Measuring the Online Reputation of Sustainable Tourism Destinations.

Reputation Institute Conference 2010 he Sustainability Imperative: A Strategic Role for Reputation Management T  

Measuring the Online Reputation of Sustainable

Tourism Destinations

Elena Marchiori Alessandro Inversini

Lorenzo Cantoni

webatelier.net Faculty of Communication Sciences University of Lugano, Switzerland

(elena.marchiori; alessandro.inversini; lorenzo.cantoni)@usi.ch

TITLE OF CONFERENCE PAPER Measuring the Online Reputation of Sustainable Tourism Destinations Abstract The understanding and management of online reputation is a crucial practice for complex organizations such as tourism destinations. Destinations’ managers need to holistically listen and manage online discourses to better interact with prospect travellers and to better communicate online. This research investigates the online discourses (eWord of Mouth) of three popular sustainable destinations mainly focusing on the environment related topics. The research refers to a model called Destination Online Reputation Model (DORM) already tested in tourism related other cases. Keywords: online reputation, eWord of Mouth, online reputation model, tourism destination online communication. Biographies of authors Elena Marchiori is a PhD candidate at the Università della Svizzera italiana (USI, University of Lugano, Switzerland – www.usi.ch). Elena’s research interests focus on web reputation and reliability in the eTourism field. She has studied the online communication of the cruise industry, and done consultancy activities in this area. Elena holds a Master degree in Media Management from the University of Lugano, and earned her Bachelor degree in Communication Sciences at the University of Padua (Italy – www.unipd.it).

PhD Alessandro Inversini recently earned his PhD at USI, University of Lugano, Switzerland – www.usi.ch. Alessandro holds a Master in Communication Sciences and Communication Technologies. His research activity primarily deals with usability, quality and new technologies of communication in cultural tourism. His PhD research concerned online communication of cultural tourism destinations.

Prof. PhD Lorenzo Cantoni graduated in Philosophy and holds a PhD in Education and Linguistics. L. Cantoni is full professor at USI, Faculty of Communication Sciences. He is vice-dean, and director of the laboratories webatelier.net: production and promotion over the Internet; NewMinE: New Media in Education Lab. His research interests are where communication and new media overlap, ranging from computer mediated communication to usability, from eLearning to eTourism and eGovernment.

Introduction

Reputation represents an important asset for companies and organizations (Fombrun, Gardberg, and

Sever 1999). Furthermore, it can be seen as an economic asset for organizations, and as any economic

asset, it can be measured and managed. Moreover, the advent of the so called social web (or web2.0 -

O’Really, 2005) transformed internet users into information players and providers (pro-sumers)

(Nicholas, et al., 2007). The recent development of the internet shifted the virtual environment

(Cantoni and Tardini, 2006) to become not only a library, in which to find relevant pieces of

information, but also a public square, in which to meet people have discussions with them. Studying

and measuring online reputation has thus become an increasingly crucial marketing practice for

companies and organizations. In the tourism industry, online reputation is becoming particularly

critical due to the role of information communication technologies (ICT) and the internet.

The tourism industry presence in the so-called online tourism space (Xiang et al., 2009) is created by

different information providers (Inversini and Buhalis, 2009): official websites and unofficial website

concur to reach end-users’ attention on a given topic (Inversini and Buhalis, 2009). Among unofficial

websites, User Generated Content (UGC) websites strategy contribute to creating the online

reputation (Marchiori et al., 2010) UGC can be seen as a network of digitalized word of mouth

(eWOM) containing facts, opinions and judgements about a given product or service. The main

characteristic is that users freely share content (e.g. comments, reviews, pictures and videos) among

each other within specific online platform (e.g. social media websites). The aggregation of these

contents, help shape the online representations of a tourist organization and its reputation (Inversini et

al. 2010; Bolton et al., 2004). Thus, measuring online reputation can be viewed as an important step

towards understanding how to manage companies’ or organizations’ greater online presence

(Marchiori et al., 2010). Destination representations’ obtained from search engine results can

influence the prospective traveller’s. A prospective traveller can reach contents concerning “cognition

and behavior at a destination as well as satisfaction levels and recollection of the experience”

(Jenkins, 1999), written by other travellers who already experienced the tourism destination searched

online. Results from a recent study by Li, Pan & Zhang (2009), show that affective image components

(e.g. satisfaction levels and recollection of the experience), more than cognitive components,

significantly change after the internet exposure of a prospect traveller, and social media are the online

sources which contain affective responses (Peter and Olsen, 2002).

This research is starting from previous research (Inversini et al. 2010) which used a framework for

finding and classify UGC for a given tourism destination (TD). The framework named DORM

(Destination Online Reputation Model) adapts Reputation Quotient and RepTrak models developed

by the Reputation Institute in a new online reputation model, especially designed for tourism

destinations. The use of DORM in the previous case study about London tourism destination

(Inversini et al. 2010), showed that among seven TD dimensions (products & services, innovation,

performance, society, environment, governance and leadership), products & services dimension was

the most prevalent in the eWOM (online conversations).

Former findings allow the authors to investigate whether characteristic TDs will also exhibit products

& services dimensions. In this paper the authors selected sustainable TDs where the communication

core is environment and society. The assumption is that the most prominent dimension will aligned

with the communication core of the destination analysed. In this case the dimension expected was

environment. Results show that the relevance of the online conversations (eWOM) around these

sustainable TDs were on products and services instead environment as expected. These findings

confirm the established tendency for the contents of TD user generated contents to primarily involved

products and services dimension. Possibilities for further research will be presented at the end of the

paper.

Since the presence of eWOM is not fully under the control of the Destination Management

Organizations (DMO), destination marketers are faced with a growing challenge (Li et al., 2009).

DMOs understood the importance of their presence online and how prospective tourists can perceive

the destination from an online search (Choi et al. 2007); internet in fact has become the primary way

used by DMO to communicate with future clients (Buhalis, 2003). DMO should consider the

operational steps presented in this paper as an online marketing tool to manage their reputation.

Literature Review

Next paragraphs describe the unicum of the tourism industry online communication, starting from an

introduction about the relevant work on the role of new media in tourism communication and

outlining the role of reputation and especially online reputation.

The role of ICTs in Tourism

The recent evolution of new media has had a strong influence on the tourism domain as a whole

(Buhalis, 2003). Tourism players and especially TDs understood the importance of the internet as a

preferred marketing channel where to market their own products and services: actually the internet

has become the primary way used by DMO to communicate with prospective tourists (Buhalis, 2003).

During the last few years, both ways of purchasing tourism goods (Werthner and Klein, 1999) and the

ways by which tourists gather information (Buhalis, 2003) and comment on their travel experience

(Yoo and Gretzel, 2008), have changed dramatically (Sheldon, 1997). Tourism can be seen as an

information intensive domain where the information availability and gathering represent a crucial

issue (Poon, 1993) for the day to day operations. Recently Xiang, Wöber and Fesenmaier (2008) and

Xiang and Gretzel (2010) described the Online Tourism Domain accessible trough search engines;

within this online tourism domain (Xiang et al., 2009), it is actually possible to find official

destination and attraction websites (e.g. cultural heritage attraction websites) as well as unofficial

sources of information (Xiang and Gretzel, 2010) such as blogs (Thevenot, 2007), online

communities, social networks, personal websites etc. Information has become available both from

official and unofficial sources (Anderson, 2006). Unofficial websites are competing to reach end users

presenting almost the same information as the official websites do (Inversini & Buhalis, 2009). This

ever-increasing web2.0 phenomenon (O’Reilly, 2005), enables individual users to produce so called

User Generated Contents (UGC), to meet, share and discuss knowledge and contributes significantly

to the massive growth of information on the web (Cantoni and Tardini, 2010).

Furthermore, observing the World Wide Web, it is possible to identify two types of websites: (i)

web1.0 websites: web pages of services, business etc. presenting their business, selling a product or

integrating business processes (Cantoni and Di Blas, 2002), and (ii) web2.0 websites, which are

defined as social websites and primarily contain UGC published by end users (Boulos and Wheelert,

2007). Web2.0 sites (also called “social media”), can be generally understood as internet-based

applications that encompass “media impressions created by consumers, typically informed by relevant

experience, and archived or shared online for easier access by other impressionable consumers”

(Blackshaw, 2006). Social media are important as they help spread within the web the electronic

Word of Mouth (Litvin, Goldsmith, & Pan, 2008) which represents “a mixture of facts and opinions,

impressions and sentiments, founded and unfounded tidbits, experiences, and even rumors”

(Blackshaw & Nazzaro, 2006). UGC could be seen as relevant in different industries: they are

extremely relevant in the tourism industry because tourism is an experience, and as experience it

needs to be communicated (Inversini and Cantoni, 2009).

Marketing managers and researchers are exploiting new ways to use social media within the online

promotion activities in order to take advantage of this “electronic word-of-mouth” (Litvin, Goldsmith,

& Pan, 2008). Schmallegger and Carson (2008) suggested that the strategy of using blogs as an

information channel encompasses communication, promotion, product distribution, management, and

research. Other authors propose to view UGC websites as an aggregation of online feedback

mechanisms, which use internet bidirectional communication to share opinions about a wide range of

topics such as: products, services and events (Dellarocas, 2003), creating a network of digitized word-

of-mouth (Henning-Thurau et al., 2004). The aggregation of the entire range of online feedback about

a given product or service contributes on the creation of his own reputation (Dellarocas, 2001).

Managing the increasingly diverse range of sites and contents that build the web reputation, requires a

cross-disciplinary approach, which incorporates ideas from marketing, social psychology, economics

and decision making science (Malaga, 2001). Thus it is possible to argue that the construct “online

reputation” can be formed within the so called Web 2.0, and can be managed by destinations

(Inversini, 2009) holistically to attract more tourists.

Online Reputation in the Tourism field

Reputation is considered as “a collective assessment of a company’s ability to provide valued

outcomes to a representative group of stakeholders” (Fombrun, Gardberg, and Sever 1999), and is a

core component of an organization’s identity (Solove, 2007). Dowling (2001) underlined how tourism

is part of the experience industry, and should invest more in the development of its image: a prospect

customer select’s tourism service providers based upon their reputation.

The raise of internet as information channel creates new opportunities for promotion and marketing

strategies in the tourism industry. Not only the use of official websites is a challenge for the online

presence of a TD; the monitoring of the eWOM is also an activity in which TD managers are

investing efforts to find strategies to analyze online data produced by travellers. eWOM takes

generally place within social media websites, which allow users to easily upload contents such as text,

video, photos.

Scholars have studied the presence of social media on the firsts results of search engines (Xiang and

Gretzel, 2010), underlining how those websites are playing an important role as an information

channel for prospect travellers (Xiang, Wöber and Fesenmaier, 2008), and for them, a bad online

reputation found during online research can affect the final decision making process. As a recent

study from Li, Pan, and Zhang, (2009), a prospect customer is influenced by the affective components

expressed on social media websites (e.g. declaration of the experience satisfaction, hotel-restaurants’

reviews, recommendation of things to do once arrived at the destination).

A recent analysis of Nielsen Global Online Consumer Survey (April, 2009), shows the degree of trust

in several forms of advertising (e.g. from television, radio, online, newspaper): “consumer opinions

posted online” were perceived as trustworth by 70% of the respondents, while “recommendations

from people known” got 90%, and “brand websites” got 70%. Therefore, social media websites are

perceived as equally or more trustworthy than official websites.

Knowing the pieces of information a prospect traveller is likely to find in an online search becomes of

the utmost importance for reputation management, and is the final goal of this research.

The use of RepTrak and RepQuotient to guide eWOM analysis on a TD

Tourism destination (TD) is a complex organization, which acts as a hub with respect to the other

players and stakeholders within the destination itself (e.g. Inversini and Cantoni, 2009). Each single

player and stakeholder can influence the reputation of the entire TD (e.g. entities dedicated to the

product & services such as restaurants, hotels; society dimensions, such as residents and people

involved in delivering touristic products and services; public administration, infrastructure and so on).

The organizational complexity of a TD is emphasized by the internet. Looking at the information

available on a search engine about a given destination (i.e. its tourism online domain – Xiang et al.,

2009), it is possible to find mainly two types of websites: official websites and unofficial ones; both

are trying to reach end users’ attention and are concurring to present tourism related information

(Inversini and Buhalis, 2009), shaping the symbolic representations of the destination as a whole.

Thus, opinions generated by former tourists or residents trough the internet (eWOM) contribute to the

overall reputation of a TD. The opinions from users are expressed in specific online contexts: UGC

websites (Marchiori et al., 2010).

The use of the two models from the Reputation Institute (i.e. Reputation Quotient and RepTrak) has

been considered appropriate for the development of a Destination Online Reputation Model (DORM),

to be exploited in order to organize and interpret online contents; this approach has been considered

consistent with the Reputation Institute’s approach: although its procedure uses mainly surveys to

collect data about perceptions and attitudes of the relevant stakeholders about a given organization,

our approach proposes to consider online contents as perceptions already expressed by former tourists

or residents about a given destination, which only need to be classified and interpreted in order to

anticipate their potential impact on the decision of a prospect customer.

The overall goal of this research is to define and present a set of operational steps, which guide the

finding, harvesting, classification and interpretation of the tremendous amount of UGC present on the

web.

The Destination Online Reputation Model (DORM)

As it has been introduced above, this research presents and describes the application of a conceptual

framework (Figure 1), DORM (Destination Online Reputation Model), to analyse online contents, and

specifically UGC about a TD. Recent works from Inversini et al. (2010) and Marchiori et al. (2010)

presented the adaptation to destination-related online contents. This model classifies online

conversations in relevant dimensions of reputation drivers, and scores this content based on the tone

(positive, negative, or neutral) of the destination coverage.

This model was firstly applied to the content related to London (Inversini et al. 2010). No research has

been so far performed on the perceptual and attitudinal side of the reputation process. DORM

considers the specific characteristics of a TD as a unique and complex organizational unit of the

tourism industry. Researchers used the Reputation Quotient and the adapted version RepTrak (2006)

presented by the Reputation Institute (RI), which are based on 23 drivers that work as predictors of

reputation (Vidaver-Cohen, 2007).

The drivers are grouped in 7 core dimensions: Organizational Leadership, Product & Services quality,

Workplace environment, Performance, Citizenship activities, Innovation initiatives and Governance

procedures. Using these two models (RQ and RepTrak) as a base, authors adapted the core

dimensions and reputation drivers to the reputation of a tourist destinations, considering its

characteristics within the tourism industry.

Figure 1 – DORM core dimensions and drivers.

External layer: original reputation dimensions from RepTrak

The framework was created and adapted thanks to an extensive literature review and it was validated

through semi structured interviews with domain experts (experts and practitioners in new media,

economy of tourism, brand reputation) in order to collect the interviewees’ perception on how the

elements of the proposed model relate with each other, and influence the reputation of a TD

(Marchiori et al. 2010).

During the semi structured interviews, domain experts were asked to rank the importance of each of

the 7 core dimensions featured by the model and to add any additional element perceived as having an

influence upon the overall reputation of a destination. Results confirmed the 7 core dimensions and 22

reputation drivers presented in Table 1: the external layer shows the dimensions from RepTrack,

whereas the internal layers show the adapted reputation tourism dimensions with the relatives drivers.

Contribution of DORM to the Online Tourism Domain Analysis Through Search Engines

Search Engines can be considered as the preferred gateway used by internet users (Nielsen Media,

Wöber and

Figure 2. Integration of DORM process on

Travelers’ Use of a Search Engine for Trip Planning framework from Xiang et al. (2008)

1997) and specifically by prospective travelers to reach online information. Xiang,

Fesenmaier (2008) underlined that only a tiny part of pages indexed by the popular search engine

Google are dominating the results. Thus working on search engine positioning for tourism business

and destinations means to fight to gain user attention and traffic on their own website (Inversini and

Cantoni, 2009). On the other side, understanding the contents that are out of destination marketer’s

control, especially UGC, is an actual need in the tourism industry.

Figure 2 shows the integratio Xiang, Wöber

and Fe spect

traveller, who has some mental models; the DORM approach contributes both in shaping common

queries (i.e. name of the destination plus popular tourist keywords) and helps within the search results

content classification with seven reputation dimension (23 drivers) and with the tone analysis.

Sustainable TDs case study

n of DORM approach within the framework elaborated by

senmaier (2008): the tourism online domain is accessible trough search engines by a pro

Research Design

A previous research on destination online reputation focused on a popular destination (e.g. London –

sults suggested that only few dimensions in the DORM model could be

considered as relevant while dealing with this topic (popular tourism destination), namely products

and services, leadership and society; few work has been done so far to understand if niche

destinations, such as the sustainable ones, might present different online contents and/or online

discourses. In order to tackle this issue, this research focuses on sustainable TDs, which are defined

by the World Tourism Organization (UNWTO) as follows: “Sustainable tourism development meets

the needs of present tourists and host regions while protecting and enhancing opportunity for the

future. It is envisaged as leading to management of all resources in such a way that economic, social,

and aesthetic needs can be fulfilled while maintaining cultural integrity, essential ecological

processes, biological diversity, and life support system.” (WTO, 1998: 19).

ing process. Tendencies

related to the topic of this research show (i) an increased tourists’ awareness for the environment, (ii)

a higher consciousness of quality and value for money, (iii) more selected choice of destination, (iv)

tourists have become more physically and intellectually active, (v) tourists want to visit places, which

are environmentally friendly and socially. Furthermore, (vi) there is a general tendency to increase the

use of technology – especially internet. In other words, sustainable tourism destination is ecologically

sustainable, economically viable as well as ethically, and socially equitable; thus, moving from this

Inversini et al., 2010) and re

From the Sustainable Tourism Development Report (UNESCO, 2009), the behavioural aspects in the

tourism field point out several tendencies for the tourists’ decision mak

perspective, it can be anticipated that a relevant part of online content and online discourses about

sustainable destinations fit into the two related DORM dimensions: Environment and Society.

DORM application for the sustainable TD analysis

zed as

sustainable and mentioned in popular sustainable TDs lists (Top Five Destinations for Ecotourism -

Independent Traveleler.com; Top Ten Eco-Friendly - gogreenearth.com 2009; European Destinations

The selected destinations were: (i) Reykjavik, (ii) Palau, (iii) Malta. In order to find online contents

and online discourses about them, a set of search engine queries were defined; since search engines

provide one of the primary “access to the information” for travellers.

ogle was used as the only search engine for this study

ue to its popularity among internet users also in the travel sector (Hopkins, 2007; Bertolucci, 2007).

The research is designed as a multiple case study. The three destinations selected were recogni

of Excellence – EDEN project – which are a showcase for local environment, culture and social fabric

preservation and enhancement). Furthermore, islands were selected in order to facilitate the definition

of the destination boundaries: in fact the concept itself of destination sometimes does not match

specific geo-administrative boundaries, but only with socially perceived coordinates, which can have

different granularity levels: a destination, in fact, is a social construction built by communication acts

such as “impressions, prejudice, imaginations and emotional thoughts an individual or group might

have of a particular place” (Baud-Bovy, Lawson, 1977).

The methodological approach has been mainly based on content analysis: (i) data collection was made

thanks to extensive queries on a given search engine; (ii) results were analyzed thanks to a destination

reputation codebook (Marchiori et al., 2010).

(i) Data collection was made querying the popular search engine Google.com (international version,

from Lugano, Switzerland, in March 2010). Go

d

The name of the destinations was mixed with specific travel keywords (Xiang et al., 2009) as

presented in Table 0.1.

D1: Reykjavik D2: Palau D3: Malta Visit Reykjavik Visit Palau Visit Malta

Travel Reykjavik Travel Palau Travel Malta Holiday Reykjavik Holiday Palau Holiday Malta Vacation Reykjavik Vacation Palau Vacation Malta Table 0.1 Name of the destinations mixed with specific travel keywords

The four keyw erform activitie ; the first three

results pages (

nalyzed (120 results per destination, 3 times)

Buhalis (2009) where coders were asked to assess each

RL within the search activity following a set of codes starting from the technical classification of the

The following research questions were formulated to guide the research:

e directly accessed by users based upon specific queries?

II. Which reputation dimensions and drivers are mainly represented by found texts?

ords were used to p different search s on google.com

i.e. 30 results overall) were considered (Comescore, 2008). Thus 360 results were

a

(ii) Content analysis was done with two coders, using a version of the Destination Reputation

Codebook presented by Inversini, Cantoni and

U

medium up to the main content recognition (DORM dimension and value expressed). The atomic unit

of the analysis for the study was the landing page: each coder was asked to identify the major DORM

driver in its text, in case more than one were equally represented, up to three drivers for a single

landing page could be coded.

I. How many UGC can b

Results

Information market

rstly helped to map the information market around the four destinations (Table 1). Among

the 360 analyzed results, 86 contained UGC (23.8 %), 234 did not contained UGC and 40 were not

working or not relevant (these website were intended as the ones not accessible or with no relevance

Table 1. Information Market around the four destinations.

Among the analyzed destinations only Palau presented a balance betw en User Generated Content

(UGC) websites (n=47) and not User Generated Content websites (n=44). The same destination

unfortunately presented a high number of not working and not relevant websites (n=29). In the other

Results fi

for the touristic market). These results confirmed that social media and UGC websites are playing a

relevant role in the online tourism domain (Greztel and Xiang, 2009), and counted for the 23.8% of

the overall results. This tendency is confirmed also by other studies in the field (e.g tendency of

20.5% in Inversini et al., 2010).

UGC NOT UGC NR-NWReykjavik 26 89 5Palau 47 44 29Malta 13 101 6Tot 86 234 40

e

cases the number of not UGC websites is always greater than the number of UGC websites. Among

UGC websites, consumer review websites were the most present UGC (n=32, Tripadvisor being the

most present website for this category). Virtual communities and blogs were also predominant in the

tourism online domain analysed and lonelyplanet; vistualtourist; travbuddy, and 43things websites

were the most present ones.

Figure 3. UGC websites in the four analyzed destinations.

Figure 3 shows how the UGC information market is organized among the four destination. UGC

websites were classified according to five categories: virtual community, consumer review, blog and

micro blogging, social network, media sharing, wiki and other UGC (Gretzel, 2010). Considering

each destination it is possible to underline that consumer reviews (8.3%), and other UGC (6.7%) were

the most important categories for Reykjavik, wiki (2.5%) and Other UGC (3.3%) were really relevant

for Malta and consumer review (5.8%) and blog and micro blogging (5%) were relevant for . Due to

the limited number of not UGC websites (36.7%) Palau had interesting results for virtual community

(12.5%), consumer review (10%) and blog and micro blogging (6.7%).

Content assessment

Once UGC websites were identified, content from each single landing page was analyzed and

associated to specific drivers (up to three): e.g. a trip description written on a virtual community could

present contents related both to the dimension of products and services as well as to the dimension of

society; in that case coders counted two items associated to one driver each, each of them with a

specific value judgement.

Only 16 drivers out of 23 appeared in the UGC websites. Only seven drivers appeared in all the

destinations’ results, mainly for products & services dimension (i.e. d1, d2, d3, d5, d9, d18 and d22).

The minimum number of major drivers which were preset in the UGC results for the analyzed

destination was 9 (i.e. Malta and ), while Reykjavik presented 10 drivers. Interesting is the fact that

Palau outperformed all the other destination presenting 15 drivers. This is mainly due to the high

number of UGC websites retrieved in the search engine. On the one sides, society and environment

dimensions drivers were present and distributed in the 3 destinations; as regards the society

dimension, d9 (destination offers interesting local culture and traditions) is present in all the

destinations, d10 (destination has hospitable residents) is not present in Reykjavik. As regards the

environment dimension, d14 (destination is responsible in the use of its environment) is not present in

Malta and surprising d15 (destination supports ecological initiatives) is present only in Palau. On the

other side it is possible to notice that only product and service and environment dimensions had got all

the drivers mentioned at least for one destination. Finally, the means of the drivers’ occurrences of the

sustainable destinations together with the percentage of the positive value expressed was compared

between the sustainable destinations group (Table 2).

Dimension Code Driver Driver Occurrence

PositiveValue Expressed

d1 D. offers quality tourism P&S 13 (4.4*) 61.5%d2 D. offers a pleasant environment 8 (9.6*) 95.8%d3 D. features adequate infrastructure for tourists 4 (1*) 75.0%d4 D. offers a safe environment 0.7 (1.2*) 100%d5 D. offers P&S that are good value for the money 3.7 (3.1*) 36.4%d9 D. offers interesting local culture and traditions 4.3 (2.3*) 76.9%d10 D. has hospitable residents 2.7 (3.1*) 62.5%d17 D. presents accurate info of their P&S 1.7 (2.1*) 60.0%d18 D. presents an accurate image as a tourism destination 4.3 (4*) 76.9%d14 D. is responsible in the use of their environment 4.3(6.7*) 92.3%d15 D. supports ecological initiatives 0.7 (1.2*) 50.0%d21 D. meets my expectations as a tourism destination 1.3 (2.3*) 100%d22 D. offers a satisfying tourism experience 2.3 (2.1*) 85.7%d11 D. tourism industry and organizations cooperates and

interacts between them1 (1*) 33.3%

d12 D. tourism industry and organizations behave ethically in confront of their visitors and residents

1 (1.7*) 33.3%

Innovation 0.6%

d6 D. improves tourism P&S 0.3 (0.6*) 100%

Not Applicable 4.2%

d23

Leadership 10.7%

Performance 6.6%

Products & Services 52.6%

Society 12.5 %

Governance 3.6%

Environment 9%

Table 2 – Drivers occurrence and value expressed within the sustainable destinations.

The mean, the standard deviation and items percentage have been considered.

Table 2 shows that the products and services dimension counted for 52.6% of the total results (which

means that it obtained the most presence of the drivers mentioned): d1, d2 and d3 are relevant with an

overall of good value judgment. Besides, d4 and d5 which are not appearing in were found

contradictory: d4 regards the safety of environment and scored totally positive, while d5 which

regards the good value for money scored positive only for the 36.4% of the contents. Performance

dimension seemed important for sustainable destinations with an overall positive value judgment.

Governance and innovation dimensions were not relevant but they had contradictory results: content

about governance were judged positive (33.3%), while contents about innovation were considered

very positive by coders (100%).

Society (counted for 12.5%) and Environment (counted for 9%) dimensions which were considered

relevant as predictors of reputation for sustainable destinations were analyzed as follows: d9

(destination offers interesting local culture and traditions) was not so relevant but it obtained better

value judgments in the online discourses. D10 (destination has hospitable residents) was more

relevant but it obtained an overall positive score only in online contents. D14 (destination is

responsible in the use of its environment) was relevant positive value judgment scores (92.3%).

Finally, d15, (destination supports ecological initiatives) was present with only 50% of positive value

judgment.

Conclusions

Results show that only 16 drivers out of 23 were present within the four destinations. So that only

these 16 drivers might be considered as reputation predictors within the analyzed destinations.

In all the three destinations labelled as sustainable there was a considerable presence of the drivers

about Product and Service dimension (52.6%). This could be partially justified by the fact that

regardless the overall promotion strategy and positioning of the destination (e.g. sustainable tourism

destination) one of the major topic for the online discussions is products and services: themes related

to accommodations are always a very important discussions’ starting point. This finding confirmed a

tendency presented in Inversini et all. 2010: the tourists always need accommodations while being

abroad and due to the abundance and popularity of the accommodations’ review websites (e.g.

tripadvisor.com) they judge and review online the hotel where they stayed. Furthermore, it is possible

to find different results coming from websites such as tripadvisor.com in the first thirty search engine

results due to the constant popularity that the web2.0 websites are gaining within search engine results

(Gretzel, 2006).

Finally, Environment and Society DORM dimensions cannot be considered as reputation predictors

for sustainable destinations, but as regards Society DORM dimension, the driver d9 is very popular

among the destinations analysed, and driver d10 only lacks in the Reykjavik results. The overall value

judgment for the destination labelled as sustainable is positive. Values, (i.e. d9: 76.9% positive and

d10: 62.5% positive) indicates that there are discussions about the society dimension within the

destination; these specific discussions could be deeply analyzed and the discussions moderated by the

Destination Management Organization to foster the sustainable image of the destination. As regard

the Environment dimension, only driver d14 is very popular while d15 (the driver about ecological

initiatives) did not appear in the online conversations. This result sounds strange for the overall

communication strategy used by these destinations. In order to foster their sustainable reputation in

the online tourism domain, destinations might guide discussions also about these topics in order to

reflect in the online market their communication strategies and activities.

Limitations mainly regards (i) the limited number of destinations considered and (ii) the time

consuming nature of this content analysis practice. This study should be repeated on a larger number

of destinations in order to capture different online discourses and to better explore the domain.

Moreover, the need of automatic instruments or tools able to harvest and categorize online content is

important. Content analysis requires trained coders able to analyze a big number of online documents

in a proper way. Furthermore, this study represent a snapshot of the online discourse about a group of

destinations. Destination Managers may need to constantly monitor their online reputation in order to

modify their online communication strategies and to holistically manage reputation.

Future work will mainly deal with the fine tuning of the DORM model. Findings allow to further

explore products and services dimension due to its importance within the destinations analysed: e.g.

adding sub-dimensions such as: accommodation, events, food & beverage, site attractions, outdoor

activities, in order to better define the topics expressed online.

Furthermore, a comparison among official DMO websites and online discoursers will be studied to

better understand misalignments of online communication.

References

Anderson, C. (2006). The Long Tail: Why the Future of Business is Selling Less of More. Hyperion, NY

Baud-Bovy, M., Lawson, F. (1977), Tourism and Recreation Development, Architectural Press, London

Bertolucci, J. (2007). Search engine shoot-out. PC World, 25(6), 86-96

Blackshaw, P. (2006). The consumer-generated surveillance culture. Retrieved October 13, 2008, from

http://www.clickz.com/showPage.html?page=3576076

Blackshaw, P., & Nazzaro, M. (2006). Consumer-generated media (cgm) 101: Word-ofmouth in the age of the

web-fortified consumer

Bolton,G.E., Katok,E., Ockenfels, A. (2004). How Effective Are Electronic Reputation Mechanisms? An

Experimental Investigation. Management Science, 50(11), 1587-1602

Boulos, MN. and Wheeler S. (2007) The emerging Web 2.0 social software: an enabling suite of sociable.

Buhalis, D. (2003). eTourism: Information technology for strategic tourism management. Prentice Hall, Harlow

Cantoni, L. and DiBlas, N. (2002) Teorie e Pratiche della Comunicazione, Apogeo, Milano

Cantoni, L. and Tardini, S. (2006). Internet (Routledge Introductions to Media and Communications).

Routledge, London – New York

Cantoni, L., Tardini, S. (2010), The Internet and the Web, in D. Albertazzi & P. Cobley (eds), The media. An

introduction (3rd ed.), New York et al.: Longman, 220-232

Choi,S., Lehto, XY., Oleary, JT. (2007). What does the consumer want from a DMO website? A study of US

and Canadian tourists perspectives. International Journal of Tourism Research. 9, 59-72

Comescore, (2008), comScore Releases December U.S. Search Engine Rankings, Retrieved March 2008,

http://www.comscore.com/press/release.asp?press=2016

Dellarocas, C. (2003). The Digitization of Word-of-Mouth: Promise and Challenges of Online Reputation

Mechanisms, Management Science, 49 (10), 1407-1424

Dowling, G. (2001). Creating Corporate Reputations. Identity, Image, and Performance. Oxford: Oxford

University Press

EDEN - Destination of Excellence (2009). Tourism Sustainable Development Unit.

https://secure2.gov.mt/TSDU/eden

Fombrun, C. J., Gardberg, N. A., & Sever, J. M. (1999). The Reputation Quotient sm: A multi-stakeholder

measure of corporate reputation. The Journal of Brand Management, 7 (4), 241-255

Gogreenearth (2009). Top Ten Eco-Friendly Cities of World

http://gogreenearth.wordpress.com/2009/11/17/top-ten-ecofriendly/

Henning-Thurau, T., Gwinner, K.P., Walsh, G., Gremler, D., D. (2004). Electronic Word of Mouth via

consumer opinion platforms: what motivates consumer to articulate themselves on the Internet? Journal of

Vacation Marketing, 18 (1), 38-52

Hopkins, H. (2008). Hitwise US travel trends: how consumer search behaviour is changing. Available from:

http://www.hitwise.com/registration-page/hitwise-report-travel-trends.php

Inversini, A., Buhalis, D. (2009). Information Convergence in the Long Tail. The Case of Tourism Destination

InformationIn. In W. Hopken, U. Gretzel & R. Law (Eds.), Information and Communication Technologies in

Tourism 2009 - Proceedings of the International Conference in Amsterdam, Netherland (pp. 381-392). Wien:

Springer

Inversini,A., Cantoni,L. (2009). Cultural Destination Usability: The Case of Visit Bath. In W. Hopken, U.

Gretzel & R. Law (Eds.), Information and Communication Technologies in Tourism 2009 – Proceedings of the

International Conference in Amsterdam, Netherland (pp. 319-331). Wien: Springer.iProspect

Inversini,A., Cantoni,L., Buhalis,D. (2009) Destinations Information Competition and Web Reputation. To be

published in the International Journal of IT in Travel and Touirsm

Inversini A., Marchiori E., Dedekind C., Cantoni L. (2010). Applying a Conceptual Framework to Analyze

Online Reputation of Tourism Destinations. in Ulrike Gretzel, Rob Law & Matthias Fuchs (eds.), Information

and Communication Technologies in Tourism 2010 (Proceedings of the International Conference in Lugano,

Switzerland, February 10-12, 2010), Springer, Wien – New York 2010, pp. 321-332

Jenkins, H. (1999). Understanding and measuring tourist destination images. International Journal of Tourism

Research: 1-15

Lawson, F., and Baud-Bovy, M. (1977). Tourism and Recreational Development. London: Architectural Press

Li, X., Pan, B., Zhang, L., (2009). The Effect of Online Information Search on Image Development. Journal of

Travel Research, Vol. 48, No. 1, 45-57

Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism

management. Tourism Management, 29, 458-468

Malaga, R., A..(2001) Web-based reputation management systems: Problems and suggested solutions.

Electronic Commerce Research, 1(4)

Marchiori, E., Inversini, A., Cantoni, L., Dedekink,C. (2010). Managing Tourism Destinations Online

Reputation. Accepted to 6th Thought Leaders International Conference in Brand Management, Lugano - CH

Nicholas, D., Huntington, P., Jamali, H.J. Dobrowolski, T. (2007). Characterizing and evaluating information

seeking behavior in digital environment: spotlight on the bouncer. Information processing and Management,

43(4), pp 1085-1102.

Nielsen Global Online Consumer Survey (April 2009). Global Advertising: Consumers Trust Real Friends and

Virtual Strangers the Most. http://blog.nielsen.com/nielsenwire/consumer/global-advertising-consumers-trust-

real-friends-and-virtual-strangers-the-most/

Nielsen Media. (1997). Search engines most popular method of surfing the web (Website). Commerce

Net/Nielsen Media. Retrieved 30.8.2000 from the World Wide Web:

http://www.commerce.net/news/press/0416.html.

O’Reilly, T. (2005). What Is Web 2.0. http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/ what-is-

web-20.html

Pan, Bing., & Fesenmaier, Daniel R. (2006). Online Information search. Vacation Planning Process. Annals of

Tourism Research, 33(3), 809–832

Peter, J., and J. Olsen. (2002). Consumer Behavior and Marketing Strategy. 6 ed. Boston, MA: McGraw-Hill

Irwin

Poon, A. (1993). Tourism, Technology and Competitive Strategies. Wallingford, CT: CAB International,

Oxford

Schlichter, S. Top Five Destinations for Ecotourism. Independent Traveler.com

http://www.independenttraveler.com/resources/article.cfm?AID=741&category=22

Schmallegger, D., & Carson, D. (2008). Blogs in tourism: Changing approaches to information exchange.

Journal of Vacation Marketing, 14(2), 99-110

Sheldon, P. (1997). Tourism Information Technology. CABI Publishing: Wallingford

Solove, D. J. (2007). The future of Reputation. Gossip, rumor, and privacy on the internet. London: Yale

University Press

Thevenot, G. (2007). Blogging as Social Media. Tourism and Hospitality Research, Vol 7, 3 /4, pp 282-

289Xiang, Z. and Gretzel, U.(2009, Forthcoming). Role of Social Media in Online Travel Information Search.

Submitted to Tourism Management

Vidaver-Cohen, D. (2007). Reputation Beyond the Rankings: A conceptual framework for Business School

Research. Corporate Business Review. 10(4): 278-304

Yoo, K. H. and U. Gretzel (2008). The influence of perceived credibility on preferences for recommender

systems as sources of advice. Journal of Information Technology & Tourism, 10(2): 133-146

Xiang, Z., Wöber, K. and Fesenmaier, D.R. (2008). Representation of the Online Tourism Domain in Search

Engines. Journal of Travel Research 47; 137

Xiang, Z. and Gretzel, U. (2010). Role of Social Media in Online Travel Information Search, Tourism

Management. Vol. 31, No. 2, pp. 179-188

Ecological Tourism in Europe/UNESCO-BRESCE (2009): The trail planning guide. An insight into the process

of planning interpretative trails

Werthner, H. and Klein, S. (1999) Information Technology and Tourism – A Challenging Relationship, Wien,

New York: Springer

World Tourism Organization (UNWTO) (2004): Indicators of sustainable development for tourism destinations.

A guidebook – Madrid