Likert scale is adopted. Second, the Fuzzy k-Means clustering model for fuzzy data has been employed to segment a sample of web users. Two clusters have been identified that require different marketing communication strategies.
Riassunto: Nel presente lavoro viene proposto un approccio per la individuazione di break struttu... more Riassunto: Nel presente lavoro viene proposto un approccio per la individuazione di break strutturali in serie temporali quando si dispone di se rie esplicative. Il metodo si articola in uno schema iterativo basato sull’uso alternato della analisi canonica e della regressione ad albero. In particolare, l’informazione conte nuta nelle serie esplicative viene sintetizzata, a mezzo della analisi canonica, in combinazi oni lineari. Queste ultime sono successivamente impiegate come covariate nella regressione ad albero in cui la variabile di risposta ` e la serie temporale di cui si desiderano identificare i break strutturali. La proposta sar` a illustrata mediante uno studio di simulazione.
Physica a Statistical Mechanics and Its Applications, 2013
ABSTRACT This paper addresses the topic of classifying financial time series in a fuzzy framework... more ABSTRACT This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
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Papers by Carmela Cappelli