86 research outputs found
Covid-19 and Possible Bias in Statistical Information: Pandemic Indicators and the Risk of Infodemic
No full textAbstract. A widely discussed theme at this time in Italy concerns the statistical data used to evaluate the Covid-19 trend, given that some indicators have had considerable influence in determining policy choices. The statistical collection can produce an infodemic process that we must counteract and avoid. In some cases, information on the effects of Covid-19 is difficult to obtain, and data are not always scientifically collected. Pandemic data are often analysed without being standardised, or do not have an established definition. Some indicators are difficult to measure, while the use of a single recognised measure would help to better understand the effects of the pandemic. Moreover, the way in which statistical information on Covid-19 is disseminated also contributes to create a framing that can affect the use of the variables (or indicators) analysed. The correct use and interpretation of indicators becomes relevant when an increasing amount of information contains measurement errors due to non-structured data or interpretative framing. The aim of the article is to identify the potential bias that can be generated by reading pandemic data. The entire process of statistical collection, including its communication, should be monitored because good public choices should depend on the correct use of statistics
Il Turismo delle radici in Italia. Origini, caratteristiche e opportunità per i territori.
No full textThe roots' tourism represents a tourism sector characterised by great potential,
largely unexpressed and still little exploited2. This research aims to provide useful
reflections on the development of a sector that is still insufficiently known and may
have important developments. The catchment area that can be part of the roots'
tourism is constantly increasing due to the dynamics of external migration that have
historically characterised our country. The tourism of the roots, just as a reflection
of the past, prefers middle-aged people who, in addition to the availability of time
and resources, have a strong identity vocation. But the available statistical
information fails to define this phenomenon's characteristics exhaustively.
Moreover, roots' tourism seems to express a different idea of tourism, less linked
to leisure tourism. The tourism of the roots is, in fact, mainly linked to the culture of
the territories. The narrative, also through digitalisation, becomes an opportunity to
know their roots in a sustainability perspective because there can be no future
without knowing their past
Predicting Domestic Tourists’ Length of Stay in Italy leveraging Regression Decision Tree Algorithms
No full textThis study innovates in predicting domestic tourists’ Length of Stay (LoS)
in Italy by using decision tree models, addressing the gap in understanding
LoS’s determinants, and improving upon inconsistent results from traditional
parametric analyses. Utilizing the 2019 “Viaggi e Vacanze” survey by the
Italian National Institute of Statistics and categorizing variables into sociodemographic, economic, travel-related, and psychological factors, the research
applies one-hot encoding to analyse 48,410,000 trips. Through evaluating
random forest and gradient boosting models, the study highlights their superiority in identifying complex data patterns, offering actionable insights for
tourism policymakers. These models enable precise LoS estimation, facilitating enhanced strategic planning for extending stays, optimizing services, and
improving promotional efforts to maximize tourism’s economic impact. This
approach offers a comprehensive tool for developing policies that boost visitor engagement and economic benefits, showcasing a significant advancement
in tourism management practices
Predicting Domestic Tourists’ Length of Stay in Italy leveraging Regression Decision Tree Algorithms
No full textL’INTEGRAZIONE DEI DATI PER UNA INFORMAZIONE STATISTICA ESAUSTIVA PER L’ANALISI PREVISIONALE. APPLICAZIONI NEL TURISMO
No full textPredictive modelling of length of domestic stays in Italy: A comparative study of machine learning techniques
No full text
Development of an integrated data system for regional tourism analysis in Italy: A microdata perspective
No full textThis paper presents the development of an integrated data system tailored for the Italian regions, combining
microdata from the Bank of Italy’s and ISTAT’s surveys. These datasets offer an in-depth analysis of both domestic and international aspects of tourism, framed within the theoretical context of the tourism determinants.
By merging this integrated dataset with additional data from other statistical sources, this study offers a
queryable relational database enabling granular regional analysis. Currently, tourism statistics in Italy are
fragmented and do not provide a unified picture of tourism in its many aspects. The relational model’s interoperability addresses Italy’s fragmented tourism data landscape, and its data definition language represents an
important step towards the creation of a unified tourism archive. Micro-data allows for different statistical analyses than those usually carried out with aggregated data, increasing knowledge of the dynamics of the sector
The Role of Demographic and Environmental Factors in the Outbreak of COVID-19 Across Italian Provinces
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