196,035 research outputs found
Il benessere finanziario e il modello proposto dal Consumer Financial Protection Bureau (CFPB)
No full textIl lavoro si propone di analizzare la metrica di misurazione del benessere finanziario sviluppata dall’Autorità americana di protezione degli utenti di servizi finanziari
Il benessere finanziario: il quadro teorico di riferimento e le prime analisi empiriche
No full textIl lavoro si propone di: illustrare il concetto di benessere finanziario, fornire un’analisi dei principali riferimenti in letteratura, identificare le possibili evoluzioni nella sua misurazione
Quantile dependence in tourism demand time series: Evidence in the Southern Italy market
No full textTravel and tourism is an important economic activity in most countries around the world. In 2018, international tourist arrivals grew 5% to reach the 1.4 billion mark and at the same time export earnings generated by tourism have grown to USD 1.7 trillion. The rapid growth of the tourism industry has globally attracted the interest of researchers for a long time. The literature has tried to model tourism demand to analyze the effects of different factors and predict the future behavior of the demand. Forecasting of tourism demand is crucial not only for academia but for tourism industries too, especially in line with the principles of sustainable tourism. The hospitality branch is an important part of the tourism industry and accurate passenger flow forecasting is a key link in the governance of the resources of a destination or in revenue management systems. In this context, the paper studies the interdependence of tourism demand in one of the main Italian tourist destinations, the Campania region, using a quantile-on-quantile approach between overall and specific tourism demand. Data are represented by monthly arrivals and nights spent by residents and non-residents in hotels and complementary accommodations from January 2008 to December 2018. The results of the analysis show that the hotel-accommodation component of the tourism demand appears to be more vulnerable than extra-hotel accommodation component to the fluctuations of the overall tourism demand and this feature is more evident for the arrivals than for nights spent. Moreover, the dependence on high quantiles suggests strategy of diversification or market segmentation to avoid overtourism phenomena and/or carrying capacity problems. Conversely, dependence on low quantiles suggests the use of push strategies to stimulate tourism demand. Finally, the results suggest that it could be very useful if the stakeholders of the tourism sector in Campania focused their attention on the collaboration theory
Google Trends data and transfer function models to predict tourism demand in Italy
No full textPurpose – The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making
in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends
have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the
application of the quantitative analysis on internet new data sources, proposes a prediction method using
Google Trends data based on an estimated transfer function model.
Design/methodology/approach – The paper uses the time-series methods to model and predict Google
Trends data. A transfer function model is used to transform the prediction of Google Trends data into
predictions of tourist arrivals. It predicts the United States tourism demand in Italy.
Findings – The results highlight the potential expressed by the use of big data-driven foresight approach.
Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The
two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective,
the methodological path could be applied to other tourism origin markets, to other internet search engine or
other socioeconomic and environmental contexts.
Originality/value – The study raises awareness of foresight literacy in the tourism sector. Secondly, it
complements the research on tourism demand forecasting by evaluating the performance of quantitative
forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival
predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that
could be used to make decisions
Food-Tourism relationship in the Italian destinations
No full textFood and tourism are two aspects for which Italy is famous all over the world, but today in a
globalized and highly competitive tourist system in which even the stronger destinations need to
differentiate themselves from the others, there is need policies of development capable of enhancing their
interaction. Tourism promotion, for example, can focus on food products that may stimulate export
demand, while food promotion may focus on the regional landscape and lead to a growth in tourism. Local
food is a fundamental component of a destination’s attributes, adding to the range of attractions and the
overall tourist experience (Symons, 1999). In an increasingly competitive world of tourism marketing,
every region or destination is in a constant search for a unique product to differentiate itself from other
destinations. In this paper, therefore, through the canonical correlation analysis (Hotelling, 1936), we want
to examine, at regional level, the relationship between food and tourism in Italy, in the belief that their
combination is the starting point not only for differentiating tourism destinations, but also for the use and
conservation of food local production
MULTISCALE DOCUMENTATION AND MONITORING OF L’AQUILA HISTORICAL CENTRE USING UAV PHOTOGRAMMETRY
No full textNowadays geomatic techniques can guarantee not only a precise and accurate survey for the documentation of our historical heritage
but also a solution to monitor its behaviour over time after, for example, a catastrophic event (earthquakes, landslides, ecc). Europe
is trying to move towards harmonized actions to store information on cultural heritage (MIBAC with the ICCS forms, English
heritage with the MIDAS scheme, etc) but it would be important to provide standardized methods in order to perform measuring
operations to collect certified metric data. The final result could be a database to support the entire management of the cultural
heritage and also a checklist of “what to do” and “when to do it”. The wide range of geomatic techniques provides many solutions to
acquire, to organize and to manage data at a multiscale level: high resolution satellite images can provide information in a short time
during the “early emergency” while UAV photogrammetry and laser scanning can provide digital high resolution 3D models of
buildings, ortophotos of roofs and facades and so on. This paper presents some multiscale survey case studies using UAV
photogrammetry: from a minor historical village (Aielli) to the centre of L’Aquila (Santa Maria di Collemaggio Church) from the
post-emergency to now. This choice has been taken not only to present how geomatics is an effective science for modelling but also
to present a complete and reliable way to perform conservation and/or restoration through precise monitoring techniques, as shown
in the third case study
A grid based IMS learning design player: the ELeGI case study
No full textThis paper illustrates the work done and the results achieved within the ELeGI project about the orchestration and the delivery of Learning Services lying in the GRID inside an IMS Learning Design (IMS-LD) Unit of Learning and running under an enhanced version of the CopperCore Player. The added value of GRID technologies for the creation and the execution of dynamic learning experiences is evidenced as well as the experimentation performed to overcome the original IMS-LD limitation on running services is presented. The aim of the ELeGI project is to promote and support a learning paradigm centred on the knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way through the definition and implementation of a service oriented Grid based software architecture
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