Destination Reputation in Online Media: Covered Topics and Perceived Online Dominant Opinion

Destination Reputation in Online Media: Covered Topics and

Perceived Online Dominant Opinion

Ph.D. DissertationElena Marchiori

Supervisor: prof. Lorenzo Cantoniwebatelier.net Lab, Faculty of Communication Sciences

Università della Svizzera italiana, University of Lugano - Switzerland

questions classification perceptions findings futuretheoretical

Govers and Go, 2005, 2009 Xiang and Gretzel, 2009

Cultural identity tension Commerce

Tourism hedonic consumption experience

context

eWOM

context questions classification perceptions findings futuretheoretical

Govers and Go, 2005, 2009 Xiang and Gretzel, 2009

Cultural identity tension Commerce

Online public opinions are creating challenges for the tourism industry

Gretzel, 2006; Tussyadiah, et al, 2011; Xiang and Gretzel, 2009; Yang et al. 2008


eWOM – Social Media shift from an “architecture” brand perspective… Morgan et al. 2003, 2004; Go and Govers, 2009; Xiang and Gretzel, 2009

Rethinking Place Branding strategies


… to a “live context perspective” Morgan et al. 2003, 2004; Go and Govers, 2009; Xiang and Gretzel, 2009


eWOM

Public opinions

• Agenda setting theory (McCombs et al., 1972; Weaver et al., 1981; Noelle-Neumann, 1974; Ho and McLeod, 2008)

• Social information processing (Walther, 1992; 2009; Antheunis et al., 2010)

• Signaling theory (Connelly et al., 2011)• Dual process theory

(Deutsch and Gerard, 1955; Chaiken and Trope, 1999; Cheung et al., 2009)

social influence

and

message elaboration

Arndt, 1967; Katz and Lazarsfeld, 1955; Blackwell et al., 2001; Gruen et al., 2006; Hennig-Thurau et al., 2004; Chen and Xie, 2008; Sharma et al., 2012; Blackwell et al., 2001; Zhou and Moy, 2007


image

reputation



Organization reputation studies antecedents reputation consequences

Research Objectives


Organization reputation studies

Message elaboration Dual process theory Media effects studies

antecedents reputation consequences

Online message cues

??? ???

Second-hand experiences (online conversations)

Belief Attitudes

Confirmation/disconfirmation of prior belief

???

Research Objectives





Online message cues

??? ???


Belief Attitudes


WHATThematic dimensions of tourism destination

WHICH

drivers influencing the perception of reputation in online media

???

Research Objectives

• simplification • cognitive associations to an object • might drive the behavior

Bergler, 1948; Jackman, 1990

Psychological


• collective agreement • social construct• give a degree of legitimacy to an actor

Lang & Lang, 1988; Camic, 1992

Psychological Sociological


Psychological Sociological Economic • cognitive interpretation of the

organization performanceShapiro, 1983; Allen, 1984; Weigelt & Camerer, 1988


Psychological Sociological Economic

reputation is a de-verbal noun, derived from the latin verb:RE (prefix) = iteration of something- evaluative dimension PUTO (verb) = opinion vs. exact information

Linguistic

putoputo

putoputo

puto putore-


2. stakeholder 3. relevant object

5. long-term/stable4. social/group of people

Puto -

Re -

1. opinion

b. set of reference values/standards

c. direct / mediated

a. multidimensional experience




Puto -

Re -

1. opinion





Judgments/ feelings expressed on the online conversation Dickinger et al. (2011); Go, Govers (2005); Choi et al. (2007); Pan et al. (2007); Ip et al. (2011); Scharl et al. (2008); Govers, Go (2005); Tussyadiah, Fesenmaier (2009)

Longitudinal Study(professional tools)

Authors, website’ s ownerArsal et al. (2008); Mich, Kiyavitskaya (2011); Zhu, Lai (2009); Chiappa (2011); Burgess et al. (2009)

Tourism destination

multidimensional categories

Dickinger et al. (2011); Go, Govers (2005);

Tussyadiah, Fesenmaier (2009); Choi et al. (2007); Pan et al. (2007); Ip et al. (2011); Scharl et al. (2008)

Information provided by different sources De Ascaniis, Greco Morasso (2011); Inversini, Cantoni (2009)

Online contents analysis: the measurement issue

Offline survey and data presented online produce similar results (Dickinger et al., 2011)

However:- not standard models and procedures- contents online is time consuming - heavy delegation to technology- confusion with:

- consumer brand advocacy- reported consumer experiences- different type of influence(Mandelli, 2011)


?





Online message cues

??? ???


Belief Attitudes



WHICH


HOW

???

Research Objectives

Steps to create a contents classification framework

1. Extensive literature review adaptation of a RepTrak model/Rep Quotient model

structured interviews with the tourism domain experts

2. Online content analysis case studies (n° 4)

3. Survey with the destination demand side (prospective tourists – leisure travelers: 485 usable responses) in order to rank the topic dimensions of the proposed model

4. Test with untrained users in order to evaluate users’ agreements on recognizing the dominant topic, and the dominant feeling expressed on social media pages


Online contents classification framework

Core Dimensions Drivers Avgposition

Products and Services(Subcategories: )AccommodationFood & BeverageSite AttractionsEventsEntertainmentTransportationInfrastructureOther

1 Destination offers a satisfying tourism product 5.56

2 [D] offers a pleasant atmosphere 8.73

3 [D] offers products and services that are good value 4.49

4 [D] presents accurate information of their products and services

10.14

Society5 [D] offers interesting local culture and traditions 8.62

6 [D] has hospitable residents 8.74

Governance

7 Tourism industry and organizations cooperate and interact 12.02

8 [D] presents innovative and/or improved products and services 12.03

Environment9 [D] has a high eco-awareness 12.6410 [D] has a favorable weather 7.96

11 [D] offers a safe environment 6.78

Performance

12 [D] presents an accurate image 9.2713[D] meets my expectations 9.11

14 [D] offers a satisfying tourism experience 6.93


Online contents classification framework

Core Dimensions Drivers Avg. position

Products and Services(Subcategories: )AccommodationFood & BeverageSite AttractionsEventsEntertainmentTransportationInfrastructureOther

1 Destination offers a satisfying tourism product 5.56

2 [D] offers a pleasant atmosphere 8.73

3 [D] offers products and services that are good value 4.49

4 [D] presents accurate information of their products and services

10.14

Society5 [D] offers interesting local culture and traditions 8.62

6 [D] has hospitable residents 8.74

Governance

7 Tourism industry and organizations cooperate and interact 12.02

8 [D] presents innovative and/or improved products and services 12.03

Environment9 [D] has a high eco-awareness 12.6410 [D] has a favorable weather 7.96

11 [D] offers a safe environment 6.78

Performance

12 [D] presents an accurate image 9.2713[D] meets my expectations 9.11

14 [D] offers a satisfying tourism experience 6.93



Dominant topic recognition – untrained users agreement test

facebook tripadvisor travbuddy - blog





Online message cues

??? ???


Belief Attitudes



WHICH


HOW

???

Research Objectives

Argument strength

Message sidedness

Message consistency

Trust attitude towards

social media

Attitude of being an online

reputation seeker

Perceived reputation in social media

H2a

H2b

H2c

H4bH1

H3a

H3b

H3c

H4a

Research Model


Online Public Opinions facets: exposure to online contents

Antecedents

Argument strength

Message sidedness

Message consistency


social media


reputation seeker


H2a

H2b

H2c

H4bH1

H3a

H3b

H3c

H4a

Belief T2

Perceived Belief

Change

Belief T1

H5c

H5d

H5a

H5b

Research Model

Consequences


Online Public Opinions facets: exposure to online contents

After exposure knowledge

Antecedents

Data collection


Pilot panel: 10,000 usersUsable: 310

Final panel: 8 groups x 15,000 users = 120,000 users--------------------Total responses: 4,115 Usable responses: 2,5053.4% response rate 313 usable responses per destination

Online survey with Americans internet users gathered from vacationfun.comJuly 23, 2012 to August 20, 2012

detroit kansaslas

vegasnew

orleans orlando phoenixsan

francisco seattle

Section 1: name of a tourism destination: had visited? prior belief about the 5 topic dimensions?

Section 2: subjects were exposed to a list of 20 links Stimuli materials = screenshots of original online conversations related to the given tourism destination. Select and view at least one link.

Section 3: re-evaluation of the 5 topic dimensions + follow-up questions about the study constructs

Section 4: demographic questions

Online questionnaire


[name of the destination] + [topic category keywords]

Online questionnaire: creation of the stimuli materials


DetroitKansas CityLas Vegas

New OrleansOrlandoPhoenix

San FranciscoSeattle

Good value for money. costs + accommodation + tipsCulture. culture + tips

Overall image. trip + experience + tips

Weather. Keywords used: trip + weather + tips

Safety. Keywords used: safety + tips

DetroitKansas CityLas Vegas

New OrleansOrlandoPhoenix

San FranciscoSeattle

Good value for money. costs + accommodation + tipsCulture. culture + tips

Overall image. trip + experience + tips

Weather. Keywords used: trip + weather + tips

Safety. Keywords used: safety + tips

[name of the destination] + [topic category keywords]



sentiment polarity5-point Likert

+ -

From the URLs analysis: the four highest ranked URLs per each of the five topic dimensions have been selected as stimuli materials

Money Culture Image Weather SafetyDetroit L H L L LKansas H H L H LLas Vegas L H H L LNew Orleans H H H L LOrlando H H H L HPhoenix H L H H HSan Francisco H H H H H Seattle H H H L H

L= Low: majority of sentiment expressed on the URLs is negative H= High: majority of sentiment expressed on the URLs is positive



Male 32% Less than $20,000 4.30%Female 68% $20,000-$29,999 6.00%

$30,000-$39,999 6.20%20 years and below 0.50% $40,000-$49,999 9.40%21-25 1.70% $50,000-$74,999 18.90%26-30 3.90% $75,000-$99,999 16.00%31-40 11.70% $100,000-$149,999 14.00%41-50 22.20% $150,000-$199,999 4.30%51 - 60 32.70% $200,000 or more 3.00%61 years and older 27.20% Do not wish to comment 18.00%

Less than high school 0.50% Novice 3.50%High school 9.20% Intermediate User 34.60%Some college, not completed 24.80% Advanced User 43.60%Completed college 34.70% Expert 18.30%Post graduate work 29.60% Use of UGC 79.60%Do not wish to comment 1.30% Not use of UGC 20.04%

Demographic characteristics of the respondents



Stimuli viewed1 22.1%

2 – 5 49.4%6 – 10 23.0%> 10 5.5%

Time spent0 to 5 min. 7%6 to 10 min. 36.2%

11 to 20 min. 39.1%21 to 30 min. 8.5%

31 to 1 h. 4.7%1.01 h. and plus 4.5%

Popular destinations: Las Vegas; New Orleans; Orlando; San Francesco; Seattle

Less popular destinations: Detroit; Kansas; Phoenix

Topic selected:overall imagevalue for moneyculture-traditionsafetyweather

Mean Std. Dev. Coefficient Alpha

ARG_1 3.79 .791 0.891ARG_2 3.66 .838ARG_3 3.65 .841ARG_4 3.83 .821SIDED_1 3.77 .922 0.727SIDED_2 3.78 .900SIDED_3 3.75 .873CONS_1 3.6 .778 0.891CONS_2 3.63 .775CONS_3 3.66 .770CONS_4 3.60 .780P_REP_1 3.88 .722 0.664P_REP_2 3.61 .814P_REP_3 3.64 .785P_CHANGE1 2.71 1.051 0.702P_CHANGE2r 2.24 .834P_CHANGE3r 2.22 .844AT_REP1 4.08 .721 0.878AT_REP2 4.02 .782AT_REP3 3.96 .765AT_REP4 4.12 .766AT_REP5 3.98 .771AT_REP6 3.94 .771

Descriptive and reliability statistics for constructs in the model


Mean Std. Dev. Coefficient Alpha

TRUST_1 3.68 .779 0.808TRUST_2 3.73 .832TRUST_3 3.60 .820TRUST_4 3.59 .942BT1_MONEY 3.26 .881 0.794BT1_CULTURE 3.74 1.100 BT1_IMAGE 3.22 1.078 BT1_SATEFY 3.32 1.104 BT1_WEATHER 3.55 1.054 BT2_MONEY 3.51 .955 0.842BT2_CULTURE 3.84 1.071 BT2_IMAGE 3.31 1.090 BT2_SATEFY 3.49 1.115 BT2_WEATHER 3.82 1.053

Argument strength

Message sidedness

Message consistency


social media


reputation seeker


.457

.068

.330

.055

.220

.527

.365

.470

.581

Belief T2

Perceived Belief

Change

Belief T1

.726

.044

n.s.

- .502

Research Model results

R2 : .338 R2 : .694

R2 : .254

R2 : .277

R2 : .133

R2 : .221

CFI=0.912, TLI=0.900, χ2/df ≤ 2.5, RMSEA=0.067, SRMR=0.097



Hypothesis Group1 = popular2 = less popular

Path Estimate

H1 P_REP AT_REP

12

0.283 0.167

H2a P_REP ARG

12

0.439 0.506

H2b P_REP SIDED

12

n.s.n.s.

H2c P_REP CONS

12

0.335 0.305

H3a ARG AT_REP

12

0.516 0.511

H3b SIDED AT_REP

12

0.331 0.376

H3c CONS AT_REP

12

0.450 0.472

H4a AT_REP TRUST

12

0.588 0.584

H4b P_REP TRUST

12

n.s.0.109**

H5a BT2 BT1

12

0.709 0.732

H5bP_CHANGE BT2

12

0.073** n.s.

H6a BT2 P_REP

12

n.s.n.s

H6b P_CHANGE P_REP

12

-0.497-0.524 ** = significant > 05

Filter: only with who have not visited the destinations

Grouping among popular (Las Vegas; New Orleans; Orlando; San Francesco; Seattle)Not popular destinationDetroit; Kansas; Phoenix

Findings


Operationalization of the reputation construct

Perception of a dominant opinion



Puto -

Re -

1. opinion





Operationalization of the reputation construct

Tourism destination topic dimensions

products &

services

society

environment

governance

performance

+ -

1. good value for

the money

2. satisfying tourism experience

3.safe environment 4. favorable weather

5. local cultures and traditions

Findings


Perception of a dominant opinion

Identification of the online messages cues more: argument’s strength, and message consistency;less: sidedness, and trust

confirmation of prior belief

- Role of the experience with the destination- Type of destinations

Features?

- illusory correlation paradigm- conform to the same view

- time issue

Conclusions


familiarity with the reputation constructlooked at the online dominant opinion

reputation seekers

source of information for the confirmation of prior beliefs

experience with the destination and type of destination

positive effects of online message cues

attitude / antecedents

online features consequences

Future research


Indicators for monitoring• Message cues and feature cues

• Automatic tools• Long term analysis

Model extension• Construct refinement

• Keywords• Sample• Real navigation• Role of type of destinations

Different contexts• Mobile • Issue of reputation power in online media

Management issue• Impact on decision-making

• Reputation risk management


listening and learning about a destination from overwhelming online messages

occasion to discover & social control

Practical implications


Thank [email protected]

Destination Reputation in Online Media: Covered Topics and Perceived Online Dominant Opinion

Social Media

destination reputation

perception of reputation

online contents analysis

message elaboration

dual process theory

theory mccombs

theory connelly

multidimensional experience