Keywords

1 Introduction

Tourism is one of the core sectors of the Austrian economy, accounting for around 9 % of Austria’s GDP (Wikipedia 2013). In 2007, Austria ranked 9th worldwide in international tourism receipts, with a total of 18.9 billion US$ (Wikipedia 2013), and a total of more than 121 million overnight stays (Statistik Austria 2013). By 2012, an 8 % increase can be noticed with a little over 131 million overnight stays (Statistik Austria 2013). Tourism has comparable influence on the economic and social situation of Austria. Therefore, possessing all of the required key competencies necessary for running this economic sector is of great strategic importance for Austria. Losing a cornerstone of this process could lead to a significant loss of income and revenue.

The rapid advance of ICT technologies, and their increasing importance in the tourism domain, has led to an exponential growth in online communication opportunities. This includes the websites of the touristic service providers, other websites (e.g., the website of the Tourist Board, Wikipedia, etc.), email, email lists, chat, instant messaging, news, message boards, internet fora, blogs, microblogs, podcasts, photo and video sharing, collaborative tagging, social networks, mobile platforms, recommendation sites, booking channels, destination management websites, search engines and meta-search engines, rich snippets, semantic annotations, etc. In addition, high visibility and ranking in popular search engines such as Google, Yahoo or Bing is also a key goal that any online presence must not neglect. Known as Search Engine Optimization (SEO), this goal can be achieved mainly by having accurate, relevant, up-to-date annotations in the formats and vocabularies that search engines understand and use as part of their internal search mechanisms.

All channels mentioned above are important means of implementing successful online marketing and driving sales. These are no longer an option for touristic service providers, but a necessity. Maintaining competence and competitiveness in online marketing for tourist service providers, coupled with ubiquitous access, interaction and book ability of the services they provide through mobile devices, may therefore be key to the future prosperity of Austria. This chapter analyses the online presence and marketing of a large, representative set of Austrian touristic service providers ranging from small to large hotels and hotel chains. We perform an empirical analysis of the usage pattern of the Web, particularly, Web 2.0—Social Web—and Web 3.0—Semantic Web—technology for their online presence. We begin by introducing our work through research questions and presenting related studies (Sect. 2). Next, we introduce the methodology setup for the analysis (Sect. 3). We then analyse the online presence of touristic service providers based on our results (Sect. 4), and finally conclude in Sect. 5.

2 Related Work and Research Questions

The application of internet technologies in the tourism domain has been the topic of several scientific studies which focus specifically on the adoption of classical internet/web technologies by hotels. For example, Murphy et al. (2006) evaluates the internet adoption by analysing 200 Swiss hotel websites and email responses. Automatic techniques based on complementary multivariate and artificial neural networks help in the evaluation and classification process. Chan and Law (2006) focuses on the usability of websites, effectiveness of interface, amount of information, ease of navigation and user friendliness of a dozen hotels from Hong Kong. Schegg et al. (2002) explore a small slice of the soaring travel marketplaces, investigating how 125 Swiss hotels use Web-based marketing tools. The study focuses on classical Web technologies and finds that most hotel websites broadcast static information but provide limited transactional functions (e.g., rates, offers, etc.). A more recent study coming from the same group (Schegg et al. 2008) analyses the application of Web 2.0 technologies for more than 3,000 tourism businesses. At the time of the study, the authors concluded that most of the tourism enterprises were in the early stages of applying Web 2.0 concepts to their businesses. Scaglione et al. (2013) revisit the results of Schegg et al. (2008), showing the evolution of this adoption over the period 2008–2012. The set of criteria used in Schegg et al. (2008) is adopted and complemented in light of the technological progress that occured during the period previously mentioned. A total of 4,700 tourism websites in Europe have been analysed by primarily looking at the general use of Web 2.0 and Web 3.0 technologies. The authors conclude that while for some techniques the take-off phase is finished, for other new techniques, such as RDF, the tourism sector is still at the very beginning of the adoption process. The level of infiltration of Web 2.0 technologies in the tourism domain is the theme of several studies such as Ayeh et al. (2012) for the Hong Kong hospitality industry, or Stankov et al. (2010) and Shao et al. (2012) for destination marketing organizations (DMOs).

Other studies such as Grüter et al. (2013) focus more on analyzing the multimedia aspects of the hotels’ online presence and the potential benefits of using these multimedia applications. Using the Swiss hotel business as an example, the study shows that while pictures appear on nearly every website, the use of videos and three-dimensional (3D) presentation formats is much less common. They stress that advances in multimedia formats such as videos and 3D presentations on hotel websites could have a positive impact on brand awareness, image and confidence in the hotel on the part of the customer.

Despite a large volume of studies available in the literature, none of them provide an extensive analysis of uptake of the Web technologies (Web 1.0, 2.0 and 3.0) in the tourism domain considering: (1) a large number of criteria from these areas and (2) including thousands of hotels, as in our study. Therefore, the research questions of this study are formulated as follows:

  1. 1.

    To what extent do hotels in Austria exploit the Web 2.0 and 3.0 solutions?

  2. 2.

    Is the Content Management System related to the integration of Web 3.0 technologies?

  3. 3.

    Is there any correlation between the hotels’ star rating with the usage of Web 2.0 and 3.0 technologies?

In this respect, by investigating these questions, we aim to identify the adoption of Semantic Web annotations and Social Web channels and discover correlations between these, and the hotels’ infrastructure. These results will help to observe and analyse any correlation between the current situation in online direct marketing and the extent that hotels are using the various technologies and means of communication on the Web through their websites. If the results indicate vast room for improvement, it would imply that online direct marketing could also bring better results and return on investment (ROI) by improving the situation and strengthening the online weaknesses.

3 Methodology

In this section, we introduce the methodology that we followed which comprises of: (a) the dataset specification as well as any technical decisions; and (b) the selection and evaluation criteria for the analysis.

We began by collecting data from various sources (Google Places, TripAdvisor) about the hotels that exist in Austria. Our dataset of hotels includes URLs, star ratings and geo-coordinates. The sample was selected randomly. Over 2,000 hotels were selected (i.e., 2,155 to be precise), and 75 % of the hotels selected have 3–5 stars. As shown in Fig. 1, they are distributed within the Austrian borders.

Fig. 1
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Geographic distribution of hotels in our dataset

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Our research workflow continues with the specification of the criteria with which we used to evaluate the dataset. Thus, our criteria can be divided into two main categories, namely the Web 2.0 direction and the Web 3.0 direction. In our case, the Web 2.0 represents the media that is mainly described as the ‘Social Web’. Furthermore, the Web 3.0 represents the Semantic Web technologies that a hotel could apply on its website in order to gain more visibility on the web. Particularly, we focus on the existence of semantic annotations that could bring a hotel’s website into a better position in search results of the major search engines (e.g., Google, Bing, Yahoo!, etc.) and with a richer presentation among the results by exploiting the opportunities that exist in the user interfaces of the search engines, such as in the case of Google with the Google Rich Snippets (Steiner et al. 2010).

The next step towards gathering the hotel websites’ data was the implementation of a Web crawler that would access the hotels’ websites and extract information about the criteria that we have specified and which are demonstrated in Sect. 3.1. Therefore, we built a Web crawler in Python based on a well-known open source high-level screen scraping and web crawling framework, i.e., Scrapy (www.scrapy.org). For the storage of the crawled data, we preferred to use a NoSQL database, namely the MongoDB (www.mongodb.org), and store JSON objects with the distilled information from the various pages. It is worth mentioning that we set a limitation of depth for the crawler, i.e. three levels from the starting page, in order to achieve better performance. However, this limitation cannot affect the accuracy of our results as our criteria are met at the very first pages of the websites.

3.1 Criteria

The aim of our Web analysis is to unveil insights hidden at the HTML mark-up of the hotel websites by crawling the URLs of our dataset. We applied the criteria during the crawling process, rather than downloading the whole website locally. Our criteria cover the Web 2.0 major channels and the Web 3.0 technologies, namely the formats and vocabularies for semantic annotations, as shown in Tables 1 and 2, respectively.

Table 1 Web 2.0 criteria
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Table 2 Web 3.0 criteria
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Table 1 presents the Web 2.0 dimensions that we looked into during our analysis of the collected data, while Table 2 presents the Web 3.0 formats and vocabularies from which hotels could benefit.

As we were interested in the uptake of the Web 3.0, we focused on the existence or nonexistence of technologies used for adding semantic annotations (i.e., machine-readable metadata) to websites. In this respect, we distinguish between formats and vocabularies within our criteria. Formats refer to the technologies with which a web developer could add semantic annotations to a website. As shown in Table 2, there are three main formats, as broadly adopted options, namely microformats, RDFa and microdata.

Microformats (abbreviated as μF) are conventions used to describe a specific type of information on a web page (e.g., people, organizations, locations, etc.). In general, microformats overload the class attribute in the HTML tags to assign descriptive names to entities. They can be realised as format and vocabulary combined. The second version of microformats add prefixes to the terms in order to understand which class names are used by microformats (e.g., u-photo is used to annotate the URL of a photo).

Resource Description Framework in Attributes (RDFa) provide a set of mark-up attributes to augment Web page content with semantic annotations. RDFa are based on attributes by re-using HTML tags and defining namespaces in the XHTML to assign types and names to entities and properties. None of the attributes introduced or used by RDFa have any effect on the rendering of the web pages.

Microdata specification is similar to microformats, but introduces new HTML tag attributes (i.e. itemscope, itemprop, itemtype, etc.) that can host terms from any vocabulary. It is supported by schema.org and is part of the HTML 5 specification. In comparison to the aforementioned formats, we could say it combines ease of use, effectiveness and flexibility, all of which make it a great option for semantic annotations.

The results from our analysis, presented in Sect. 4, aim to answer our research questions.

4 Analysis Results

Following the methodology presented in Sect. 3, we collected data from more than 2,000 hotels in Austria, and from which we have gained some useful insight that will answer the research questions which we posed at the beginning of this chapter. The distribution of CMS systems is shown in Fig. 2 and Table 3. The percentages of Table 3 refer to the occurrences of the second column divided by the total number of websites with a CMS system (i.e., 946 out of 2,155 websites).

Table 3 Distribution of CMS systems
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Studying the data in Table 3, it is evident that there is great diversity in the CMS decisions by the web development agencies. It is worth mentioning that we have information about the type of the CMS system for roughly 44 % of the dataset. The main reason is the way that this piece of information is extracted. Thus, we are able to capture only those CMS systems that specify their name explicitly within the HTML metadata fields. However, according to our knowledge, all the major CMS systems do so, which means that for the rest of the hotels we could say that they are not using any of the well-known and well-designed CMS systems or they do not use a CMS system at all.

The most popular CMS seems to be TYPO3 with 44 % frequency among the CMS systems retrieved for our dataset. In second place is the well-known Joomla! CMS and third is WordPress, which is mostly used for blogging. It is worth mentioning the fact that we observed the usage of systems, like Adobe GoLive,Footnote 1 which have not been available for the last 5 years. This fact implies that there are a significant number of hotels that have stopped investing in their Web presence as far as their website is concerned. It is common practice to update the website from time to time in order to keep the design and functionality aligned to the current paradigms and competitors’ level.

Figure 2 offers interesting insight into the diversity. Thus, 27 % of hotels use other CMS systems rather than one of the popular (i.e., Drupal, Joomla!, TYPO3, WordPress, MS FrontPage). We observed 87 different CMS systems within the aforementioned portion of 27 %.

Fig. 2
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Distribution of content management systems (CMS)

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Regarding the adoption of Web 2.0 technologies, we measured the usage of the major Social Web channels (i.e., Facebook, Flickr, Google+, HolidayCheck, Instagram, Pinterest, RSS, Tripadvisor, Twitter, Vimeo, YouTube) within the websites of the hotels. We found that 53 % of the hotels in the dataset exploit the opportunities offered by the Web 2.0 by adding links on their websites to one channel or more of their Social Web profiles. However, this does not imply that the remaining 47 % of hotels are not present on the observed channels. It only highlights the fact that they have not connected those channels with their website. Thus, it can be the case that a hotel maintains a Facebook page but does not point the website users to it.

Furthermore, 68 % of the active Web 2.0 hotel websites (roughly 1,150), link their fan page or account to Facebook, while 48 % link to HolidayCheck. The potential of Twitter and Google+ seems to be realised by 14–15 % of the hotels in the dataset, while 25 % exploit YouTube and RSS as shown in Fig. 3. We measured more than 600 hotels linking to at least one review site.

Fig. 3
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Usage of Web 2.0 channels

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The next step includes the analysis of the Web 3.0 (also known as Semantic Web) technologies uptake by the hotels in our dataset. The results in this dimension prove that most of the hotels completely ignore the existence of technologies that could enrich the website content with high level metadata and give machine readable meaning to the presented information. As shown in the pie chart of Fig. 4, only 5 % of websites employ some Semantic Web technologies, while the rest seem to ignore the potential of adding semantics to their websites.

Fig. 4
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Uptake of Web 3.0 technologies in the Austrian accommodation sector

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Other than not being aware of the potential benefits and advantages the Web 3.0 can offer, another possible reason for lack of uptake could be the delays in the alignment of web development agencies with state of the art technologies in the field, or the hesitation to adopt Semantic Web technologies due to their complexity. However, semantic annotation technologies are already mainstream and widely applied on the Web.

Moreover, it is interesting to examine the distribution of the CMS systems in conjunction with the use of semantics as described in the second research question presented in Sect. 2. In this respect, Fig. 5 depicts the usage of CMS systems among the hotels which adopt Web 3.0 technologies, i.e. 5 % of the hotels in our dataset according to Fig. 4. The presented figures are related to the number of hotels that use a CMS, i.e. as mentioned earlier, 44 % of the hotels in our dataset.

Fig. 5
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Correlation of CMS systems and Web 3.0 integration

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In the case of “Web 3.0 ready” hotel websites, WordPress seems to hold the first position, while TYPO3 is in second. Thus, the distribution of Web 3.0 integration within CMSs does not follow the CMS usage distribution. It is remarkable that we did not observe any occurrence of Drupal 7 within this subset of hotels, as Drupal 7 is meant to be the most semantically friendly and supportive CMS at the time of writing, and to the best of our knowledge (Clark 2011).

Last but not least, we examined the correlation between the number of stars and the adoption of Web 2.0 and Web 3.0 technologies (3rd research question). Therefore, the diagram of Fig. 6 depicts the correlation among these variables. Hotels with one and two stars seem to be less responsive to the development of new web technologies and paradigms, like Web 2.0 and 3.0. This result can be expected, as the development of the onsite quality of services is of highest importance and takes priority over online presence, especially considering the limited budget available in most of the cases.

Fig. 6
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Correlation of hotels applying Web 2.0–3.0 with number of stars

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Furthermore, Fig. 6 demonstrates a proportional relationship between the number of stars and the percentage of hotels per category that link their websites with their Web 2.0 channels. Specifically, 42 % of the websites of three-star hotels make use of Web 2.0 technologies including RSS feeds, video and photo sharing services, like Flickr and YouTube, and Social Web channels, like Facebook and Twitter. While, an average of 59 % of four and five-star hotels make use of the Web 2.0 channels, the corresponding figures for the Web 3.0 adoption do not exceed 6 % of the websites in each category, which are not significant enough to compare. The same situation more or less is observed in the remaining cases, meaning hotels rated with one and two stars.

Concluding from the data in Fig. 6, we can deduce that semantic annotations have a long way to go in order to bring the hotel websites to their full potential in terms of visibility on the Web search engines.

5 Conclusion

This chapter analyses the use of the new Web 2.0 and Web 3.0 technologies on a set of hotel websites in Austria. The aim of this work has been to explore the uptake of the related technologies, in order to identify the status quo of direct online marketing in the Austrian tourism domain, as online visibility is the cornerstone of advertising in today’s world. In this respect, our approach has included crawling and extracting the information on the current use of modern technologies, such as Social Media (Web 2.0) and Semantic Web markup (Web 3.0), on the hotels’ websites.

The analysis outcome has shown the current sparse usage of such technologies by the hotels’ websites. The slow technology take-up is hindered by the technical (e.g., difficult integration due to the usage of heterogeneous CMSs within in the sector) and educational factors (e.g., knowledge about the new technologies and understanding of their advantages). Thus, there is large space for improvement regarding the visibility of the hotels on the current Web ecosystem. Failure to act on improving the use of the latest Web paradigms would keep the visibility of the hotels moderately low in search engine algorithms, as they are becoming more and more sophisticated. This fact prevents online direct marketing to be monetised via direct bookings and limits the impact of Online Travel Agencies (OTA) on the budget of the hoteliers.

Future steps have already been considered, including the expansion of the geographical region in which our criteria and crawling are applied in order to cover the whole of Europe. Furthermore, the criteria will be re-worked in order not to overlook any means of dissemination and added value within the website.