Phase A3 Classification system refinement via users’ perceptions

Phase A3 presents the results of a survey carried out to validate eTDR (Tourism Destination Reputation in Online Media framework). The survey addressed the destination demand side, namely prospective tourists (people who travel for leisure), and was performed in order to collect their perception on how the elements of the proposed model can influence the perception of reputation regarding a tourism destination.

The study was performed in two Italian airports (airport might nowadays be recognized as one of the most important transport nodes for tourism). Two airports of Milan (Italy), Malpensa and Linate, were chosen as they are responsible for transporting international and domestic visitors to national and international tourism destinations attractions. According to Assaeroporti (Italian Airports Association), Malpensa and Linate were respectively the second and third most important airports in Italy during the year 2009 in terms of passengers (almost 26 million passengers, preceded only by the airport of Fiumicino, Rome). Passengers were interviewed at the airport gates or in the surrounding area prior their flight departure. Since the two airports have both national and international flights, it has been possible to interview tourists of different nationalities. A total of 502 surveys were collected in eleven days (six days in Linate and five days in Malpensa); of all the surveys collected, 485 were considered usable. The analysis has been carried out from the 6th August to the 23rd August 2010.

Objectives of the Phase A3 were:

(i) to asses eTDR relevance on the demand side, directly interviewing prospective tourists in order to (ii) test which kind of destination topics are more relevant on the decision-making process; (iii) understand, among the tourists who trust online conversations more, what are the key drivers destination influencing the decision making process.

The questionnaire was divided in two parts: i) ranking of the eTDR drivers in order to explored which kind of topics are more relevant during the decision-making process, ii) a set of questions to collect data on demographics, use of Internet and tourism habits. This second part of the survey has to be considered as essential to explored the link between trust and inclination to be influenced by online conversations. Finally, the questionnaire also collected data on information sources used in holiday decision making; and age, gender, and place of residence (see Appendix 1).

3.4 Phase A3. Classification system refinement via users’ perceptions 87

Profile of Respondents

There were slightly more female (53.5%) than male (46.5%) respondents to the survey, and the majority of the respondents belonged to the age range 18-29 (58,5%); 39% to the age range 30-49, while only the 2,5% were more than 50 years old. 84.3% of respondents are Italian, while the other 15.7% were spread among other 25 countries, such as UK (3.3%), Australia (1.9%), France, and US (both 1.4%).

Analysis of tourists’ use of online conversations

The respondents recognize the importance of tourists’ comments, reviews and suggestions that can be found online, thus social media websites might be considered as one important component of the information gathering. Results indeed showed that 92.1% of people that use other tourists’ contents, either voluntary or coming across when searching for information. Only 2.7% of the respondents were not able to distinguish tourists’ generated resources from the whole contents provided by the web, while 5.3% did not use online conversations at all. Consumer reviews websites such as TripAdvisor or Booking were the most used social media online travel sources (69.3%), followed by wikis (e.g. wikitravel.org) with 28.9%, social networks like Facebook (15.3%), media sharing websites (e.g. YouTube or Flickr, 12.2%), blogs (9.3%) and other types of sources such as virtual communities (5.2%).

Respondents were influenced by online conversations produced by other tourists: 61.7% of the interviewees stated that online conversations have an average or high influence on their decision-making process for the destination choice. The remaining 39.3% were low influenced or not influenced at all.

Analysis of tourists’ trust towards online conversations

Respondents considered the contents produced by other tourists as trustworthy: when asked to rate their trust towards online conversations, only 19.2% of interviewees declared to have low or very low trust; more than 26% of respondents have high or very high trust towards online conversations. Interviewees were asked to express the importance they give to the following motivations of being trustful regarding an online conversation:

- High number of replies (3.32 mean)

- Comments and/or replies up to date (3.48 mean) - Author of the comment profile (2.65 mean) - Other users’ approval (3.22 mean)

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Since the question was structured as a Likert scale one (where the value 1 is ‘not important at all’ and 5 is ‘very important’), the higher is the mean the more important is the motivation for the respondents. According to these results, it is possible to state that for interviewees the availability of updated comments (or replies) is the most important motivation in order to consider online conversations trustworthy (mean 3.48). Thus having a high number of replies and the approval of other users is considered quite important for an online conversation (mean respectively 3.32 and 3.22), while the profile of the author is seen as not so important (mean 2.65).

Relevance of destination topics on the decision-making process. Analysis of the destination reputation drivers’ ranking

Respondents were asked to order from 1st position to 14th position each eTDR driver, results are presented in Table 3.16. Respondents could choose to not order drivers considered as not important.

Table 3.16. Topics which influence the reputation in online media of a tourism destination from a demand viewpoint

Dimension Driver Average

position

Products and Services

D. offers a satisfying tourism product 5.56 D. offers a pleasant atmosphere 8.73 D. offers products and services that are good value for the money

4.49

D. presents accurate information of their tourism products and services

10.14

Society _{D. offers interesting local culture and traditions} 8.62

D. has hospitable residents 8.74

Governance _{D. tourism industry and organizations cooperates and}

interacts between them

12.02

D. presents innovative and/or improved tourism products and services

12.03

Environment _{D. has an high eco-awareness} 12.64

D. has a favourable weather 7.96

D. offers a safe environment 6.78

Performance _{D. presents an accurate image as a tourism destination} 9.27 D. meets my expectations as a tourism destination 9.11 D. offers a satisfying tourism experience 6.93

3.4 Phase A3. Classification system refinement via users’ perceptions 89

Value for money (driver listed on the Product and Services dimension) was the most influential element of the reputation in online media of a tourism destination, having reached an average position of 4.49. The other three drivers that can be considered as influencers of reputation in online media were product satisfaction (5.56), safety (6.78) and overall satisfaction (6.93).

However, among the respondents there was no general agreement about the elements shaping the reputation in online media of a tourism destination; in fact, the average position of the best driver, value for money, was 4.49: it means that the interviewees ranked this driver on average between 4th and 5th place. A general agreement could have been identified if the best driver/s was positioned on average at 3th place or above. On the other hand, there was a general agreement about the least influential drivers: interaction between tourism industry and organizations (12.02), innovation (12.03) – both belonging to the Governance dimension – and destination’s eco-awareness (12.64).

Influence of specific destination topics on the decision-making process of online conversations trustful tourists:

Through the use of the ‘Independent Samples T-Test’, a comparison of the means of two groups on a given variable can be achieved. Basically, the drivers and another variable (i.e., trust and influence) were crossed in order to highlight possible significant differences among different groups of the variable itself.

In table 3.17 the difference between people who have low trust towards online conversations and those who have high trust is presented. Findings shown that the two drivers Product satisfaction and Overall satisfaction were definitely more important for people who have high trust towards online conversations (respectively 4.78 vs. 7.06 and 6.16 vs. 7.83). These two drivers are very “Online conversations-oriented” (e.g. more than drivers such as safety or weather): thus this type of result could have been expected.

Table 3.17. T-Test:Trust towards online conversations

Driver Trust rate Mean Sig. (2-tailed) 95% Confidence Interval of the difference Lower Upper Product satisfaction 1-2 7.06 .001 .969 3.651 4-5 4.78 .001 .914 3.656 Overall satisfaction 1-2 7.83 .024 .227 3.114 4-5 6.16 .026 .226 3.135

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Table 3.18. T-Test: Influence of online conversations in destination choice or vacation planning

Driver Influence

rate

Mean Sig. (2-tailed) 95% Confidence Interval of the diff. Lower Upper Product satisfaction 1-2 6.82 .000 1.017 3.317 4-5 4.65 .000 1.061 3.273 Local culture 1-2 7.95 .006 -2.662 -.447 4-5 9.50 .005 -2.638 -.471 Image 1-2 10.18 .000 .900 3.058 4-5 8.20 .000 .922 3.037 Meeting of expectations 1-2 9.87 .000 .998 3.233 4-5 7.75 .000 1.012 3.220 Overall satisfaction 1-2 7.96 .006 .492 2.914 4-5 6.25 .005 .516 2.889

Table 3.18 shows that together with Product satisfaction and Overall satisfaction, the drivers Image and Meeting of expectations were more important for people that are highly influenced by online conversations when choosing a destination or planning a vacation. Surprisingly, the driver Local culture and traditions was more important for the “low-influenced” (7.95 vs. 9.50).