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Social Computing in Tourism WebsitesAlton Y.K Chua
Wee Kim Wee School ofCommunication and Information,
Nanyang Technological University,31 Nanyang Link, WKWSCI Building
Singapore 63771865-67905810
ABSTRACT The rapid growth of user-generated content on the Internet
represents a great potential in deploying social computing tools toenrich communication and collaboration among different
stakeholders in the tourism industry. The purpose of this paper is
to address two research questions pertaining to tourism websites:
(1) how prevalently are social computing tools used? (2) In what
ways have social computing tools been used? A total of 90tourism-related websites was randomly drawn from Asia,
American and Europe for analysis. The findings reveal that the
order of prevalence among the different social computing tools is
as follows: social tagging services, blogs, mashup, RSS and
multimedia sharing services. This paper examines the use ofvarious social computing tools and concludes with three
limitations as well as recommendations for further research.
Categories and Subject DescriptorsH.3.5 [Online Information Services]; H.5.2 [User
Interfaces]:Evaluation/methodology.
General Terms Management; Measurement; Verification
Keywords Web 2.0; Social computing; Tourism industry
1. INTRODUCTIONAs one of the largest and fastest growing industries in the twenty-
first century, global tourism, which was worth around US$620
billion in 2004, is expected to grow steadily over the next decade by some 5% to reach US$10 trillion in 2015 [1]. Along with the
expansion of the industry is the explosion of travel-related
information.
The easy digitalization of travel-related information means that it
can be distributed in the electronic marketplace through the
Internet. Thus, establishing a web presence has now become a
strategic necessity for tourism organizations. Nonetheless, the
emergence of social computing tools (known also as Web 2.0) inrecent years has triggered another shift in the tourism industry
landscape.
It no longer seems sufficient for tourism organizations to poststatic Web pages or simply feature electronic transaction
capabilities on their websites. Rather, they are expected to support
multilateral flows of information with and amongst users. In thisway, tourism has transcended from a mere industry into a social
force [2] where users’ travel decisions such as where to go and
what to do are shaped by the collective experiences and opinions
of others.
Social computing tools refer to a suite of applications that are
interactive, context-rich, and easy to use [3]. The explosion of
user-generated content on the Internet points to the immense potential of Web 2.0 in enriching communication and
collaboration in an unprecedented scale. Nonetheless, not much
scholarly efforts have been trained on
studying the adoption of
social computing tools particularly in the tourism industry.
For this reason, this paper addresses the following two research
questions pertaining to tourism websites: (1) how prevalently are
social computing tools used? (2) In what ways have social
computing tools been used?
The scope of this paper is confined to 90 tourism websitesselected randomly across three different regions, namely Asia,
America, and Europe. They also represent an equal distribution
among government, community and business websites.
2. LITERATURE REVIEWInternet technology has been used traditionally in the tourism
industry to provide access to reliable and accurate information,
improve service quality, and contribute to greater travelersatisfaction. It is also used as a convenient means to gather
feedback and complaints from travelers [4]. Additionally, cost is
also one of the motivating factors for the tourism industry to adopt
Internet technology as businesses reap savings from business-to-
business and business-to-customers transactions done online.
With the emergence of social computing tools on the Internet inthe last decade, many tourism websites have begun using them to
alter the manner in which information is created, distributed and
collected. Interestingly, users have reciprocated actively by
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exchanging personal information and experiences with candor, asseen in tourism social networking sites such as WAYN
(www.wayn.com).
This paper focuses on five common social computing tools used
in tourism websites. They are blogs, RSS, social tagging services,
mashup, and multimedia sharing services.
A blog is a collection of texts, images, videos arranged in areverse chronological order to present specific information aboutevents, places and personal experiences. Blogs can be used as a
platform to share travel-related information and has the potential
to create a community of like-minded users.
Rich Site Summary (RSS) is a family of subscription-based Web
feeds that is used to syndicate content from blogs or web pages
without requiring users to visit the corresponding websites. A
tourism organization can create RSS feeds to update theirsubscribers with information such as promotion, advertisement,
and the latest news. In this way, the organization is able to
maintain a constant tie with its users.
Social tagging services allow users to annotate tourism websites
using freely assigned keywords known as tags so that thesewebsites can be easily accessed in the future. These tags mayfurther be shared by others in a social tagging system, which can
in turn foster socialization among a group of like-minded users
A mashup is an application that seamlessly draws content from
different sources to create entirely new services. User can rely on
a mashup, for example, to locate parking lots, restaurants and
walking tours from the comfort of their homes before arriving at
the destinations. The types of mashup include those designed for
mapping, photo-organization, meta-search, custom-interface andcontent visualization purposes [5].
Multimedia sharing services refers to applications that support the
sharing of sound and video files along with user annotations. In
the tourism industry, these services give users a richer dimension
of tourism-related information such as hotels and destinations,
and could be deployed by tourism organizations ascommunication and marketing tools.
3. METHODOLOGY
3.1 Data SourcesDistributed equally across three geographical regions, a total of 90
websites were drawn randomly from three types of tourism
websites, representing those belonging to government agencies, business organizations and community-led efforts. Websites of
government agencies were searched directly using names of
country while business websites and community websites were
trawled from different sources such as CNN travel, The Times
Online and Yahoo!Directory. The three regions, namely, Asia,America, and Europe were selected due to the availability of a
large number of tourism websites. Websites unavailable in
English were excluded.
Government websites refer to government tourism agencies such
as Japan National Tourism Organization, Vietnam National
Administration of Tourism and the Bureau of Consular Affairs inthe US. Business websites include those hosted by commercial
entities in the tourism industry. These include Cathay Holidays (a
subsidiary of Cathay Pacific Airways), Flight Centre and Expedia.
Community websites refer to third-party interest groups set up to
promote peer sharing as well as candid appraisal of tour packages
and destinations among travelers. They do not provide any
booking and payment facilities. These include TripWiser.comand Webcams.travel.
3.2 Method of Analysis
All 90 selected websites were analyzed using a two-step contentanalysis method. The aim of the first step was to determine the
presence of the various social computing tools. Content on the
websites as well as their associated hypertext links were accessedto check for the availability of blogs, RSS, social tagging services,
mashup and multimedia sharing services. The data was binary
coded with “1” and “0” denoting the presence and absence of
each of the social computing tool.
Where a particular social computing tool was found, a second step
of analysis was done to study how it was used. Details including
the content delivered, intended addressees and the intent of thetool in relation to tourism-related information and services were
noted.
4. RESULTS4.1 Prevalence of Social Computing ToolsShown in Table 1, the finding reveals that all 90 tourism websites
have used all five social computing tools in varying extent.
Specifically, social tagging services (STS) is the most popular
social computing tool used in the tourism industry (83.3%),
followed by blogs (58.9%), mashup (40%), RSS (40%) andmultimedia sharing services (MMS) (24.4%).
Table 1. Prevalence of Social Computing Tools
Blogs RSS STS Mashup MMS
Asia
Gov 3 6 10 3 4
Biz 4 0 8 6 3
Comm 6 3 7 2 1
America
Gov 2 4 7 3 5
Biz 7 5 10 2 1
Comm 10 7 10 6 1
Europe
Gov 4 3 8 5 5
Biz 8 5 9 7 1
Comm 9 3 6 6 1
Total 53(58.8%)
36(40%)
75(83.3%)
40(44.4%)
22(24.4%)
While the adoption of various social computing tools differs
across different geographical regions, the differences in the
prevalence of blogs [2(2, N = 90) = 4.773, p= .092], RSS [2 (2,
N = 90) = 3.611, p= .164], STS [2 (2, N = 90) = 1.92, p= .383],
Mashup[2 (2, N = 90) = 4.41, p= .110] and MMS [2 (2, N = 90)
= .12, p= .942] are not statistically significant.
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However, in terms of tourism organization types, it appears thatthe differences in the adoption of social computing tools are
statistically significant, particularly for blogs [2 (2, N = 90) =
17.99, p < .05] and MMS [2 (2, N = 90) = 12.939, p < .05].
Specifically, community websites lead in the use of blogs (25/30= 83.3%), followed by business websites (19/30 = 63.3%) and
government websites (9/30 = 30%). However, government
websites lead in the use of MMS (14/30 = 46.4%), followed by business (5/30 = 16.6%) and community websites (3/30 = 10%).
The prevalence of RSS [2 (2, N = 90) = .833, p= .659], STS [2
(2, N = 90) = 1.92, p= .383] and Mashup[2 (2, N = 90) = 1.17,
p= .557] are not statistically significant.
4.2 Use of Social Computing ToolsTourism websites that feature blogs use them to facilitate
information sharing among users and with site masters. With blogs, users may publish stories about their travel experiences and
the discoveries of interesting food or places. For example, Slow
Travel (www.slowtrav.com) allows its members to contribute
content through blogs. Other users can subsequently comment on
each post or seek clarification from the authors directly. Moreover, blogs can also be used as a means of communication between the
site master and users. For example, Wego (www.wego.com) uses
blogs to deliver content ranging from news to poll results. All
blog postings could attract further comments by users, thereby
promoting a multi-way communication.
RSS is widely used in tourism websites to provide syndicatedupdate of content automatically to subscribers. The use of RSS is
particularly prevalent in government websites. For example,
Tourism Malaysia (www.tourism.gov.my) provides an RSS feed
on various categories such as events, promotional activities and
articles from trade partners in Malaysia. In TravBuddy
(www.travbuddy.com), members can subscribe to blog feeds offellow users to receive quick updates of each other’s blog posts
that may contain travel-related information and experiences.
Tourism sites use STS to support information sharing among theirusers. For example, Things Asian (www.thingsasian.com) allows
users to upload and tag travel photos with freely-assigned
keywords to facilitate retrieval at a later time. In addition, userscan tag each other’s photos depending on their personal
interpretations of the photos. To aid information searching, the
tags are visualized through a tag cloud. Another use of STS is
exemplified in Nextstop (www.nextstop.com) where members can
tag a specific location on a map, and in so doing, make a
recommendation of that location to other users. Users of
Nextstop are also able to browse the tagged locations to finduseful information for their travel plans.
Mashup are versatile applications that combine data from multiple
sources to create useful information. For example, utilizing
Google Map, EveryTrail (www.everytrail.com) enables users toshare their GPS tracks and displays the route that user had
traversed. This information can be tagged and shared as a photoslide show for other users. On the other hand, Travature
(www.Travature.com) uses a mashup that integrates meta search
engines for airfares, user-generated travel guides and hotel
reviews. As a one-stop solution for travelers, Travature has the
potential to cultivate long-term relationships with online visitorsand its users.
The use of multimedia sharing services is popular with
government websites where tourism information is delivered bothvia audio (podcast) and video (vodcast) files. For example,
Tourism Authority of Thailand (tourismthailand.com) provides
videos on the seven wonders of Thailand, an introduction to
Chiang Mai and speeches from the Minister of Tourism. These
videos can be streamed online or subscribed through RSS. The
Indie Travel Podcast (http://indietravelpodcast.com) contains anumber of user-generated podcasts on a range of topics including
traveler’s experiences, review of places and laundry ideas while
traveling.
5. DISCUSSION
5.1 Social Computing Tools Across
Organization TypesOn the basis of the data collected, three main findings can be
culled. First, different tourism websites embrace social
computing tools differently. Among the 90 selected websites, the
order of prevalence of these tools is as follows: STS, blog,
mashup, RSS and MMS.
One possible reason for the popularity of the STS could lie in theway users consume and share tourism-related information on the
Internet. Given that tags are freely-assigned keywords, users may
find them a convenient means to organize their Internet resources
for later retrieval, as well as to share Internet resources with other
like-minded users. Furthermore, as more social tagging sites suchas Digg and Delicious emerge, and as their user bases grow, it
becomes increasingly easy for tourism websites to latch on to
these social networking sites [6].
The prevalence of blogs in community websites is indicative of
the tourism information need of users: comments and experiences
from fellow users may be deemed more credible than those from
sources such as business and government websites.
The fact that government websites use MMS more prevalently
compared to business and community websites could be seen as areflection of the government’s conscious effort to draw tourists to
their websites through media-rich means.
5.2 Social Computing Tools Across
Geographical RegionsSecond, Internet technology has created a level-playing field for
the tourism industry across Asia, America and Europe. From 90
websites analyzed, it appears that websites region-wise have a
comparable level of adoption of social computing tools. As
travelers become more mobile, tourism has broken geographical
boundaries. Hence, users’ tourism information needs are not
confined to any particular location.However, there are some subtle differences in the prevalence ofdifferent social computing tools. Websites in Europe, for example,
tend to feature mashup more than those in the other two regions.
One possible reason could be that the European continent is
smaller in size than the Asian and the American continent. Thus,websites in Europe use mashup, which invariably relies on Google
Map, as a way to enable travelers discover nearby tourist
attractions. Furthermore, the European market is matured in the
areas of online social gaming, online social networking and
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mobile technology including GPS [7]. Hence, in Europe, there isa growing trend in the use of mashup that combine these elements.
On the other hand, RSS and STS are the most popular tools
among websites in America. This could be due to the advanced
stage of adoption of electronic news media and online newspapers
in America [8], resulting in a flow-over effect to the tourism
sector. Moreover, many social tagging services companies suchas Digg (http://digg.com), StumbleUpon (www.stumbleupon.com),
and Delicious (www.delicious.com) are American-based startup
companies.
5.3 Integrated Use of Social Computing ToolsThird, while the underlying function of all social computing tools
points towards piquing users’ interests and enhancing their online
experience, the manner in which individual tools can be used islimited by the imaginations of site masters and decision makers.
For example, in EveryTrail (everytrail.com), multimedia sharing
services, blogs and mashup are integrated with other social
networking services such as Facebook and Twitter so that users
traverse from one social computing tool to another seamlessly.
Rather than treating each social computing tool as being distinct,tourism websites have correctly recognized how the tools can
complement each other to increase the level of user engagement.
In particular, it is common to find blogs used in conjunction with
RSS feeds so that users can be notified whenever new posts
related to a particular topic of interest emerge. Such aggregateddeployment of social computing tools, which conceivably serves
the needs of users better, is likely to become more common in
tourism websites.
5. CONCLUSIONIn the era of information digitalization, users of tourism websites
are increasingly reliant on information available on the Web as
part of their travel planning. Even as the Internet technology has
enabled fast and efficient distribution of information, the adventof social computing tools has altered the landscape for interaction.
While users in the past could only visit static web pages and
access institutional content that mirrored print-based publications,
they are now able to create and distribute their own content withease.
Government, business and community websites in the tourism
industry have begun to feature various social computing tools to
better engage their users. Although the explosion of user-
generated content points to the immense potential social
computing tools brings, little scholarly attention has been trained
on their adoption in the tourism industry. Thus, this paper seeks toinvestigate the prevalence and use of social computing tools in
tourism-related websites.
Across all 90 websites selected for analysis, the order of
prevalence of five common social computing tools is as follows:
STS, blog, mashup, RSS and MMS. In terms of geographical
regions, the differences in the adoption of all five social
computing tools are not statistically significant. In terms oforganization types, the differences are statistically significant for
blogs and MMS. In particular, community websites lead in the
use of blogs while government websites lead in the use of MMS.
As a platform of communication, blogs are used to share personal
anecdotes and travel experiences. RSS is used in tourism
websites to provide syndicated update of content automatically to
subscribers. In this way, tourism agencies are able to keep theirusers abreast of news and new offerings. Users rely on STS to
bookmark Internet resources for later retrieval, as well as make
recommendations of point of interests to others. Combining data
from disparate sources, mashup are commonly used to presentannotated travel routes for users. Finally, MMS enriches usersexperience on the Web by presenting tourism-related information
through sound and video.
Three limitations in this paper need to be acknowledged. First,
data collection scope was confined only to 90 tourism websites.
Second, the selection of websites from Asia, America and Europe
was limited to those available only in English. This could limit the
analysis in the findings since there are websites in other languagessuch as Chinese which also feature social computing tools.
Finally, the tools studied in this report are only limited to blog,
RSS, folksonomy, mashup, and podcast.
For interested scholars, there are a number of suggested areas for
research. For example, a more exhaustive study involving a larger
sample of websites could be used. Future work can look into othergenres of Web 2.0 applications such as virtual worlds,
microblogging as well as other applications designed for mobile
devices. Another possibility is to examine Web 2.0 applications
in tandem with websites’ quality and performance.
6. ACKNOWLEDGMENTSThe authors would like to thank Anthony Steven, Chen Chi, Ryan
Justin and Wely for their data collection efforts.
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