The SAGE Handbook of Online Research Methods

Tourism expenditures have been much researched in the past: at the aggregate level to evaluate national benefit of the tourism industry and at the disaggregate level to evaluate the attractiveness of tourist market segments. Past studies, however, fail to take into account that tourism expenditures are affected by the plethora of other expenditures households make and that households are heterogeneous in allocating discretionary funds to alternative spending options. The present study fills this gap by investigating heterogeneity in household discretionary expenditures derived from a realistic choice task. In doing so, it challenges the implicit paradigm of prior research into tourism expenditures in which the context of the household tradeoff in allocating income is ignored. The results, highlight the importance of studying tourism expenditure in the context of other household expenditure decisions; demonstrate the high level of heterogeneity between individuals with respect to their spending preferences; and illustrate the value of this knowledge for tourism destination management as well as government policy in being able to assess the competition between expenditure categories and identify market segments most suitable for the product category offered.

Tourism And Discretionary Income Allocation - Heterogeneity Among Households

The objective of this article is to analyze travel expenses across and within types. The empirical application examines the determinant factors of total expenses, controlling for potential endogene...

Determinant Factors of Tourist Expenses

Network approach to tourist segmentation via user generated content

The impact of distribution channels on budget hotel performance

This paper analyses the use of the main e-tourism platforms by European tourists. A computer-aided Web interview (CAWI) was used to conduct the research in 19 European countries: Germany, Austria, Belgium, Denmark, Spain, Finland, France, Holland, Ireland, Italy, Norway, Poland, Portugal, Russia, Sweden, Switzerland, Luxemburg, Czech Republic, and the United Kingdom. The final sample consisted of 13,243 tourists. Through the methodology of Social Network Analysis (SNA), the study focuses on detecting key network players (social media, OTAs, etc.) in the e-tourism ecosystem. The network analysis reveals the structural characteristics of the network of networks in the European e-tourism ecosystem: number of platforms (473), centrality degree and betweenness, and the specific characteristics of the networks by country. The results show an e-tourism network of platforms following a pattern known as core-periphery. Four platforms show a predominant role: Facebook, TripAdvisor, Google, and Booking. These ‘big four’ ego-networks are graphically represented to better understand the e-tourism network. The results also show that different networks are formed by country according to the use of e-tourism platforms. This study helps understand in a novel way the behaviour of European tourists when using e-tourism platforms to choose their travel destination. The results obtained are useful for companies and Destination Marketing Organizations (DMOs), understanding how e-tourism platforms are connected in order to design their segmentation and promotion strategy through e-tourism platforms in the European market.

Understanding European tourists’ use of e-tourism platforms. Analysis of networks

The purpose of this study resides in a better understanding of the relationship between the use of traditional operators, online travel agencies, such as Booking.com and Expedia, comparators, tour operators and traditional travel agencies, airlines, new non-tourist companies like Google and the use of sharing economy platforms to obtain information about a travel destination.,Applying an analysis to 13,243 tourists from 19 European countries, a binomial logit analysis was carried out with the latest version of the SPSS statistical analysis program.,The use of Expedia and Booking.com has a positive effect on the use of sharing economy platforms to obtain information about travel destinations. However, it can also be observed how the use of Google, Facebook, tour operators and travel agencies, airlines and Twitter can have a negative effect.,The study provides interesting recommendations for destinations to be able to design better marketing strategies which focus on cognitive components of the destination image in different information sources.,Tourists search for information that helps them make better decisions when it comes to choosing a travel destination and they do so using different channels that have evolved over time. The proliferation of internet platforms has transformed the way tourists search for information and consequently the way the secondary image of destination is formed. The sharing economy plays an important role in this new tourism ecosystem. These new business models, based on platforms, coexist with other traditional information sources, tour operators and travel agencies and airlines. However, previous studies have not inquired about the relationship between them all.

New digital tourism ecosystem: understanding the relationship between information sources and sharing economy platforms

The aim of this study is to identify spending patterns of tourists in relation to the leisure activities performed throughout their day-by-day stay at the destination. Using the methodology of soci...

Tatiana David-Negre

Papers

Understanding European tourists’ use of e-tourism platforms. Analysis of networks

New digital tourism ecosystem: understanding the relationship between information sources and sharing economy platforms

Understanding tourists' leisure expenditure at the destination: a social network analysis

Use of the Social Network Analysis Methodology to Study the Image of Tourist Destinations