Raffaele Scuderi

Visitors to two types of museums: do expenditure patterns differ?

The authors study the determinants of the expenditure behaviour of visitors to two types of museums. Ad hoc surveys were conducted between June and September 2011 of visitors to the South Tyrol Museum of Archaeology and the Museum of Modern and Contemporaneous Art of Trento and Rovereto (MART). These are the two principal museums in the Italian provinces of Bolzano and Trento. The double-hurdle model is used via the Heien and Wessels two-step estimator. This procedure splits the process of spending decision into the stages of ‘selection’ and ‘outcome’, and also results in consistent estimates. The findings highlight two distinct profiles. The spending of visitors to the modern art museum is positively related to its cultural interest, whereas the expenditure profile of the archaeological museum visitors is more ‘generalist’.

Segmenting visitors of cultural events: The case of Christmas Market

Abstract Market segmentation in tourism makes use of sets of powerful analytical tools for the sake of planning and managing demand-oriented policies. This paper contributes to this strand of literature by segmenting tourists visiting a cultural event. We utilize the Bagged Clustering method, a combination of traditional partitioning and hierarchical techniques, which is proven to be more effective. An ad hoc survey was conducted in 2011 among the Italian visitors of the Christmas Market in Merano, Northern Italy. A total of 802 questionnaires were collected. In discussing the results, marketing and managerial implications are stressed for both policymakers and local organizers.

Scad-elastic net and the estimation of individual tourism expenditure determinants

This paper introduces the use of scad-elastic net in the assessment of the determinants of individual tourist spending. This technique approaches two main estimation-related issues of primary importance. So far studies of tourism literature have made a wide use of classic regressions, whose results might be affected by multicollinearity. In addition, because of the absence of robust economic theory on tourism behavior, regressor selection is often left to researchers choice when not driven by non-optimal automatic criteria. Scad-elastic net is an OLS model that accounts for both these problems by including two types of parameters constraints, namely the smoothly clipped absolute deviation (scad) and the ?2-norm. We analyze an official dataset of incoming tourists to Uruguay. Socio-demographic, psychographic and trip-related variables are used as explanatory of per capita per day tourist expenditure. Significant impact on tourism expenditure of some accommodation facilities such as expensive one and second dwellings, personal experiences rather than the number of past visits, doing certain activities, place of stay, and seasonality are the main conclusions that are drawn from the analysis. We use scad-elastic net to analyze tourist expenditure in Uruguay.Our penalized regression approaches overcome some limitations of classic models.The technique handles multicorrelation and regressor selection.Accommodation is crucial to predict levels of spending.Space and seasonality effect also emerge.

Learning at the museum: Factors influencing visit length

Museum attendance is often seen as a chance for visitors to learn and thus increase their cultural capital. However, a share of the visitors may decide to attend museums for reasons other than cultural capital accumulation. This article investigates whether learning process takes place also in the case of tourists whose main motivation for the visit is recreational. Different attitudes towards cultural consumption may have a role in explaining visit length, seen as a proxy for learning. We present an empirical analysis of the determinants of both willingness to stay and actual length of stay at a museum. Evidence is based on a survey of tourists visiting the Italian museum of Vittoriale. Generalized ordered logit under partial proportional odds assumption and Cox proportional hazard models are used to assess the role of the covariates. A set of economic, socio-demographic, trip-related and psychographic controls is tested, with particular emphasis on motivation.

Dynamics of internationalisation of the hotel industry: the case of Spain

Purpose – This paper aims provides an empirical analysis of the development of the internationalisation process in the Spanish hotel industry, which has experienced major changes during the past decade. The degree of internationalisation between 2000 and 2010 is used as a proxy variable with the aim of mapping the development of international strategies. Design/methodology/approach – A longitudinal dataset measuring the internationalisation of Spanish hotel chains is used. Cluster analysis identifies the different behaviour of groups of firms during the analysed period. Findings – Two different clusters are detected, which can be attributed to different internationalisation strategies over time. Small and medium (SME) hotel companies seem to follow a different path of development than more established multinational companies. Over time, the entire group tends to be more compact, whereas the distance between the clusters is shown to diverge in final years. The groups’ composition suggests that business-net...

ClustOfVar and the segmentation of cruise passengers from mixed data

The ClustOfVar algorithm is applied to segment cruise tourists.The technique is suitable for mixed qualitative and quantitative variables.Clusters of cruise visitors to Uruguay are detected and analysed.Economic impact is linked to positive perception of local people.Port of call and age are main discriminators of groups. Market segmentation comprises a variety of measurement methodologies that are used to support management, marketing and promotional policies in tourism destinations. This study applies ClustOfVar, a relatively recent algorithm for cluster analysis from mixed variables. The technique finds groups of variables by using a homogeneity criterion based on the sum of correlation ratios for qualitative variables, and squared correlations for quantitative variables. Then principal components from each cluster of variables are extracted in order to segment cruise passengers. CART analysis is finally used for the sake of finding the variables that drove the formation of the clusters. All the analysis is based on an official survey of tourists who disembarked in Uruguayan ports. The analysis identified five clusters, both for variables and cruise passengers. Findings highlight the importance of the enjoyment of the contact with local people for the economic impact, as well as the important role of age and gender related variables. Managerial implications are also discussed.

An examination of tourist arrivals dynamics using short-term time series data: a space-time cluster approach

The purpose of this study is to examine the development of Italian tourist areas (circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an increasing trend.

Assessing the Beneficial Effects of Economic Growth: The Harmonic Growth Index

In this paper we introduce the multidimensional notion of harmonic growth as a situation of diffused well-being associated to an increase of per capita GDP. We say that a country experienced a harmonic growth if during the observed period all the key indicators, proxies of the endogenous and exogenous forces driving population well-being, show a significantly common pattern with the income dynamics. The notion is operationalized via an index of time series harmony which follows the functional data analysis approach. This Harmonic Growth Index (HGI) is based on comparisons between the coefficients from cubic B-splines interpolation. Such indices are then synthesized in order to provide the global degree of harmony in growth inside a country. With an accurate selection of the key indicators, the index can be used also to rank countries thus offering a useful complementary information to the Human Development Indexes from UNDP. An exemplification is given for the Indian economy.

Short Term Dynamics of Tourist Arrivals: What Do Italian Destinations Have in Common?

This work aims to detect the common short term dynamics to yearly time series of 413 Italian tourist areas. We adopt the clustering technique of Abraham et al. (Scand J Stat. 30:581–595, 2003) who propose a two-stage method which fits the data by B-splines and partitions the estimated model coefficients using a k-means algorithm. The description of each cluster, which identifies a specific kind of dynamics, is made through simple descriptive cross tabulations in order to study how the location of the areas across the regions or their prevailing typology of tourism characterize each group.

A Measure of Polarization for Tourism: Evidence from Italian Destinations

This paper proposes an index of polarization for tourism which links the axiomatic theory of Esteban and Ray with the classical hierarchical agglomerative clustering techniques. The index is aimed at analyzing the dynamics of the average length of stay across Italian destinations, and more specifically to detect whether the polarization within the set of clusters of places with similar values of the indicator has varied over time.