ENTER2017 eTourism Conference presentation

1. ENTER 2017 Research Track Slide Number 1
“Don’t Let Me Think!”
Chinese Adoption of Travel Information on Social
Media: Moderating Effects of Self-disclosure
Junjiao Zhanga,
Naoya Itob,
Wenxi Wuc, and Zairong Lid
a Graduate School of International Media, Communication, and Tourism Studies,
Hokkaido University, Japan
junjiaozh@gmail.com
b Research Faculty of Media and Communication, Hokkaido University, Japan
naoya@imc.hokudai.ac.jp
c, d School of Media Science, Northeast Normal University, China
{wuwx613; lizr569}@nenu.edu.cn

2. ENTER 2017 Research Track Slide Number 2
Introduction
Hypotheses development
Research design
Results
Implications
Future research
OUTLINE

3. ENTER 2017 Research Track Slide Number 3
Social Media (1)
• Travel-related information
 User-generated content (UGC);
 Self-information.
1250
Million
Posts with tourism
destination
24.95
Million
Travel-related posts
added location
560
Million
Tourism destination
searching
Data period: 2015/10/01-2016/09/30
Source: Sina & Weibo Data Center. (2016). Retrieved from http://data.weibo.com/report/reportDetail?id=338
Introduction

4. ENTER 2017 Research Track Slide Number 4
Social Media (2)
Data period: 2017/01/15-2017/01/18 http://www.weibo.com/u/2141791335
Sociability InteractivityPersonalization

5. ENTER 2017 Research Track Slide Number 5
Travel Information Adoption （1）
• Information cognitive process
 Dual-route persuasive communication;
 Elaboration likelihood model (ELM)
• Central route: Argument quality； Peripheral route: source credibility;
• ELM is considered feasible and applicable to draw upon travel
information adoption.
• Earlier studies implicitly considered message arguments more important
than source cues for consumers with high involvement (Kitchen et al.,
2014).
Argument
Quality
Source
Credibility
Attitude Behavior
Intention
Elaboration
Likelihood

6. ENTER 2017 Research Track Slide Number 6
RQ1
Argument quality and source credibility, which route is more
effective in travel information adoption on social media?
Data period: 2017/01/15-2017/01/18 http://www.weibo.com/u/2141791335

7. ENTER 2017 Research Track Slide Number 7
Travel Information Adoption （2）
• Social cognitive process
 Social exchange between users;
 Self-disclosure
• Voluntarily disclose self-information to others (Lin et al., 2016);
• A crucial indicator of social exchange (Homans, 1958);
• A weigh of benefits and costs (Homans, 1958) .
 High self-disclosure
• Reciprocal information exchange (Huang, 2016);
• Users’ perceived risk of compromised privacy (Tseng & Wang (2016).

8. ENTER 2017 Research Track Slide Number 8
Self-disclosure:
thoughts,
feelings,
experiences
RQ2
How does users’ self-
disclosure bias the
process of travel
information adoption
on social media?

9. ENTER 2017 Research Track Slide Number 9
Research goals
• To examine which route is more effective in predicting
travel information adoption in social media contexts.
 Develop new insights into the validity of ELM in interpreting travel
information processing on social media from social psychological
perspective.
• To explore the biased process of travel information
adoption influenced by users’ self-disclosure.

10. ENTER 2017 Research Track Slide Number 10
Related Work
Fig. 1. Elaboration
Likelihood Model (ELM)
(Petty & Cacioppo, 1986)
Fig. 2. Information Adoption
Model (IAM) (Sussman &
Siegal, 2003)
Argument
Quality
Source
Credibility
Information
Usefulness
Information
Adoption
Technical
adequacy
Argument
Quality
Source
Credibility
Attitude Behavior
Intention
Elaboration
Likelihood
H3
Hypotheses
development
Self-
disclosure ③
②
②
①

11. ENTER 2017 Research Track Slide Number 11
Dual-route
• Richer media
 Facebook: Less users’ ability to access information; Users’ attention
from message itself to source (Chung et al., 2015).
 E-WOM from social media: Perceived low credibility of EC-eWOM → SM-
eWOM from friends (Yan et al., 2016).
• Chinese travellers
 Socialization: Travel-related social media (e.g., Qyer) in China facilitates
socialization in travel activities (Li et al., 2015).
 Performance: Various travel accounts; Much more trust in peer reviews
than British travellers (Michopoulou & Moisa, 2016).
H4 Source Credibility > Argument quality

12. ENTER 2017 Research Track Slide Number 12
Technical Adequacy
• Predictor of information cognitive process
 Perceived interactivity: Two-way communication drives recommended
messages processing (e.g., Doong et al., 2009);
 Perceived personalization: Meeting user preferences increases trust in
service encounters (Li et al., 2013);
 Perceived sociability: Message delivery fulfills user needs for sociability
and, in turn reinforces product involvement on social media (Lee, 2017).
H5 Technical Adequacy → Argument quality
H6 Technical Adequacy → Source Credibility

13. ENTER 2017 Research Track Slide Number 13
Self-disclosure
• Reciprocal benefit-exchanging process
 H7 Stronger effect of argument quality —— Low self-disclosure
 H8 Stronger effect of source credibility —— High self-disclosure
High
self-disclosure
Social
support
Perceived benefits
Confidence to senders
Useful
information
Disclose first Greater others’
disclosure
Trustworthy
sources
(Huang, 2016; Chen & Shen, 2015; Lin et al., 2016)
Low
self-disclosure
Perceive more
risk or costs
Information
argument
(Tseng & Wang, 2016)

14. ENTER 2017 Research Track Slide Number 14
Research Model
Technical
Adequacy
Argument
Quality
Source
Credibility
Travel
Information
Adoption
Perceived
Information
Usefulness
H4:SC>AQ
H3(+)Self-
disclosure
Fig. 3. Research model

15. ENTER 2017 Research Track Slide Number 15
• Measurement
 Multi-item approach & 7-point Likert scale
• Technical adequacy: 2nd-order factor; Three elements.
• Self-disclosure: a formative variable with five items (amount, depth, honesty,
intent, and valance).
• Data collection
 Online survey in China in January 2016;
 Valid sample size: 357 (out of 524);
 Screening criteria: Participants who used social media to adopt
travel information in the past 12 months.
• Data analysis
 Measurement model → SEM → Multi-group analysis
Research design Research
design

16. ENTER 2017 Research Track Slide Number 16
Results (1) Results
Characteristics Frequency %
Type of social media Wechat 333 93.3
Weibo 259 72.5
QQ 243 68.1
Baidu Baike 175 49.0
Video website 134 37.5
Zhihu 129 36.1
Douban 89 24.9
Renren 19 5.3
Others 16 4.5
Momo 8 2.2
Type of travel-related
social media
Comprehensive social media (e.g., Weibo; Wechat) 205 57.4
Comprehensive OTA (e.g., Ctrip.com) 203 56.9
Vertical search (e.g., Qunar.com) 179 50.1
Comprehensive search engine (e.g., Baidu) 126 35.3
Travel-related UGC (e.g., Qyer; Mafengwo) 106 29.7
Sub-website based on search engine (e.g., lvyou.baidu.com) 82 23.0
E-commerce platform (e.g., Alitrip.com) 66 18.5
Table 1. Experience in social media use (N=357)

17. ENTER 2017 Research Track Slide Number 17
Results (2)
Technical
Adequacy
Argument
Quality
Source
Credibility
Travel
Information
Adoption
Perceived
Information
Usefulness
Perceived
Interactivity
Perceived
Sociability
0.719***
0.636***
0.710***
0.840***
R2=0.404
R2=0.505
R2=0.457 R2=0.517
Second-order factor
*p<.05, ***p<.001
Perceived
Personalization
• H1-H6 were significantly supported.
Results
Fig. 4. Results of structural equation model
χ2(197)=320.84, χ2/df=1.629,
p<.001, GFI=0.924,
NFI=0.931, CFI=0.972,
RMSEA=0.042

18. ENTER 2017 Research Track Slide Number 18
Results (3)
Moderator Path
High self-disclosure
(n=161, M=5.31)
Low self-disclosure
(n=196, M=3.60)
t-Value Result
Self-
disclosure
AQ →
PIU
0.597* 0.114ns 1.639ns Unsupported
SC → PIU 0.106ns 0.517*** -2.364* Unsupported
*p<.05, ***p<.001
• H7 Stronger effect of argument quality on PIU—— Low self-disclosure
• H8 Stronger effect of source credibility on PIU—— High self-disclosure
Table 2. Structural path coefficient differences

19. ENTER 2017 Research Track Slide Number 19
Theoretical Implications (1)
• Findings show that the extended ELM with technical adequacy is
powerful in predicting travel information adoption in social media
contexts.
• Findings enrich the knowledge of source credibility, confirm its more
effective role than argument quality in predicting travel information
adoption on social media in China, therefore identifying the take-the-
best decision principle.
 Information overload → Users’ cognitive load in information assessment (Samson &
Kostyszyn, 2015).
Implications

20. ENTER 2017 Research Track Slide Number 20
Theoretical Implications (2)
• This study contributes an exploration in understanding the interaction
between self-disclosure and travel information processing on social
media.
• Self-disclosure negatively rather than positively moderated the effect
of source credibility on perceived information usefulness.
 Utilitarian: Hope less self-disclosure but more favorable information (Lee & Cranage,
2011);
 Superficial information: May not helpful in building more trust to sources ;
 Confidence: High self-disclosure = more experience in privacy control and setting
(Liang, Shen, & Fu, 2016);
 Default trust: Groups of close and trusted persons in China = neglect the
assessment towards source credibility.

21. ENTER 2017 Research Track Slide Number 21
Practical Implications
• Source credibility highly determines potential travellers’ decision-
making process. Thus, it is essential for managers to take insights into
how consumers process information on social media in particular how
consumers perceive source credibility embedded in travel
information.
• Precision marketing would be more effective according to consumers’
different levels in self-disclosure.
 High self-disclosure: Rich content & default trust in a community;
 Low self-disclosure: Recommend experienced users with similar interests.

22. ENTER 2017 Research Track Slide Number 22
Future Research
• Limitation: Participant sample.
• What does self-disclosure mean for Chinese in adopting
travel information?
• Apart from information-oriented factors, how do other
cognitive factors exert their power in individuals’ adoption
of travel information?
Future research

23. ENTER 2017 Research Track Slide Number 23
THANK YOU VERY MUCH!
Junjiao Zhang
PhD Candidate, Graduate School of International Media, Communication, and Tourism Studies,
Hokkaido University, Japan
junjiaozh@gmail.com