Analysing intra-destination movements and activity participation of tourists through destination card consumption

Abstract

This study investigates tourist behaviour in the Canton of Ticino Switzerland, a geographically dispersed destination, by analysing use patterns of a 'destination card' sold by the local destination management organization. Destination cards offer free or highly discounted entry into partner attractions and activities often coupled with free public transport access in the area. Within this context, the study sought to determine if evidence of concentrated behaviour existed, either spatially or by activity. Cluster analysis revealed four discrete market segments. Three of them showed a high degree of spatial concentration in their movements, augmented by some clearly defined activity preferences. The fourth showed no clear pattern, travelling widely throughout the Canton and sampling a range of activities. Hence, the combination of transport and attractions' entrance appeals to two different user groups, one looking to gain access to attractions and one seeking ease of transport. Discriminant analysis further supported the results with defining the determinant variables of the cluster membership and confirmed that the point of sales has an important role in identifying the consumption of activities and the extension of the area visited. Thus, to conceptualize the decision process in an intra-destination level, the spatial structure of the destination seems to play a greater influence on behaviour than its product structure. The paper illustrates how analysis of destination card data can assist destinations in better understanding their markets and discusses potential research opportunities that can generate real marketing benefits. A number of recommendations especially for destination managers and tourism operators are also identified to enhance the information gathered. Product bundling, regional cooperation and strategic marketing opportunities at sales points are suggested in this context to further incentivize tourist mobility.

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

“…In this article, we analyzed and compared the spatiotemporal patterns in the activities of tourists and residents at different venues in Shanghai over a period of six months. We contributed to the current LBSN and tourism literature by; a) comparing the activity patterns of tourists and residents in one study, while most previous studies focused on tourist activities alone (e.g., [9,11]); b) classifying and extending the analysis to different venue classes, while most studies considered only specific tourism areas (e.g., [14,29]); and c) exploring the spatiotemporal patterns in activities for both tourists and residents, while most studies consider the movement of tourists in a city (e.g., [28,60]).…”

“…The spatiotemporal analysis of tourists mainly involves their movement, interactions, as well as the types of activities they perform in urban spaces within the city, such as what venues are visited at what times [7,8]. Many studies have been conducted on this topic, but mostly focused on movement patterns, spatial distribution, and analyzing the factors influencing the tourists' behavior (e.g., [9][10][11].…”

Measuring tourism destinations using mobile tracking data

“…This approach enabled the authors to cluster tourists based on their spatial behaviour and preferred activities. The knowledge thus gained about connected places and activities can be used for better destination management and marketing (Zoltan & McKercher, 2015). The importance of identifying connected places based on tourists' actual behaviour and bundling them together as a destination for marketing and management purposes has been noted in other studies (Huang & Wu, 2012;Hwang & Fesenmaier, 2003;Hwang, Gretzel, & Fesenmaier, 2006;Lew & McKercher, 2006).…”

“…Nowadays, this can be analysed empirically using various digital datasets containing behavioural data about tourists' actions and communications. For example, Zoltan and McKercher (2015) used destination cards with an embedded chip to analyse their patterns of usage in the Canton of Ticino Switzerland. This approach enabled the authors to cluster tourists based on their spatial behaviour and preferred activities.…”

Determination of tourist flow patterns in a low mountain study area

“…According to Lau and McKercher (2007) analysing the pattern of travel between destinations (either between continents or within larger countries) is more frequent (Flognfeldt, 2005;Lue, Crompton & Fesenmaier, 1993;Nickerson, Bosak & Zaret, 2009;Oppermann, 1997) than that of flown and distribution within a single destination (e.g. Debbage, 1991;Gao, Hsueh, Liu, Lee & Huang, 2013;Lew & McKercher, 2002;Zoltan & McKercher, 2015).…”