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The purpose of this study is to understand the status quo of the use of Web analytics tools by European destination management organizations (DMOs) and to provide guidelines in using these metrics for business intelligence and tourism design. In addition, the goal is to improve destination management at the city level using Web analytics data.

In this exploratory study, the authors analyze how European DMOs view Web analytics data through the lens of the “data to knowledge to results” framework. The authors analyze the use of Web analytics tools by DMOs through the theory of affordances and “data-to-knowledge framework” developed by Davenport et al., which incorporates several factors that contribute to a successful transformation of data available to an organization to knowledge, desirable results and ultimately to building an analytical capability.

The results show that European DMOs mainly use Web analytics data for website quality assurance, but that some are also using them to drive marketing programs. The study concludes by providing several suggestions for ways in which DMOs might optimize the use of Web analytics data, which will also improve the management of destinations.

Web analytics tools are used by many organizations such as DMOs to collect traffic data, to evaluate and optimize websites. However, these metrics can also be combined with other data such as bednights numbers and used for forecasting or other managerial decisions for destination management at the city level. There is a research gap in this area that focuses on using Web analytics data for business intelligence in the tourism industry and this research aims to fill this gap.

This study aims to use mixed methods to create a new conceptual framework to understand the unique characteristics of virtual tourism experiences (VTE), which has not been systemically examined.

Study 1 uses topic modeling with Latent Dirichlet Allocation to analyze 91,609 online reviews from the Airbnb Experience platform. Study 2 uses content analysis of open-ended qualitative responses from VTE customers. The two studies together are used to build a new conceptual model.

Building upon the Stimulus–Organism–Response (S-O-R) model and the experience economy, results present a new conceptual model and identify VTE as unique in terms of Stimulus (education, entertainment, esthetics, escapism and connection), Organism (experiencing synchronicity, telepresence, participation and customization, emotion) and Response (evaluation and behavioral responses). Given the uniqueness of VTE, the new construct of the virtual servicescape is incorporated, recognizing the host, the focal customer and other customers, and the technology as the four main components.

The proposed framework can be used to guide the design, development, and evaluation of VTE, including identifying the key considerations, engagement within the ecosystem and providing guidance to hosts and operators.

To the best of the authors’ knowledge, this is the first study that systematically explores VTE and proposes the theoretical framework to comprehensively understand this new form of experience in sharing economy by combining the unique aspects of the stimulus, organism, response and virtual servicescape.

The purpose of this paper is to analyze the ex ante projected future trajectories of real tourism exports and relative tourism export prices of the EU-15, conditional on expert real gross domestic product growth forecasts for the global economy provided by the Organisation for Economic Co-operation and Development for the years 2013-2017.

To this end, the global vector autoregression (GVAR) framework is applied to a comprehensive panel data set ranging from 1994Q1 to 2013Q3 for a cross-section of 45 countries. This approach allows for interdependencies between countries that are assumed to be equally affected by common global developments.

In line with economic theory, growing global tourist income combined with decreasing relative destination price ensures, in general, increasing tourism demand for the politically and macroeconomically distressed EU-15. However, the conditional forecast increases in tourism demand are under-proportional for some EU-15 member countries.

Rather than simply relying on increases in tourist income, the low price competitiveness of the EU-15 member countries should also be addressed by tourism planners and developers in order to counter the rising competition for global market shares and ensure future tourism export earnings.

One major contribution of this research is that it applies the novel GVAR framework to a research question in tourism demand analysis and forecasting. Furthermore, the analysis of the ex ante conditionally projected future trajectories of real tourism exports and relative tourism export prices of the EU-15 is a novel aspect in the tourism literature since conditional forecasting has rarely been performed in this discipline to date, in particular, in combination with ex ante forecasting.